USBR baffle block

Numerical investigation of hydraulic jumps with USBR and wedge-shaped baffle block basins for lower tailwater

하부 테일워터를 위한 USBR 및 쐐기형 배플 블록 분지를 사용한 유압 점프의 수치적 조사

Muhammad Waqas Zaffar; Ishtiaq Hassan; Zulfiqar Ali; Kaleem Sarwar; Muhammad Hassan; Muhammad Taimoor Mustafa; Faizan Ahmed Waris

Abstract


graphic

The stilling basin of the Taunsa barrage is a modified form of the United States Bureau of Reclamation (USBR) Type-III basin, which consists of baffle and friction blocks. Studies revealed uprooting of baffle blocks due to their vertical face. Additionally, the literature highlighted issues of rectangular face baffle blocks: less drag, smaller wake area, and flow reattachment. In contrast, the use of wedge-shaped baffle blocks (WSBBs) is limited downstream of open-channel flows. Therefore, this study developed numerical models to investigate the effects of USBR and WSBB basins on the hydraulic jump (HJ) downstream of the Taunsa barrage under lower tailwater conditions. Surface profiles in WSBB and modified USBR basins showed agreement with previous studies, for which the coefficient of determination (R2) reached 0.980 and 0.970, respectively. The HJ efficiencies reached 57.9 and 58.6% in WSBB and modified USBR basins, respectively. The results of sequent depths, roller length, and velocity profiles in the WSBB basin were found more promising than the modified USBR basin, which further confirmed the suitability of the WSBB basin for barrages. Furthermore, WSBB improved flow behaviors in the basin, which showed no fluid reattachment on the sides of WSBB, increased wake regions, and decreased turbulent kinetic energies.

Keywords


barrage, geometry, hydraulic jump, stilling basin, wedge-shaped baffle blocks

INTRODUCTION


Barrages in Pakistan were built about 50–100 years ago and play an important role in the economy. However, as time passed, the stability of these barrages was compromised due to hydraulic and structural deficiencies (Zaidi et al. 2011). Similarly, Taunsa Barrage Punjab, on the mighty river Indus, is one of the major hydraulic structures, which was constructed about 65 years ago. The barrage was designed for a design discharge capacity of 28,313 m3/s, and its stilling basin was a modified form of the United States Bureau of Reclamation (USBR) Type-III basin that consisted of USBR impact friction and baffle blocks. These arrangements dissipate excessive kinetic energy, enhance turbulence, kill rollers, and stabilize the hydraulic jump (HJ) even in case of less tailwater depth. The barrage consists of 64 bays, and the total width of the barrage between the abatements is 1,324.60 m. Of total width, 1,176.5 m is a clear waterway (Zaffar & Hassan 2023a). Figure 1 shows the typical cross-section of the Taunsa barrage.

Figure 1

Typical cross-section of the Taunsa barrage.

Typical cross-section of the Taunsa barrage.

Soon after the barrage operation in 1958, multiple problems occurred on the barrage downstream, such as uprooting of the impact baffle blocks due to their vertical face, damage to the basin’s floor, lowering of tailwater levels, and bed retrogression (Zulfiqar & Kaleem 2015). During 1959–1962, repair works were carried out to cater to these issues, but the problems remained persistent. To resolve these issues, the Punjab Government constituted a committee of experts in 1966 and 1973, but no specific measures were taken, and the issues continued to aggravate (Zaidi et al. (2004). Additionally, these traditional impact blocks also face flow reattachment on the sides that decreases the drag force (Frizell & Svoboda 2012). On the contrary, after investigating the wedge-shaped baffle blocks (WSBBs) downstream of pipe outlets, research scholars (Pillai et al. 1989Verma & Goel 2003Verma et al. 2004Goel 2007Goel 2008Tiwari et al. 2010) reported that these blocks increased the energy dissipation and created more eddies and wake regions on either side. These studies further mentioned that upon the use of WSBBs, the overall length of stilling basins was also reduced from 15 to 25%.

Energy dissipation is the most common issue faced in the design of hydraulic structures. The kinetic energy typically comes from the upstream of the dams (El Baradei et al. 2022), spillways (Sutopo et al. 2022), chute, sluice gates, and weirs, which are further induced by the HJ and its turbulent structure (Elsaeed et al. 2016). In the HJ, flow suddenly changes from supercritical to subcritical conditions which dissipate the energy of the upstream flow, thereby saving the hydraulic structures from damage. The HJ occurs when Froude Number (Fr) falls below unity, which is the ratio of inertia to gravitational forces that can be calculated by the following equation (Bayon-Barrachina & Lopez-Jimenez 2015Bayon-Barrachina et al. 2015).

formula

(1)

where vh, and g are stream-wise velocities, flow depth, and acceleration due to gravity, respectively. Hager & Sinniger (1985) investigated characteristics of the HJ for abrupt changes in horizontal bed and proposed the following equation to compute the efficiency  of HJs.

formula

(2)

where Fr1 is the Froude number in the supercritical flow before the HJ.

Bakhmeteff & Matzke (1936) developed HJ similarity models and proposed dimensionless Equation (3) for the free surface profile of HJs.

formula

(3)

where  is the water depth at x (hi) and the variable X is the dimensionless longitudinal coordinates (x), as shown in the following dimensionless equations, respectively.

formula

(4)

formula

(5)

where D is the gate opening and h1 and h2 are the water depths in supercritical and subcritical regions, respectively. X1 and X2 are the functions of variable X, and their values can be calculated at the toe of the HJ and the end of the roller region, respectively. The components of Equations (4) and (5) are shown in Figure 2.

Figure 2

Schematic diagram for the dimensionless free surface profiles of HJs.

Schematic diagram for the dimensionless free surface profiles of HJs.

Habibzadeh et al. (2012) conducted experiments to investigate the role of baffle blocks for submerged HJs and energy dissipation downstream of low-head hydraulic structures. Chachereau & Chanson (2011) and Wang & Chanson (2015) investigated free surface profiles and turbulent fluctuation within the HJ for a wide range of initial Froude number (Fr1). The velocity profiles showed a wall jet-like profile, and turbulence intensities were high due to the fluctuations at the free surface. Maleki & Fiorotto (2021) developed a semi-empirical method to investigate HJs on a rough bed. The results showed that the characteristic length scale was linearly changing with Fr1Macián-Pérez et al. (2020b) carried out experiments on the USBR-II stilling basin to investigate the characteristics of HJs. The results of sequent depths and HJ efficiency agreed with the experimental studies, which reached 99.2 and 97%, respectively. The results of the dimensionless free surface profile also agreed with the previous studies for which the value of the coefficient of determination (R2) reached 0.979. Murzyn & Chanson (2009) conducted experiments for a wide range of Fr1 up to 8.3 to investigate bubbly and turbulence structure within the HJ. The results showed that void fraction (Cmax) and bubble frequency (Fmax) were found in the developing region, and vertical interfacial velocity agreed with the wall jet-like profile. Qasim et al. (2022) conducted experiments on bed discordance downstream of different weirs. The results indicated that as the bed discordance increased, the dimensionless flow depth decreased downstream of the discordance, which increased the Froude number. The results further showed that as the configuration of bed discordance was changed, the free surface profiles were also changed, which affected the flow depths and velocity profiles. Bhosekar et al. (2014) conducted experiments to investigate the characteristics of discharge downstream of orifice spillways. The results showed that free surface profiles were not elliptical due to the flat curve near the gate opening. The results further indicated that the flat curve developed a negative pressure on roof profiles, which reduced the discharge capacity of the spillway.

To stabilize the HJ in the stilling basins, different shapes of baffle blocks are employed, i.e., baffle blocks (Habibzadeh et al. 2012), friction blocks (Chaudary & Sarwar 2014), end sill (Mansour et al. 2004) and vertical sill (Alikhani et al. 2010), splitter blocks (Verma & Goel 2003), curved (Eloubaidy et al. 1999), T-shaped and triangular (Tiwari & Goel 2016), and WSBB (Pillai et al. 1989Goel 2007Goel 2008). These arrangements control the HJs in case of fewer tailwater depths (Peterka 1984) and minimize the erosion downstream of structures (Zaffar et al. 2023). Sayyadi et al. (2022) investigated HJ characteristics for negative steps in the stilling basin. The results showed that the negative step increased the energy dissipation up to 11%. Pillai et al. (1989) compared three different stilling basins for the Fr1 up to 4.5. The results showed that the stilling basin with the WSBB reduced the scour and overall length of the basin. Goel (2008)Goel (2007), and Tiwari et al. (2010) conducted experiments to investigate HJ characteristics downstream of square and circular pipe outlets using WSBBs. The results showed that as compared to the impact USBR-VI basin, the WSBB basin spread the fluid efficiently in the lateral direction and reduced the basin length up to 50%.

In the former section, the experimental studies on HJs, velocity distribution, free surface profiles, and turbulent kinetic energy (TKE) are discussed, which could be assisted by Computational Fluid Dynamics (CFD) models (Ghaderi et al. 2020). Furthermore, over these hydraulic structures, the flow is very complex and associated with secondary currents, which characterized it as highly turbulent in all directions. Hence, using laboratory and field experiments, it is hard to accurately measure the free surface profile, velocities, secondary currents, and TKE over these hydraulic structures (Jothiprakash et al. 2015). Furthermore, physical experiments and on-site measurements are usually expensive and time-consuming. In contrast, the improvements in computational speed, storage, and turbulence modeling have made CFD a viable complementary investigation tool for hydraulic modeling (Ghaderi et al. 2021). Consequently, the use of numerical modeling tools such as Open Foam (Bayon-Barrachina & Lopez-Jimenez 2015), ANSYS Fluent (Aydogdu et al. 2022), and FLOW-3D (Hirt & Sicilian 1985) has become prevalent to get hydraulic characteristics of grade-control structures. Such modeling tools are helpful, especially when the basic fundamental equations are unable to provide desired outputs, like in the case of multifaceted geometries (Herrera-Granados & Kostecki 2016). So far, many researchers have employed numerical models in the hydraulic investigations of HJs and energy dissipation, but only a few of the latest studies are highlighted here. FLOW-3D numerical models were employed to investigate the HJ (Zaffar & Hassan 2023a) and baffle blocks (Zaffar & Hassan 2023b) for different stilling basins of the Taunsa barrage. These studies focused on velocity distribution, TKE, free surface profiles, energy loss energy, and the effects of baffle blocks on the HJ characteristics. Macián-Pérez et al. (2020a) carried out a numerical investigation on a high Reynolds of 210,000 to study the HJ characteristics. Upon comparison, the FLOW-3D model showed 93% accuracy in the roller length of HJs. The results also indicated 94.2 and 94.3% accuracy for sequent depths and HJ efficiency, respectively. Nikmehr & Aminpour (2020) examined the HJ characteristics on rough beds using FLOW-3D, and compared results with the experiments. The results indicated that roughness height and its distance affected the HJ length. Gadge et al. (2018) conducted a numerical study to investigate the impact of roof profiles on the discharge capacity of orifice spillways and validated the models with experimental results. The study revealed that in addition to the pond level and height of orifice (d), the bottom and roof profiles also affected the discharge coefficient (Cd).

From the literature review, it is found that only a few studies are conducted on the flow characteristics downstream of the Taunsa barrage (Zaidi et al. 20042011Chaudhry 2010). These studies were carried out in laboratory flume and investigated the effects of tailwater on the location of HJs. However, the studies were lacking in providing the data for other essential hydraulic parameters, i.e., velocity distribution, free surface profiles, TKE, and relative energy loss in the stilling basin. On the contrary, the literature has revealed many experimental and numerical studies on different shapes of baffle blocks downstream of open-channel flow, but the use of WSBB downstream of river diversion barrage is found limited. In the previous studies (Pillai et al. 1989Verma & Goel 2003Verma et al. 2004Goel 20082007Tiwari et al. 2010), these blocks have only been tested downstream of pipe outlet basins for the initial Froude number of 4.5. Therefore, in the present study, FLOW-3D numerical models are developed to investigate the effects of presently available USBR baffle blocks in the stilling basin of the Tuansa barrage. Due to the uprooting problems of these blocks, the study also investigates the suitability of WSBBs downstream of the studied barrage and draws a comparison between the results of modified USBR and WSBB basins. In this study, based on results from the literature, WSBB with a vertex angle of 150° and cutback angle of 90° is applied for Fr1 up to 6.64. The main objective of this study is to investigate HJs and flow behavior with USBR baffle blocks and WSBB downstream of an investigated barrage at 44 m3/s discharge. At 44 m3/s discharge, the numerical models are operated at the minimum tailwater level of 129.10 m, and investigated free surface profiles, sequent depths, roller lengths, HJ efficiency, velocity profile, and TKE in the two different stilling basins.

MATERIALS AND METHODS


Existing and proposed stilling basins, appurtenances

Listen

The present numerical models are developed downstream of the Taunsa barrage, Pakistan. The stilling basin of the barrage includes USBR impact friction and baffle blocks (Zaffar & Hassan 2023bZaffar et al. 2023). In the basin, floor level and weir crest are fixed at 126.79 and 130.44 m, respectively. The slopes of upstream and downstream weir glacis are maintained at 1:3 and 1:4 (H:V), respectively. In both the studied basins, the blocks are installed 14.63 m away from the centerline of the crest and are placed in a staggered position. The overall length and height of the USBR blocks is 1.37 m as shown in Figures 3(a) and 3(b). Additionally, between the two staggered rows of baffle blocks, a 1.37-m distance is maintained, while the top width of all the USBR blocks is 0.46 m, which is angled at 45° from the rear side. On the other hand, in the WSBB basin, WSBB is placed at the locations of impact USBR baffle blocks. Furthermore, in both the studied basins, two staggered rows of friction blocks are also placed at the basin’s end about 28.95 m away from the weir’s crest. These friction blocks are 1.37 m long, 1.22 m wide, and 1.37 m high. The top surface of these blocks is identical to their bottom. The overall length, width, and height of the WSBB are kept at 1.37 m, and a detailed geometry of the investigated WSBB can be seen in Figures 3(c) and 3(d). Currently, for the investigated WSBB, a vertex angle of 150° and a cutback angle of 90° are employed.

Figure 3

Baffle block geometry for the basins: (a) top view of USBR baffle blocks, (b) isometric view representing front of USBR baffle blocks, (c) top view of WSBBs and (d) isometric view representing front of WSBBs.

Baffle block geometry for the basins: (a) top view of USBR baffle blocks, (b) isometric view representing front of USBR baffle blocks, (c) top view of WSBBs and (d) isometric view representing front of WSBBs.

Numerical model implementation

Environmental flows are governed by the laws of physics and represented by Navier–Stokes Equations (NSEs), which are inherently nonlinear, time-dependent, and contain three-dimensional partial deferential schemes (Viti et al. 2018). These partial differential equations explain the procedures of continuity, momentum, heat, and mass transfer. For one- and two-dimensional models, these equations can be solved analytically, while for the solution of three-dimensional models, CFD models are employed to discretize the NSEs. In these models, flow equations, i.e., NSEs and continuity equations, are discretized in each cell. Generally, these models start with a mesh, which further contains multiple interconnected cells in the employed mesh blocks. These meshes subdivide the physical space into small volumes, which are associated with several nodes. The values of unknown parameters are stored on these nodes, such as velocity, temperature, and pressure. Different numerical techniques are available to discretize the NSEs, i.e., Direct Numerical Simulation (DNS) (Jothiprakash et al. 2015), Large Eddy Simulation (LES) (Ghosal & Moin 1995), and Reynold Averaged Navier–Stokes (RANS) Equation (Kamath et al. 2019). However, as compared to DNS and LES models, due to less computation cost and simulation time, the RANS model is frequently used in river and hydraulic investigations. Using the RANS model, two additional variables are generated, for which turbulence closure models are usually employed (Carvalho et al. 2008). These models find closure by averaging the Reynolds stress terms in NSEs and append additional variables for turbulent viscosity and transport equations.

Presently, FLOW-3D models are developed to investigate the effects of different shapes of baffle blocks on HJ downstream of the river diversion barrage. The models employ RANS equations to solve algorithms and equations of incompressible fluid in each computational cell. To further address the additional terms, i.e., Reynolds stresses and turbulent viscosity, the Renormalization group (RNG Kɛ) method is applied. For the discretization of RANS and other algorithms, at present, the Volume of Fluid (VOF) method (finite volume method (FVM)) is employed, while the equations of the controlled volume are formulated with area and volume porosity functions. This formulation is called the ‘Fractional Area/Volume Obstacle Representation’ (FAVOR) method (Hirt & Sicilian 1985). The proceeding section describes the equations used for the present models.

Assuming the flow is steady and neglecting the fluctuation of specific weight (⁠ = 0), Equations (6) and (7) are used for the turbulent flow (Carvalho et al. 2008).

formula

(6)

formula

(7)

Following the above equations, it is apparent that these relationships consist of three momentum and one continuity equation, in which there are 10 unknowns (puv, w, and six Reynolds stress components). In the present study, the flow is considered incompressible, which implies the following equation to solve the flow domain (Viti et al. 2018).

formula

(8)

In Equations (6)–(8uv, and w, are velocity components in xy, and z directions, respectively.  and p are total pressure and fluid density while the terms  are known as the Reynolds stresses. AxAy, and Az are flow areas while R,⁠, and RSOR are the model’s coefficient, flow generic property, and mass source term, respectively.

Turbulence modeling and free surface tracking

Six turbulence models are available in FLOW-3D, which employs numerous equations to solve the closure problems. Among various models, the two-equation turbulence models such as standard Kɛ (Bradshaw 1997, RNG Kɛ (Yakhot et al. 1991), and Kω (Wilcox 2008) are widely used in hydraulic investigations.

The standard Kɛ and RNG Kɛ models solve transport equations for TKE and its dissipation. The formulation of both models is identical, but the former derives model coefficients empirically. However, RNG K–ɛ applies a statistical approach to derive the transport equations explicitly, which has shown better capability in low-turbulence and high-shear regions (Macián-Pérez et al. 2020a2020b) than the standard K–ɛ model. In contrast, the Kω model was implemented for stream-wise pressure gradient and near-wall boundaries (Wilcox 2008). The model replaces turbulent dissipation rate with turbulent frequency. In the Kω model, the values of TKE and turbulent frequency are specified at the inlet boundaries. The above-mentioned turbulence models were investigated by Macián-Pérez et al. (2020b) for flow behaviors in the USBR-II stilling basin and the study indicated that the RNG K–ɛ model showed better accuracy. Also, RNG K–ɛ (Macián-Pérez et al. 2020a) showed more promising results for a grid convergence index (GCI), free surface, roller lengths, and HJ efficiency. Additionally, the RNG K–ɛ model predicted good results in flow rate, free surface profiles, and velocity profiles. Based on bibliographical results, this study also employed the RNG K–ɛ model, for which the following transport equations (Equations (9) and (10)) are utilized for TKE (K) and its dissipation (ɛ), respectively (Macián-Pérez et al. 2020a).

formula

(9)

formula

(10)

where  is the coordinate in the x direction;  is the dynamic viscosity;  is the turbulent dynamic viscosity; K is the turbulent kinetic energy;  is the turbulent dissipation;  is the fluid density, and  is the production of TKE. Finally, the terms⁠, ⁠, ⁠, and  are model parameters whose values are given in Yakhot et al. (1991).

For free surface modeling, the VOF method is employed. VOF applies an additional variable, which is called fraction of fluid (F), in which F represents the proportion of fluid. To compute F in the domain, the following equation (Hirt & Sicilian 1985) is used:

formula

(11)

In FLOW-3D, the fluid fraction (F) in each cell is usually presented by three possibilities:

  • (A)F = 0, cell is empty.
  • (B)F = 1, a cell is fully occupied by fluid.
  • (C)0 < F < 1, cell represents the surface between the two fluids.

One fluid (water) with a free surface is considered in the present models, for which FLOW-3D automatically selects the free surface method from the availableVOF advection scheme. For the free surface tracking, 0.5 value is assigned in each computation cell.

Pressure velocity coupling

One of the major issues in solving the NSEs is pressure–velocity coupling, and for that, a network of algorithms (SIMPLE (Patankar & Spalding 1972) and PISO (ISSA 1985)) has been developed. These above-mentioned algorithms use under- and over-relaxing factors for pressure correction in the continuity and momentum equations, which contain large memory. Additionally, due to the relaxation factors, sometimes the solution becomes unstable and does not find convergence. On the contrary, FLOW-3D employs the Generalized Minimum Residual Method (GMRES) (Joubert 1994) because it possesses good convergence, high speed, and uses less memory. Additionally, GMRES does not apply any relaxation factor and possesses an additional algorithm, ‘Generalized Minimum Residual Solver (GCG),’ to treat the viscous terms.

Model geometry

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The solid geometry of the barrage bay was designed in AutoCAD and converted into a stereo lithography file. Before importing the stereo lithography file into FLOW-3D, it was tested in Netfabb-basic software to remove any holes, facets, and boundary edges. Figures 4(a) and 4(b) show stereo lithography files used for the studied models.

Figure 4

Geometry details of the studied stilling basins: (a) modified USBR baffle block basin and (b) WSBB basin.

Geometry details of the studied stilling basins: (a) modified USBR baffle block basin and (b) WSBB basin.

Meshing and boundary condition

The structured rectangular hexahedral mesh was employed to resolve the geometry and flow domain. To resolve the flow domain, a coarse mesh block was initiated upstream of the barrage (Xmin = 10 m) which ended at the upstream side of the gate (Xmax = 32.90 m). However, the fine mesh block was started from Xmin = 32.90 m which was extended up to the basin’s end (Xmax = 71 m). In total, 60 m of the model domain was simulated, out of which 22.90 m comprised upstream while the remaining included downstream side. For discharge measurement, mesh sensitivity analysis was performed. The blocks with coarse meshes were initially employed to calculate the volume flow rate (Q). The total number of mesh cells used in the coarse mesh block was 1,108,705. Out of 1,108,705 mesh cells, 481,000 cells were employed for the upstream block, while 627,705 mesh cells were utilized for the downstream mesh block. On the contrary, upon the use of fine mesh blocks, a total of 2,991,820 mesh cells were employed, out of which 481,000 cells were contained in the upstream mesh block while 2,510,820 cells were employed on the downstream side. Figure 5 shows mesh grids employed for flow and solid domains.

Figure 5

Meshing setup of the modeling domain.

Meshing setup of the modeling domain.

It is essential to mention that in both meshing scenarios, fine mesh blocks were used on the downstream side of the bay because the focus of the present investigation was made around the baffle blocks and in the HJ regions. The details of mesh cell size and mesh quality indicators for the various mesh blocks are provided in Tables 1 and 2, respectively. Notably, except for discharge analysis, the results of other hydraulic parameters are produced from the fine meshing.

Table 1

Details of mesh blocks and cell sizes

Mesh blockNumber of cellsMaximum adjacent ratioMaximum aspect ratio
Block-1 X = 196; Y = 65; Z = 37 X Y Z X–Y Y–Z Z–X 
1.0 1.0 1.0 1.999 1.0 1.993 
Block-2 X = 261; Y = 130; Z = 74 1.0 1.0 1.0 1.0 1.0 1.0 

Table 2

Meshing quality indicators for various mesh blocks

ScenariosMesh block-1 (cell characteristics)Mesh block-2 (cell characteristics)
Coarse meshing Δx (m) Δy (m) Δz (m) Δx (m) Δy (m) Δz (m) 
0.142 0.284 0.284 0.142 0.284 0.284 
Fine meshing Δx (m) Δy (m) Δz (m) Δx (m) Δy (m) Δz (m) 
0.142 0.284 0.284 0.142 0.142 0.142 

A vertical gate of 18.5-m width, 0.53-m length, and 6.10-m height was mounted upstream of the weir crest. Pond levels of 135.93 and 136.24 m were maintained for free and orifice flows, respectively. Table 3 shows the conditions used for models’ operation.

Table 3

Free and gated flow conditions for operation of the simulations (Zaffar & Hassan 2023b)

Discharge through barrage (m3/s)Single bay discharge (m3/s)Pond level (m)Tailwater levels for jump formation (m)Gate opening (m)Turbulence model
28,313 444 135.93 133.80 Free flow RNG K–ɛ 
2,831 44 136.24 129.10 0.280 RNG K–ɛ 

For the first mesh block, the upstream and downstream boundaries were set as pressure (P), while for the second block upstream boundary was set as symmetry (S). The lateral sides were set as rigid boundaries (W), and no-slip conditions were expressed as zero tangential and normal velocity (u=v=w = 0), where uv, and w are the velocities in xy, and z directions, respectively. These boundaries indicate a wall law velocity profile, which further expresses that the average velocity of turbulent flows is proportional to the logarithm of the distance from that point to the fluid boundary. For all variables (except pressure (P) (which was set to zero), upper boundaries (Zmax) were set as atmospheric pressure to allow water to null von Neumann. For both mesh blocks, the lower boundaries (Zmin) were set as walls.

For the present models, the stability and convergence at each iteration were checked by Courant number (Ghaderi et al. 2020), which affected the time steps from 0.06 to 0.0023 and 0.015 to 0.0025 for free and gated flow, respectively. It is worth mentioning here that for the free flow analysis of higher discharge such as 444 m3/s, the steady state solution can only be achieved by mass-averaged fluid kinetic energy (MAFKE) and volume flow rate (VFR) at the inlet and outlet boundaries. Therefore, the time at which the MAFKE and VFR reach the steady state is assigned as the simulation time (Ts) of models. Presently, VFRs at the inlet and outlet boundaries are considered as the stability and convergence indicators. Based on the criterion mentioned above, the present free and gated models achieved hydraulic stability at Ts = 60 s while the actual time (Ta) of models ranged between 30 and 48 h. However, to accommodate free surface fluctuations, the models were run for Ts = 80 s.

Models’ verification and validation

Analysis of design discharge

For performance assessment of the numerical models, He/Hd = 0.998 (Johnson & Savage 2006Gadge et al. 2019Zaffar & Hassan 2023a2023b) was implemented for free flow analysis, where He and Hd are effective and designed heads, respectively. This was the design discharge of the Taunsa barrage, for which the models were operated on the pond and tailwater levels of 135.93 and 133.8 m, respectively, as provided in Table 3.

Gated flow modeling

Computational discharge is of paramount importance in hydraulic modeling, and the following discharge formula is used for gated flow operations (Gadge et al. 2018). To model 44 m3/s of discharge, gate opening and designed head for orifice are set at D = 0.280 m and Hd = 136.24 m, respectively. Figure 6 illustrates the typical cross-section for gated flow operations.

formula

(12)

where Q (m3/s) is discharged through the orifice opening, A (m2) is the area of the orifice, g (m/s2) is the acceleration due to gravity and hc is the centerline head (hc = HdD/2). The values of coefficients of discharge (Cd) used and simulated were 0.816 and 0.819, respectively, and were found well within the range of Cd values calculated by Bhosekar et al. (2014).

Figure 6

Cross-section showing gated flow through the orifice.

Cross-section showing gated flow through the orifice.

RESULTS AND DISCUSSION

Discharges and flow evolution

Figure 7 shows the time instant of flow evolution for designed discharge. At the start of the simulation, due to the inlet velocity, the free surface was found to be changed. However, when it reached a steady state, a fully developed flow on the downstream glacis was achieved, as shown in Figure 7. A stable free jump was observed at Ts = 60 s for free and gated flow, and the free surface on the downstream side was found to be stable with little fluctuation. The accuracy of FLOW-3D simulations was checked by comparing those discharges with designed values. At Ts = 80 s, the modified USBR baffle block basin underestimated the discharge, which reached 440.48 m3/s and displayed a 0.80% error. Similarly, at Ts = 80 s, for the WSBB basin, the model produced 440.17 m3/s discharge, in which the maximum error reached 0.893%. However, upon the use of coarse meshing, the errors in the computed discharge were increased, which reached −5 and −4% in modified USBR and WSBB basins, respectively. The free flow analysis of modified USBR and WSBB models showed acceptable validation with the designed flow, which allowed us to run the models for orifice discharge.

Figure 7

Flow evolution at the designed flow: USBR basin (a–c) and WSBB basin (d–f).

Flow evolution at the designed flow: USBR basin (a–c) and WSBB basin (d–f).

For the gated flow, on using fine meshing with similar meshing and boundary conditions, the modified USBR basin produced 44.14 m3/s of discharge, for which the maximum error reached 0.32%. However, in the WSBB basin, the numerical model underestimated the flow, which displayed only a 1.14% error. The evolutionary process of gated flows is shown in Figure 8. Based on the validation results of free and gated flows, further analysis was performed on the characteristics of HJs in the two different basins, and their results were compared with the relevant literature.

Figure 8

Evolutionary process of orifice discharge: USBR basin (a–c) and WSBB basin (d–f).

Evolutionary process of orifice discharge: USBR basin (a–c) and WSBB basin (d–f).

Free surface profiles

Due to the limited results of investigated hydraulic parameters on the studied barrage, the models’ results are compared with the previous relevant experimental and numerical studies. For such comparison, the models require some similarity in boundary and initial conditions, as obtained from Bayon-Barrachina & Lopez-Jimenez (2015) and Wang & Chanson (2015). Similar to the studies by Bayon-Barrachina & Lopez-Jimenez (2015) and Wang & Chanson (2015), in the present gated models, the upstream and downstream initial conditions are set to fluid elevation, i.e., pond and tailwater level, with hydrostatic pressure boundaries, while upstream boundaries are set to atmospheric pressure. Additionally, the sides and bottom are set to wall boundaries as described in Bayon-Barrachina & Lopez-Jimenez (2015) and Wang & Chanson (2015). However, the present models differ from the basin appurtenances as the compared studies have investigated HJ and other parameters on the horizontal flat beds. Furthermore, Bayon-Barrachina & Lopez-Jimenez (2015) and Wang & Chanson (2015) have investigated hydraulic parameters such as sequent depths, roller lengths, free surface profiles, energy dissipation, and TKE for Fr1 of 6.10 and 3.8 < Fr1 < 8.5, respectively. Similar to the above-mentioned study, the present modified USBR and WSBB basins are investigated for the Fr1 of 6.5 and 6.64, respectively. Hence, to confirm the results of free surface profiles, the studies of Bayon-Barrachina & Lopez-Jimenez (2015) and Wang & Chanson (2015) are utilized, for which the relevant discussion is made in the proceeding paragraphs.

Using Equation (3) of Bakhmeteff & Matzke (1936), the free surface profiles of HJs were obtained by the VOF method. Figure 9 compares the results of free surface profiles with Bayon-Barrachina & Lopez-Jimenez (2015) and Wang & Chanson (2015). The results of the present model agreed well with Bayon-Barrachina & Lopez-Jimenez (2015) (coefficient of determination (R2) = 0.992), for which the value of R2 in WSBB and USBR basins reached 0.980 and 0.970, respectively. Similarly, after comparing free surface profiles with Wang & Chanson (2015), the results of the present model were found to be more promising. However, as compared to the USBR basin, the results of free surface profiles in the WSBB basin showed more agreement with the compared studies, as can be seen in Figure 9.

Figure 9

Comparison of dimensionless free surface profiles of HJs with the literature.

Comparison of dimensionless free surface profiles of HJs with the literature.

To further assess the performance and gain deeper insight into the models’ efficiency, residual plots are drawn for the investigated hydraulic parameters. These errors referred to the difference between the observed (literature) and predicted data, which monitored the regression quality (Hassanpour et al. 2021). At a 5% level of significance, a homo-scedasticity analysis measured the residual errors, and the results of predicted residual errors were compared with the previous study.

Figure 10 compares the residual errors of free surface profiles of present models with Wang & Chanson (2015) and Bayon-Barrachina & Lopez-Jimenez (2015). Notably, the solid horizontal line in Figure 10 is the agreement line. From Figure 8(b), the maximum residual errors of free surface profiles in the experimental study of Wang and Chanson ranged between −0.2 and 0.13, while from the agreement line, the maximum negative and positive residual errors in the numerical study of Bayon-Barrachina & Lopez-Jimenez (2015) reached −0.12 to 0.20. In comparison to the previous studies, at the start of the regression line, the residual errors in the present models indicated a random scattered pattern below the agreement line, which further showed that the residual errors in the present and compared models were not normally distributed. After X = 0.3, above the agreement line, the distribution pattern of residual errors was also not normal. The stilling basin with USBR baffle blocks indicated the maximum negative and positive residual values of −0.160 to 0.10, respectively, while −0.184 to 0.124 values of residuals were noticed in the WSBB basin. Furthermore, from Figure 10, it is evident from residual analysis that the free profiles of HJs within modified USBR and WSBB basins have followed the trend of previous studies and the residuals of the present model are found less, which indicates reasonable accuracy of the models. Overall, the regression analysis of free surface profiles both for the present and compared studies revealed a curvilinear pattern that showed a heteroscedasticity residual.

Figure 10

Residual error diagram of free surface profiles of HJs with the literature.

Residual error diagram of free surface profiles of HJs with the literature.

Sequent depth ratio

In 1840, Belanger developed a famous equation for the sequent depth of HJs in smooth rectangular channels, which is widely used by numerous researchers to validate the results. Similarly, in the laboratory experimentation for different upstream and downstream tailwater water levels, Hager & Bremen (1989) developed a relationship of sequent depth (y2/y1) against a wide range of initial Froude numbers (Fr1). For the present models, 6.5 and 6.64 values of Fr1 are obtained in WSBB and USBR basins, respectively, and their relationship with sequent depths is developed as shown in Figure 11(a). The results of y2/y1 against Fr1 are compared with the experiments of other authors (Belanger 1841Hager & Bremen 1989Kucukali & Chanson 2008) and with the numerical study of Bayon-Barrachina & Lopez-Jimenez (2015).

Figure 11

(a) Comparison of sequent depth ratio with previous studies and (b) comparison of residual errors of sequent depths with the literature.

(a) Comparison of sequent depth ratio with previous studies and (b) comparison of residual errors of sequent depths with the literature.

The sequent depths obtained from WSBB and modified USBR basins were 8.96 and 8.68, respectively, which were found to agree with the experimental results of other studies (Hager & Bremen 1989 and Belanger 1841), as shown in Figure 11(a). The results were also compared with the experiments of Kucukali & Chanson (2008), in which the value of Fr1 was 6.9. However, the Fr1 values obtained from present numerical models were 6.5 and 6.64 within WSBB and USBR basins, respectively. The comparison indicated that the present models overestimated the sequent depths, for which the errors reached 8.6 and 5.7% in WSBB and modified USBR basins, respectively. Furthermore, upon comparison with Bayon-Barrachina & Lopez-Jimenez (2015), results showed that present models underestimated the sequent depths, for which the maximum errors reached −13.2 and −9.8% errors in WSBB and USBR basins, respectively.

Figure 11(b) shows the comparison of residual errors of sequent depths with the previous studies. The maximum positive and negative residual values of 0.250 and −0.222 were found in WSBB and USBR baffle block stilling basins, respectively. The pattern of residual errors indicated an equal variance along the agreement line, which showed normal destitution of residual errors, thereby a homoscedastic pattern was noticed. The residual errors of sequent depths in both the tested basins were found within the ranges of Bayon-Barrachina & Lopez-Jimenez (2015) and Kucukali & Chanson (2008).

Roller length

Figure 12 compares the roller length (Lr/d1) of two different stilling basins with the previous studies, where Lr is the roller length of HJs and d1 is the initial flow depth before the HJ. Following Figure 10, the results showed that both the stilling basins produced almost similar roller lengths. Furthermore, in comparison to the previous studies, the relationship between roller lengths (Lr/d1) and Fr1 was found close to Kucukali and Chanson’s experiments (2008). However, the comparison with other studies indicated that the present models underestimated the roller lengths. The reason for reduced roller lengths was the effects of the basin’s appurtenance, which controlled the HJ lengths, as shown in Figures 13(a) and 13(b) (encircled regions). However, as compared to the modified USBR basin, the roller length in the WSBB basin was found to be less.

Figure 12

Comparison of roller lengths of HJ and initial Froude number with previous studies.

Comparison of roller lengths of HJ and initial Froude number with previous studies.

Figure 13

Roller lengths and energy dissipators: (a) WSBB basin and (b) modified USBR basin.

Roller lengths and energy dissipators: (a) WSBB basin and (b) modified USBR basin.

Figure 14 compares the residual errors for the roller lengths of present basins with the previous studies. The analysis showed a random distribution of residual errors and indicated homo-scedasticity of residuals. The results of residual errors for both the tested basins showed a good agreement with the compared studies and remained within the range of their residual errors. However, as compared to the USBR basin, the residual errors in the WSBB basin were found less, which reached −1.38.

Figure 14

Comparison of residual errors for the roller lengths with the previous studies.

Comparison of residual errors for the roller lengths with the previous studies.

HJ efficiency

The efficiency of the HJ is the ratio of energy loss to the upstream hydraulic head. Flow depth (hi), velocity (vi), and acceleration due to gravity (g) are the variables of HJ efficiency. The following equation was used to measure the efficiency  of the HJ (Bayon-Barrachina & Lopez-Jimenez 2015).

formula

(13)

where H1 and H2 are the specific energy heads upstream and downstream of HJs, respectively.

The results of numerical models showed 57.9 and 58.6% efficiencies in WSBB and modified USBR basins, respectively. The efficiencies for both the basins were also computed by Equation (2) and the results indicated 61.2 and 61.9% efficiencies for WSBB and modified USBR basins, respectively. The comparison further revealed that the present model underestimated the efficiencies, which reached the maximum errors of 5.41 and 5.45% in WSBB and modified USBR basins, respectively.

Figure 15(a) compares the efficiencies of present models with the previous studies. Upon comparing with Wu & Rajaratnam (1996), the results showed that the present model underestimated efficiencies for which the errors reached 6.6 and 5.54% in WSBB and modified USBR basins, respectively. Similarly, after comparing with Kucukali & Chanson (2008), the present model also showed a reduction in the HJ efficiencies for which the maximum errors reached 5.07 and 3.99% in WSBB and modified USBR basins, respectively. However, after comparing with Bayon-Barrachina & Lopez-Jimenez (2015), the results showed good agreement and indicated only 0.34 and 1.37% errors in WSBB and modified USBR basins, respectively. Overall, based on the bibliographic comparison, the overall accuracy of the present models for energy dissipation reached 93%.

Figure 15

(a) Comparison of HJ efficiency and (b) comparison of residual errors for the hydraulic jump efficiency.

(a) Comparison of HJ efficiency and (b) comparison of residual errors for the hydraulic jump efficiency.

Figure 15(b) indicates the residual errors of  for modified USBR and WSBB basins and compares the errors with the previous experimental and numerical studies. Upon comparison with the modified USBR basin and with the literature, the HJ efficiency in the WSBB basin showed a close agreement with the zero residual line, for which the maximum error reached 0.001. On the other hand, the residual error in the modified USBR basin reached 0.003. Figure 14 also showed that the maximum residual error in the HJ efficiencies was found to be less than that was observed in previous studies, which remained within the limits of the compared studies (Wu & Rajaratnam 1996Kucukali & Chanson 2008Bayon-Barrachina & Lopez-Jimenez 2015).

Velocity distribution

Velocity distribution was measured at different flow depths to obtain vertical velocity profiles in two different stilling basins. Figure 16 shows the typical profiles in HJs, where (δ) is the y value at which the maximum velocity (Umax) occurs, while (b) is the length scale where u = 0.5Umax and ∂u/∂y < 0 (Ead & Rajaratnam 2002Nasrabadi et al. 2012). The results indicated that in both basins, the velocity profiles showed a wall jet-like structure (Ead & Rajaratnam 2002). The results further showed that as the distance from the HJ-initiating locations was increased the maximum velocity decreased, thereby boundary growth layers were also decreased.

Figure 16

Typical velocity profile in HJs (Ead & Rajaratnam 2002).

Typical velocity profile in HJs (Ead & Rajaratnam 2002).

Figures 17 and 18 show that due to the supercritical velocity, a contracted jet was impinging near the beds of basins, and velocity decreased in upper fluid regions. The sections A-A and B-B in the basins indicated reverse flow and eddies in the HJs. The results of the upper fluid region of the HJ indicated typical backward velocity profiles as described by other authors (Ead & Rajaratnam 2002Nasrabadi et al. 2012). Over time, these reverse fluid circulations were found to be stabilized and showed stagnation zones (Yamini et al. 2022). The analysis further showed a recirculation region within the HJ, and the maximum backward velocity profiles were found in the developed regions. The results also showed that after the jump termination, the negative velocity profiles converted into forward velocity profiles, as can be seen in sections C-C of Figures 17 and 18. Additionally, the results showed that after the WSBB and USBR baffle blocks, the velocity near the bed decreased and became positive at the free surface.

Figure 17

2D illustration of vertical velocity profiles in the USBR basin.

2D illustration of vertical velocity profiles in the USBR basin.

Figure 18

2D illustration of vertical velocity profiles in the WSBB basin.

2D illustration of vertical velocity profiles in the WSBB basin.

Figure 19 shows the vertical velocity profile in the HJs at five different horizontal sections. The dimensionless plots between (y/b) and (U/Umax) illustrated that the velocity profiles followed the wall jet-like structure and were found to be agreed with Ead & Rajaratnam (2002), where y was the flow depth, b was the length scale, and Umax was the maximum velocity in the vertical section. The results also showed that in the HJ regions, both stilling basins produced identical structures of forward velocity profiles as can be seen in Figure 19(a) and 19(b).

Figure 19

Dimensionless velocity profiles: (a) WSBB basin and (b) modified USBR basin.

Dimensionless velocity profiles: (a) WSBB basin and (b) modified USBR basin.

From Figure 19, results showed that as the distance from the HJ toe increased, the vertical distance of Umax and inner layer thickness also increased. The analysis further indicated that as the distance from the initial location of HJs increased, the position of Umax was increased, which leveled off after the HJ, as can be seen in sections (C-C) of Figures 17 and 18. In both stilling basins, at X = 2 m, from the HJ initial location, the forward velocity profiles were found well agreed with the profile of Ead & Rajaratnam (2002) and the values of R2 reached 0.937 and 0.887 for WSBB and modified USBR basins, respectively, as shown in Figures 18(a) and 18(b), respectively. However, at X = 5.4 m, as compared to velocity (U/Umax = 0.36) in the modified USBR basin, the results showed less forward velocity (U/Umax = 0.21) in the WSBB basin at the upper fluid region.

Figure 20(a) shows the residual errors of velocity profiles in the WSBB basin. At x = 2 m, x = 3.2 m, and x = 4.3 m, the residual errors were found close to the agreement line. At the above-mentioned locations in the WSBB basin, the residual errors were also found less than Ead & Rajaratnam (2002). At x = 5.4 m in the WSBB basin, the maximum positive and negative residual errors of velocity profiles were 0.179 and −0.371, respectively, which were less than those that were found in the modified USBR basin. Figure 20(b) compares residual errors of velocity profiles in the modified USBR basin with the literature. It was evident from the residual diagrams that as the stream-wise distance from the jump-initiating location was increased, the maximum positive and negative errors also increased. The maximum positive and negative residual errors in the USBR basin were found at x = 5.4 m, which reached 1.139 and −1.352, respectively, and showed deviation from Ead & Rajaratnam (2002).

Figure 20

Comparison of residual errors with previous studies: (a) WSBB and (b) modified USBR basins.

Comparison of residual errors with previous studies: (a) WSBB and (b) modified USBR basins.

Turbulent kinetic energy

TKE is the averaged velocity value in xy, and z directions and describes energy dissipation at two different flow sections. The root mean square values of the velocity fluctuations are used to compute TKE. By considering the successive velocity values, the root mean square velocity (Urms) can be computed by the following equation (Gray et al. 2005).

formula

(14)

where u1u2, and u3 are successive velocities in the flow direction. Now, TKE can be calculated by the following equation.

formula

(15)

where urmsvrms, and wrms are the root mean square velocities in xy and z directions, respectively. Figure 21 shows the depth-wise (X–Y) TKE in a modified USBR basin. The results showed that the maximum TKE was found within and foreside of HJs while after the HJ, TKE continued to decline up to the end of the basin. Near the foreside of basins, flows were found to be strongly turbulent, dissipating most of the TKEs. Figure 19 shows the distribution of TKEs at seven vertical sections (X–Y), i.e., at Z = 0 m, 0.47 m, 0.93 m, 1.39 m, 1.85 m, 2.51 m, and free surface. At Z = 0 m, the maximum TKE in the USBR basin was found in the HJ region, which reached 0.30 J/kg, as shown in Figure 21(a). It is observed that behind the baffle blocks, TKEs were reduced due to eddies and fluid circulations, which dissipated the TKEs. Due to the impact of supercritical flows, a small number of eddies and fluid circulations were also noticed in front of the baffle blocks. The results showed that at the basin’s floor, TKEs traveled up to X = 21 m from the HJ-initiating location. Figures 21(b)–21(d) show that as the vertical distance from the basin’s floor was increased, the TKEs also increased, while their magnitude in the longitudinal direction was found to be reduced. The maximum TKEs at Z = 0.93 m, 1.39 m, and 1.85 m were 4.2, 4.5, and 3.6 J/kg, respectively. The results further indicated that as compared to the floor level, the TKEs from the central fluid depth to the free surface were found to be increased and their distribution in horizontal and lateral directions also increased. In the modified USBR basin, the maximum TKEs were noted at the toe of the HJ, which gradually reduced as the flow moved downstream, reaching 0.1 J/kg at the basin end, as shown in Figure 21(g).

Figure 21

Depth-wise distribution of TKEs in the USBR stilling basin at (a) Z = 0 m (floor level), (b) Z = 0.47 m, (c) Z = 0.93 m, (d) Z= 1.39 m, (e) 1.85 m, (f) Z= 2.51 m, and (g) free surface.

Depth-wise distribution of TKEs in the USBR stilling basin at (a) Z = 0 m (floor level), (b) Z = 0.47 m, (c) Z = 0.93 m, (d) Z= 1.39 m, (e) 1.85 m, (f) Z= 2.51 m, and (g) free surface.

In the WSBB basin, at Z = 0 m (floor level), maximum TKEs reached 0.20 J/kg as shown in Figure 22(a). The results showed that as compared to USBR baffle blocks, the WSBBs were spreading the flow more efficiently in the lateral direction. Due to the spreading of fluid in the lateral direction, the results indicated that in the WSBB basin, the TKEs declined earlier in the basin and less energy was reached at the basin’s end. In the WSBB basin, only the TKEs in central fluid depths traveled downstream, which ended at X = 13 m from the toe of HJs. It is worth mentioning here that as compared to the modified USBR basin, the TKEs in the WSBB basin declined earlier, which indicated 8 m less distance than the USBR basin.

Figure 22

Depth-wise distribution of TKEs in the WSBB stilling basin at (a) Z= 0 m (floor level), (b) Z= 0.47 m, (c) Z= 0.93 m, (d) Z= 1.39 m, (e) 1.85 m, (f) Z= 2.51 m, and (g) free surface.

Depth-wise distribution of TKEs in the WSBB stilling basin at (a) Z= 0 m (floor level), (b) Z= 0.47 m, (c) Z= 0.93 m, (d) Z= 1.39 m, (e) 1.85 m, (f) Z= 2.51 m, and (g) free surface.

The results further showed that upon the use of WSBBs, no flow reattachment was witnessed on either side of the baffle blocks. Due to reduced reattachment, more wake areas were generated on the side of the WSBB basin, and the results showed agreement with the statement of other authors (Verma & Goel 2003Verma et al. 2004Goel & Verma 2006). At Z = 0.47 m, 0.93 m, and 1.39 m, the maximum TKEs were noticed in the HJ region, which reached 4.3, 4.6, and 3.5 J/kg, respectively, as shown in Figure 22(b)–22(d), respectively. In the WSBB basin, after the HJ, the baffle blocks declined the TKEs due to the development of sharp discontinuities in the flow. After Z = 1.39 m, the value of TKEs up to the free surface gradually reduced, as shown in Figure 22(e) and 22(f). Figure 22(g) shows 2D illustrations of TKEs on the free surface, and the results indicate that as compared to the modified USBR basin, the magnitude of TKEs was lower and traveled less distance in the WSBB basin.

CONCLUSIONS

This study developed numerical models on the rigid bed to investigate the effects of USBR and WSBB baffle blocks on the HJ downstream of the river diversion barrage using FLOW-3D. VOF and RNG K–ɛ models were employed to track the free surface and turbulence, respectively. For the proposed new basin (WSBB basin), WSBB with a vertex angle of 150° and cutback of 90° is employed in the baffle block region, while the friction block region remained unchanged. The performance of the two different basins is assessed by HJs and other hydraulic parameters such as free surface profile, sequent depths, roller lengths, HJ efficiency, velocity profile, and TKE. Furthermore, the results of the present modified USBR Type-III and WSBB basins are compared with the relevant literature, for which regression analysis is performed and residual error diagrams are plotted. However, the present models are limited to the single discharge of 44 m3/s and employ only one turbulence model, i.e., RNG K–ɛ. Additionally, the present models were designed for a single bay of the barrage.

  • Upon use of fine meshing, in comparison to the designed discharge, the present models showed 0.80 and 0.90% of errors in modified USBR Type-III and WSBB basins, respectively. Similarly, for the gated flow, the results indicated 0.32 and 1.14% errors in the modified USBR Type-III and WSBB basins, respectively.
  • After employing regression analysis, the results of free surface profiles showed agreement with the previous studies for which R2 reached 0.980 and 0.970 in WSBB and modified USBR basins, respectively. From the results, it can be believed that as compared to the modified USBR Type-III, the newly proposed WSBB basin produced a better free surface profile of HJs.
  • Due to the inclusion of the baffle blocks in the studied basins, the roller lengths of HJs were contained efficiently, and thereby, as compared to the literature, lesser roller lengths were observed in the modified USBR Type-III and WSBB basins.
  • The overall efficiency of HJs in modified USBR and WSBB basins reached 58.60 and 57.90%, respectively, which showed good agreement with the literature. Based on the results of the efficiency of HJs, the accuracy of the present models reached 93%.
  • In the hydraulic regions, the results of dimensionless velocity profiles indicated a wall jet-like structure, which agreed well with the literature. In addition, as compared to the modified USBR Type-III basin, the velocity profiles in the WSBB basin were found to be more promising, for which R2 reached 0.937. Additionally, after the HJ, as compared to the USBR Type-III basin, the forward velocity (U/Umax) in the WSBB basin was found to be less. Conclusively, it can be said that in comparison to the modified USBR Type-III basin, at the lower discharges, the WSBB basin decays the velocities more efficiently.
  • The results of TKEs indicated that the flow was strongly turbulent near the foreside of the HJs, and the maximum TKEs were noted in the central fluid depths. In the WSBB basin, no fluid reattachment was observed on either side of the baffle blocks, and the results further indicated that as compared to the modified USBR Type-III basin, fewer TKEs were found at the end of the WSBB basin.

Based on the models’ results, the study confirms the suitability of WSBB downstream of the barrage for lower tailwater conditions. From the results, it is believed that FLOW-3D is a very effective and efficient tool for the hydraulic investigation of flow behavior downstream of the barrage. However, in Pakistan, the use of such modeling tools is found very limited, therefore, the study results will help hydraulic and civil engineers to assess different energy dissipation arrangements within the stilling basins and will provide suitable alternative solutions. The present study was limited to the fixed geometry of the WSBB, therefore, it is suggested to investigate HJ and flow characteristics with other vertex and cutback angles. In addition, it is also recommended to study the hydraulics of WSBB downstream of barrages by employing multiple bays of barrage and other turbulence models.

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Omega-Liutex Method

Prediction of the Vortex Evolution and Influence Analysis of Rough Bed in a Hydraulic Jump with the Omega-Liutex Method

Omega-Luitex법을 이용한 수력점프 발생시 러프 베드의 와류 진화 예측 및 영향 분석

Cong Trieu Tran, Cong Ty Trinh

Abstract

The dissipation of energy downstream of hydropower projects is a significant issue. The hydraulic jump is exciting and widely applied in practice to dissipate energy. Many hydraulic jump characteristics have been studied, such as length of jump Lj and sequent flow depth y2. However, understanding the evolution of the vortex structure in the hydraulic jump shows a significant challenge. This study uses the RNG k-e turbulence model to simulate hydraulic jumps on the rough bed. The Omega-Liutex method is compared with Q-criterion for capturing vortex structure in the hydraulic jump. The formation, development, and shedding of the vortex structure at the rough bed in the hydraulic jumper are analyzed. The vortex forms and rapidly reduces strength on the rough bed, resulting in fast dissipation of energy. At the rough block rows 2nd and 3rd, the vortex forms a vortex rope that moves downstream and then breaks. The vortex-shedding region represents a significant energy attenuation of the flow. Therefore, the rough bed dissipates kinetic energy well. Adding reliability to the vortex determined by the Liutex method, the vorticity transport equation is used to compare the vorticity distribution with the Liutex distribution. The results show a further comprehension of the hydraulic jump phenomenon and its energy dissipation.

Keywords

flow-3D; hydraulic Jump; omega-liutex method; vortex breakdown

References

[1] Viti, N., Valero, D., & Gualtieri, C. (2019). Numerical Simulation of Hydraulic Jumps. Part 2: Recent Results and Future Outlook. Water, 11(1), 28. https://doi.org/10.3390/w11010028
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[5] Nikmehr, S. & Aminpour, Y. (2020). Numerical Simulation of Hydraulic Jump over Rough Beds. Periodica Polytechnica Civil Engineering, 64(2), 396-407. https://doi.org/10.3311/PPci.15292
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[10] Liu, C., Wang, Y., Yang, Y. et al (2016). New omega vortex identification method. Science China Physics, Mechanics & Astronomy, (8), 56-64. https://doi.org/10.1007/s11433-016-0022-6
[11] Tran, C. T. & Pham, D. C. (2022). Application of Liutex and Entropy Production to Analyze the Influence of Vortex Rope in the Francis-99 Turbine Draft Tube. Tehnički vjesnik, 29(4), 1177-1183. https://doi.org/10.17559/TV-20210821070801
[12] Dong, X., Gao, Y., & Liu, C. (2019). New normalized Rortex/vortex identification method. Physics of Fluids, 31(1), 011701. https://doi.org/10.1063/1.5066016
[13] Wang, L., Zheng, Z., Cai, W. et al. (2019). Extension Omega and Omega-Liutex methods applied to identify vortex structures in viscoelastic turbulent flow. Journal of Hydrodynamics, 31(5), 911-921. https://doi.org/10.1007/s42241-019-0045-x
[14] Xu, H., Cai, X., & Liu, C. (2019). Liutex (vortex) core definition and automatic identification for turbulence vortex structures. Journal of Hydrodynamics, 31(5), 857-863. https://doi.org/10.1007/s42241-019-0066-5
[15] Tran, C. T. et al. (2020). Prediction of the precessing vortex core in the Francis-99 draft tube under off-design conditions by using Liutex/Rortex method. Journal of Hydrodynamics, 32, 623-628. https://doi.org/10.1007/s42241-020-0031-3
[16] Liu, C. et al. (2019). A Liutex based definition of vortex axis line. arXiv preprint arXiv:1904.10094. https://doi.org/10.48550/arXiv.1904.10094
[17] Samadi-Boroujeni, H. et al. (2013). Effect of triangular corrugated beds on the hydraulic jump characteristics. Canadian Journal of Civil Engineering, 40(9), 841-847. https://doi.org/10.1139/cjce-2012-0019
[18] Ghaderi, A. et al. (2020). Characteristics of free and submerged hydraulic jumps over different macroroughnesses. Journal of Hydroinformatics, 22(6), 1554-1572. https://doi.org/10.2166/hydro.2020.298
[19] Wu, Z. et al. (2021). Analysis of the influence of transverse groove structure on the flow of a flat-plate surface based on Liutex parameters. Engineering Applications of Computational Fluid Mechanics, 15(1), 1282-1297. https://doi.org/10.1080/19942060.2021.1968955
[20] Ji, B., et al. (2014). Numerical simulation of threedimensional cavitation shedding dynamics with special emphasis on cavitation – vortex interaction. Ocean Engineering, 87, 64-77. https://doi.org/10.1016/j.oceaneng.2014.05.005
[21] Tran, C., Bin, J., & Long, X. (2019). Simulation and Analysis of Cavitating Flow in the Draft Tube of the Francis Turbine with Splitter Blades at Off-Design Condition. Tehnicki vjesnik – Technical Gazette, 26(6). https://doi.org/10.17559/TV-20190316042929
Image_Sacrificial_Pier

Sacrificial Piles as Scour Countermeasures in River Bridges A Numerical Study using FLOW-3D

하천 교량의 파괴 대책으로서 희생파일에 대한 FLOW-3D를 이용한 수치 연구

Mohammad Nazari-Sharabian, Aliasghar Nazari-Sharabian, Moses Karakouzian, Mehrdad Karami

Abstract

Scour is defined as the erosive action of flowing water, as well as the excavating and carrying away materials from beds and banks of streams, and from the vicinity of bridge foundations, which is one of the main causes of river bridge failures. In the present study, implementing a numerical approach, and using the FLOW-3D model that works based on the finite volume method (FVM), the applicability of using sacrificial piles in different configurations in front of a bridge pier as countermeasures against scouring is investigated. In this regard, the numerical model was calibrated based on an experimental study on scouring around an unprotected circular river bridge pier. In simulations, the bridge pier and sacrificial piles were circular, and the riverbed was sandy. In all scenarios, the flow rate was constant and equal to 45 L/s. Furthermore, one to five sacrificial piles were placed in front of the pier in different locations for each scenario. Implementation of the sacrificial piles proved to be effective in substantially reducing the scour depths. The results showed that although scouring occurred in the entire area around the pier, the maximum and minimum scour depths were observed on the sides (using three sacrificial piles located upstream, at three and five times the pier diameter) and in the back (using five sacrificial piles located upstream, at four, six, and eight times the pier diameter) of the pier. Moreover, among scenarios where single piles were installed in front of the pier, installing them at a distance of five times the pier diameter was more effective in reducing scour depths. For other scenarios, in which three piles and five piles were installed, distances of six and four times the pier diameter for the three piles scenario, and four, six, and eight times the pier diameter for the five piles scenario were most effective.

 

Keywords

Scouring; River Bridges; Sacrificial Piles; Finite Volume Method (FVM); FLOW-3D.

 

References


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Karakouzian, Moses, Mehrdad Karami, Mohammad Nazari-Sharabian, and Sajjad Ahmad. “Flow-Induced Stresses and Displacements in Jointed Concrete Pipes Installed by Pipe Jacking Method.” Fluids 4, no. 1 (February 21, 2019): 34. doi:10.3390/fluids4010034.

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DOI: 10.28991/cej-2020-03091531

Embankment Dams Overtopping Breach: A Numerical Investigation of Hydraulic Results

Embankment Dams Overtopping Breach: A Numerical Investigation of Hydraulic Results

Mahdi EbrahimiMirali MohammadiSayed Mohammad Hadi Meshkati & Farhad Imanshoar

Abstract

The overtopping breach is the most probable reason of embankment dam failures. Hence, the investigation of the mentioned phenomenon is one of the vital hydraulic issues. This research paper tries to utilize three numerical models, i.e., BREACH, HEC-RAS, and FLOW-3D for modeling the hydraulic outcomes of overtopping breach phenomenon. Furthermore, the outputs have been compared with experimental model results given by authors. The BREACH model presents a desired prediction for the peak flow. The HEC-RAS model has a more realistic performance in terms of the peak flow prediction, its occurrence time (5-s difference with observed status), and maximum flow depth. The variations diagram in the reservoir water level during the breach process has a descending trend. Whereas it initially ascended; and then, it experienced a descending trend in the observed status. The FLOW-3D model computes the flow depth, flow velocity, and Froude number due to the physical model breach. Moreover, it revealed a peak flow damping equals to 5% and 5-s difference in the peak flow occurrence time at 4-m distance from the physical model downstream. In addition, the current research work demonstrates the mentioned numerical models and provides a possible comprehensive perspective for a dam breach scope. They also help to achieve the various hydraulic parameters computations. Besides, they may calculate unmeasured parameters using the experimental data.

월류 현상은 제방 댐 실패의 가장 유력한 원인입니다. 따라서 언급된 현상에 대한 조사는 중요한 수리학적 문제 중 하나입니다.

본 연구 논문에서는 월류 침해 현상의 수리적 결과를 모델링하기 위해 BREACH, HEC-RAS 및 FLOW-3D의 세 가지 수치 모델을 활용하려고 합니다. 또한 출력은 저자가 제공한 실험 모델 결과와 비교되었습니다. BREACH 모델은 최대 유량에 대해 원하는 예측을 제시합니다.

HEC-RAS 모델은 최고유량 예측, 발생시간(관찰상태와 5초 차이), 최대유량수심 측면에서 보다 현실적인 성능을 가지고 있습니다. 위반 과정 중 저수지 수위의 변동 다이어그램은 감소하는 추세를 보입니다. 처음에는 상승했지만 그런 다음 관찰된 상태가 감소하는 추세를 경험했습니다.

FLOW-3D 모델은 물리적 모델 위반으로 인한 흐름 깊이, 흐름 속도 및 Froude 수를 계산합니다. 또한, 실제 모델 하류로부터 4m 거리에서 최대유량 발생시간이 5%, 5초 차이에 해당하는 최대유량 감쇠를 나타냈습니다.

또한, 현재 연구 작업은 언급된 수치 모델을 보여주고 댐 침해 범위에 대한 가능한 포괄적인 관점을 제공합니다. 또한 다양한 유압 매개변수 계산을 수행하는 데 도움이 됩니다. 게다가 실험 데이터를 사용하여 측정되지 않은 매개변수를 계산할 수도 있습니다.

Keywords

DOI

  • https://doi.org/10.1007/s40996-024-01387-9

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The impacts of profile concavity on turbidite deposits: Insights from the submarine canyons on global continental margins

The impacts of profile concavity on turbidite deposits: Insights from the submarine canyons on global continental margins

프로필 오목부가 탁도 퇴적물에 미치는 영향: 전 세계 대륙 경계에 대한 해저 협곡의 통찰력

Kaiqi Yu a, Elda Miramontes bc, Matthieu J.B. Cartigny d, Yuping Yang a, Jingping Xu a
aDepartment of Ocean Science and Engineering, Southern University of Science and Technology, 1088 Xueyuan Rd., Shenzhen 518055, Guangdong, China
bMARUM-Center for Marine Environmental Sciences, University of Bremen, Bremen, Germanyc
Faculty of Geosciences, University of Bremen, Bremen, Germany
dDepartment of Geography, Durham University, South Road, Durham DH1 3LE, UK

Received 10 August 2023, Revised 13 March 2024, Accepted 13 March 2024, Available online 17 March 2024, Version of Record 20 March 2024.

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Highlights

  • •The impact of submarine canyon concavity on turbidite deposition was assessed.
  • •Distribution of turbidite deposits varies with changes in canyon concavity.
  • •Three distinct deposition patterns were identified.
  • •The recognized deposition patterns align well with the observed turbidite deposits.

Abstract

Submarine canyons are primary conduits for turbidity currents transporting terrestrial sediments, nutrients, pollutants and organic carbon to the deep sea. The concavity in the longitudinal profile of these canyons (i.e. the downstream flattening rate along the profiles) influences the transport processes and results in variations in turbidite thickness, impacting the transfer and burial of particles. To better understand the controlling mechanisms of canyon concavity on the distribution of turbidite deposits, here we investigate the variation in sediment accumulation as a function of canyon concavity of 20 different modern submarine canyons, distributed on global continental margins. In order to effectively assess the isolated impact of the concavity of 20 different canyons, a series of two-dimensional, depth-resolved numerical simulations are conducted. Simulation results show that the highly concave profile (e.g. Surveyor and Horizon) tends to concentrate the turbidite deposits mainly at the slope break, while nearly straight profiles (e.g. Amazon and Congo) result in deposition focused at the canyon head. Moderately concave profiles with a smoother canyon floor (e.g. Norfolk-Washington and Mukluk) effectively facilitate the downstream transport of suspended sediments in turbidity currents. Furthermore, smooth and steep upper reaches of canyons commonly contribute to sediment bypass (i.e. Mukluk and Chirikof), while low slope angles lead to deposition at upper reaches (i.e. Bounty and Valencia). At lower reaches, the distribution of turbidite deposits is consistent with the occurrence of hydraulic jumps. Under the influence of different canyon concavities, three types of deposition patterns are inferred in this study, and verified by comparison with observed turbidite deposits on the modern or paleo-canyon floor. This study demonstrates a potential difference in sediment transport efficiency of submarine canyons with different concavities, which has potential consequences for sediment and organic carbon transport through submarine canyons.

Introduction

Submarine canyons are pivotal links in source-to-sink systems on continental margins (Sømme et al., 2009; Nyberg et al., 2018; Pope et al., 2022a, Pope et al., 2022b) that provide efficient pathways for moving prodigious volumes of terrestrial materials to the abyssal basin (Spychala et al., 2020; Heijnen et al., 2022). When turbidity currents, the main force that transports the above mentioned sediments (Xu et al., 2004; Xu, 2010; Talling et al., 2013; Stevenson et al., 2015), slow down after entering a flatter and/or wider stretch of the canyon downstream, the laden sediments settle, often rapidly, to form a deposit called turbidite that is known for organic carbon burial, hydrocarbon reserves and the accumulation of microplastics (Galy et al., 2007; Pohl et al., 2020a; Pope et al., 2022b; Pierdomenico et al., 2023). A set of flume experiments by Pohl et al. (2020b) revealed that the variation of bed slope plays a dominant role in controlling the sizes and locations of the deposit: a) a more gently dipping upper slope leads to upstream migration of upslope pinch-out; b) the increase of lower slope results in a decrease of the deposit thickness (Fig. 1a).

From upper continental slopes to deepwater basins, turbidity currents are commonly confined by submarine canyons that facilitate the longer distance transport of sediments (Eggenhuisen et al., 2022; Pope et al., 2022a; Wahab et al., 2022, Li et al., 2023a). The concavity, defined here as the downstream flattening rate of profiles (Covault et al., 2011; Chen et al., 2019; Seybold et al., 2021; Soutter et al., 2021a), of the longitudinal bed profile of the submarine canyons is therefore a key factor that determines hydrodynamic processes of turbidity currents, including the accumulation of sediments along the canyon thalweg (Covault et al., 2014; de Leeuw et al., 2016; Heerema et al., 2022; Heijnen et al., 2022). Due to the comprehensive impacts of sediment supply, grain size, climate change, regional tectonics, associated river and self-incision, the concavity of submarine canyons on global continental margins varies greatly (Parker et al., 1986; Harris and Whiteway, 2011; Casalbore et al., 2018; Nyberg et al., 2018; Soutter et al., 2021a, Li et al., 2023b), which is much more complex than the two constant slope setup of Pohl et al. (2020b)’s flume experiment (Fig. 1a). This raises the question of how the more complex concavity influences the dynamics of turbidity currents and the resultant distribution of turbidite deposits. For instance, the longitudinal profile concavity can also be increased by steepening the upper slope and/or gentling the lower slope of canyons (Fig. 1b). Parameters, known as significant factors influencing flow dynamics, include dip angle (Pohl et al., 2019), bed roughness (Baghalian and Ghodsian, 2020), obstacle presence (Howlett et al., 2019), and confinement conditions (Soutter et al., 2021b). However, the role of channel concavity in determining the downstream evolution of flow dynamics remains poorly understood (Covault et al., 2011; Georgiopoulou and Cartwright, 2013), and it is still unclear whether changes in concavity can result in different locations of pinch-out points and variations in turbidite deposit thicknesses (Pohl et al., 2020b).

In this study, we hypothesize that a more concave profile resulting from a steeper upper slope and a gentler lower slope may lead to a downstream migration of the upslope pinch-out and an increase of deposit thickness (Fig. 1b). This hypothesis is tested in 20 modern submarine canyons (shown in Fig. 2) whose longitudinal profiles are extracted from the GEBCO_2022 grid. Due to the lack of data describing the turbidite thickness trends in these canyons, we used a numerical model (FLOW-3D® software) to simulate the depositional process. The simulation results allow us to address at least two questions: (1) How does the concavity affect the distribution and thickness of turbidite deposits along the canyon thalwegs? (2) What is the impact of canyon concavity on the dynamics of the turbidity currents? Such answers on a global scale are undoubtedly helpful in understanding not only the sediment transport processes but also the efficient transfer and burial of organic carbon along global continental margins.

Section snippets

Submarine canyons used in this study

The longitudinal profiles of 20 modern submarine canyons are obtained using Global Mapper® from a public domain database GEBCO_2022 (doi:https://doi.org/10.5285/e0f0bb80-ab44-2739-e053-6c86abc0289c). The GEBCO_2022 grid provides elevation data, in meters, on a 15 arc-second interval grid. The 20 selected submarine canyons, which span the typical distance covered by turbidity currents, have been chosen from a diverse range of submarine canyon and channel systems that extend at least 250 km

Concavity of longitudinal canyon profiles

The NCI and α values of all 20 canyon profiles utilized in this study are plotted in Fig. 4, indicating the majority of these submarine canyons typically exhibit a concave profile, characterized by a negative NCI, except for the Amazon. In most of the profiles, the NCI is lower than −0.08, with the most concave point (indicated by the minimum ratio α) located closer to the canyon head than to the profile end, and their upper reaches are steeper than lower reaches, typically observed as the

Validation of the hypothesis

As previously mentioned in this paper, one of the primary objectives of this study is to evaluate the hypothesis inferred from the flume tank experiment of Pohl et al. (2020b): whether a more concave canyon profile can exert a comparable influence on turbidite deposits as the steepness of the lower and upper slopes in a slope-break system (Fig. 1). Shown as the modeling results, the deposition pattern of this study is more ‘irregular’ compared with the flume tank experiment (Pohl et al., 2020b

Conclusion

Based on global bathymetry, this study simulates the depositional behavior of turbidity currents flowing through the 20 different submarine canyons on the margins of open ocean and marginal sea. Influenced by the different concavities, the resulted deposition patterns are characterized by a variable distribution of turbidite deposits.

  • 1)The simulation results demonstrate that the accumulation of turbidite deposits is primarily observed in downstream regions near the slope break for highly concave

CRediT authorship contribution statement

Kaiqi Yu: Writing – review & editing, Writing – original draft, Validation, Software, Methodology, Investigation, Conceptualization. Elda Miramontes: Writing – review & editing, Supervision, Conceptualization. Matthieu J.B. Cartigny: Writing – review & editing, Supervision. Yuping Yang: Software, Methodology. Jingping Xu: Writing – review & editing, Supervision, Funding acquisition, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This study is supported by the Shenzhen Natural Science Foundation (JCYJ20210324105211031). Matthieu J. B. Cartigny was supported by Royal Society Research Fellowship (DHF/R1/180166). We thank the Chief Editor Zhongyuan Chen, the associate editor and two reviewers for their constructive comments that helped us improve our manuscript.

References (70)

There are more references available in the full text version of this article.

Figure 1 | Schematic of the present research model with dimensions and macro-roughnesses installed.

On the hydraulic performance of the inclined drops: the effect of downstreammacro-roughness elements

경사 낙하의 수력학적 성능: 하류 거시 거칠기 요소의 영향

Farhoud Kalateh a,*, Ehsan Aminvash a and Rasoul Daneshfaraz b
a Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
b Faculty of Engineering, University of Maragheh, Maragheh, Iran
*Corresponding author. E-mail: f.kalateh@gmail.com

ABSTRACT

The main goal of the present study is to investigate the effects of macro-roughnesses downstream of the inclined drop through numerical models. Due to the vital importance of geometrical properties of the macro-roughnesses in the hydraulic performance and efficient energy dissipation downstream of inclined drops, two different geometries of macro-roughnesses, i.e., semi-circular and triangular geometries, have been investigated using the Flow-3D model. Numerical simulation showed that with the flow rate increase and relative critical depth, the flow energy consumption has decreased. Also, relative energy dissipation increases with the increase in height and slope angle, so that this amount of increase in energy loss compared to the smooth bed in semi-circular and triangular elements is 86.39 and 76.80%, respectively, in the inclined drop with a height of 15 cm and 86.99 and 65.78% in the drop with a height of 20 cm. The Froude number downstream on the uneven bed has been dramatically reduced, so this amount of reduction has been approximately 47 and 54% compared to the control condition. The relative depth of the downstream has also increased due to the turbulence of the flow on the uneven bed with the increase in the flow rate.

본 연구의 주요 목표는 수치 모델을 통해 경사 낙하 하류의 거시 거칠기 효과를 조사하는 것입니다. 수력학적 성능과 경사 낙하 하류의 효율적인 에너지 소산에서 거시 거칠기의 기하학적 특성이 매우 중요하기 때문에 두 가지 서로 다른 거시 거칠기 형상, 즉 반원형 및 삼각형 형상이 Flow를 사용하여 조사되었습니다.

3D 모델 수치 시뮬레이션을 통해 유량이 증가하고 상대 임계 깊이가 증가함에 따라 유동 에너지 소비가 감소하는 것으로 나타났습니다. 또한, 높이와 경사각이 증가함에 따라 상대적인 에너지 소산도 증가하는데, 반원형 요소와 삼각형 요소에서 평활층에 비해 에너지 손실의 증가량은 경사낙하에서 각각 86.39%와 76.80%입니다.

높이 15cm, 높이 20cm의 드롭에서 86.99%, 65.78%입니다. 고르지 못한 베드 하류의 프루드 수가 극적으로 감소하여 이 감소량은 대조 조건에 비해 약 47%와 54%였습니다. 유속이 증가함에 따라 고르지 못한 층에서의 흐름의 난류로 인해 하류의 상대적 깊이도 증가했습니다.

Key words

flow energy dissipation, Froude number, inclined drop, numerical simulation

Figure 1 | Schematic of the present research model with dimensions and macro-roughnesses installed.
Figure 1 | Schematic of the present research model with dimensions and macro-roughnesses installed.
Figure 2 | Meshing, boundary condition, and solution field network
Figure 2 | Meshing, boundary condition, and solution field network

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Fig. 9 From: An Investigation on Hydraulic Aspects of Rectangular Labyrinth Pool and Weir Fishway Using FLOW-3D

An Investigation on Hydraulic Aspects of Rectangular Labyrinth Pool and Weir Fishway Using FLOW-3D

Abstract

웨어의 두 가지 서로 다른 배열(즉, 직선형 웨어와 직사각형 미로 웨어)을 사용하여 웨어 모양, 웨어 간격, 웨어의 오리피스 존재, 흐름 영역에 대한 바닥 경사와 같은 기하학적 매개변수의 영향을 평가했습니다.

유량과 수심의 관계, 수심 평균 속도의 변화와 분포, 난류 특성, 어도에서의 에너지 소산. 흐름 조건에 미치는 영향을 조사하기 위해 FLOW-3D® 소프트웨어를 사용하여 전산 유체 역학 시뮬레이션을 수행했습니다.

수치 모델은 계산된 표면 프로파일과 속도를 문헌의 실험적으로 측정된 값과 비교하여 검증되었습니다. 수치 모델과 실험 데이터의 결과, 급락유동의 표면 프로파일과 표준화된 속도 프로파일에 대한 평균 제곱근 오차와 평균 절대 백분율 오차가 각각 0.014m와 3.11%로 나타나 수치 모델의 능력을 확인했습니다.

수영장과 둑의 흐름 특성을 예측합니다. 각 모델에 대해 L/B = 1.83(L: 웨어 거리, B: 수로 폭) 값에서 급락 흐름이 발생할 수 있고 L/B = 0.61에서 스트리밍 흐름이 발생할 수 있습니다. 직사각형 미로보 모델은 기존 모델보다 무차원 방류량(Q+)이 더 큽니다.

수중 흐름의 기존 보와 직사각형 미로 보의 경우 Q는 각각 1.56과 1.47h에 비례합니다(h: 보 위 수심). 기존 웨어의 풀 내 평균 깊이 속도는 직사각형 미로 웨어의 평균 깊이 속도보다 높습니다.

그러나 주어진 방류량, 바닥 경사 및 웨어 간격에 대해 난류 운동 에너지(TKE) 및 난류 강도(TI) 값은 기존 웨어에 비해 직사각형 미로 웨어에서 더 높습니다. 기존의 웨어는 직사각형 미로 웨어보다 에너지 소산이 더 낮습니다.

더 낮은 TKE 및 TI 값은 미로 웨어 상단, 웨어 하류 벽 모서리, 웨어 측벽과 채널 벽 사이에서 관찰되었습니다. 보와 바닥 경사면 사이의 거리가 증가함에 따라 평균 깊이 속도, 난류 운동 에너지의 평균값 및 난류 강도가 증가하고 수영장의 체적 에너지 소산이 감소했습니다.

둑에 개구부가 있으면 평균 깊이 속도와 TI 값이 증가하고 풀 내에서 가장 높은 TKE 범위가 감소하여 두 모델 모두에서 물고기를 위한 휴식 공간이 더 넓어지고(TKE가 낮아짐) 에너지 소산율이 감소했습니다.

Two different arrangements of the weir (i.e., straight weir and rectangular labyrinth weir) were used to evaluate the effects of geometric parameters such as weir shape, weir spacing, presence of an orifice at the weir, and bed slope on the flow regime and the relationship between discharge and depth, variation and distribution of depth-averaged velocity, turbulence characteristics, and energy dissipation at the fishway. Computational fluid dynamics simulations were performed using FLOW-3D® software to examine the effects on flow conditions. The numerical model was validated by comparing the calculated surface profiles and velocities with experimentally measured values from the literature. The results of the numerical model and experimental data showed that the root-mean-square error and mean absolute percentage error for the surface profiles and normalized velocity profiles of plunging flows were 0.014 m and 3.11%, respectively, confirming the ability of the numerical model to predict the flow characteristics of the pool and weir. A plunging flow can occur at values of L/B = 1.83 (L: distance of the weir, B: width of the channel) and streaming flow at L/B = 0.61 for each model. The rectangular labyrinth weir model has larger dimensionless discharge values (Q+) than the conventional model. For the conventional weir and the rectangular labyrinth weir at submerged flow, Q is proportional to 1.56 and 1.47h, respectively (h: the water depth above the weir). The average depth velocity in the pool of a conventional weir is higher than that of a rectangular labyrinth weir. However, for a given discharge, bed slope, and weir spacing, the turbulent kinetic energy (TKE) and turbulence intensity (TI) values are higher for a rectangular labyrinth weir compared to conventional weir. The conventional weir has lower energy dissipation than the rectangular labyrinth weir. Lower TKE and TI values were observed at the top of the labyrinth weir, at the corner of the wall downstream of the weir, and between the side walls of the weir and the channel wall. As the distance between the weirs and the bottom slope increased, the average depth velocity, the average value of turbulent kinetic energy and the turbulence intensity increased, and the volumetric energy dissipation in the pool decreased. The presence of an opening in the weir increased the average depth velocity and TI values and decreased the range of highest TKE within the pool, resulted in larger resting areas for fish (lower TKE), and decreased the energy dissipation rates in both models.

1 Introduction

Artificial barriers such as detour dams, weirs, and culverts in lakes and rivers prevent fish from migrating and completing the upstream and downstream movement cycle. This chain is related to the life stage of the fish, its location, and the type of migration. Several riverine fish species instinctively migrate upstream for spawning and other needs. Conversely, downstream migration is a characteristic of early life stages [1]. A fish ladder is a waterway that allows one or more fish species to cross a specific obstacle. These structures are constructed near detour dams and other transverse structures that have prevented such migration by allowing fish to overcome obstacles [2]. The flow pattern in fish ladders influences safe and comfortable passage for ascending fish. The flow’s strong turbulence can reduce the fish’s speed, injure them, and delay or prevent them from exiting the fish ladder. In adult fish, spawning migrations are usually complex, and delays are critical to reproductive success [3].

Various fish ladders/fishways include vertical slots, denil, rock ramps, and pool weirs [1]. The choice of fish ladder usually depends on many factors, including water elevation, space available for construction, and fish species. Pool and weir structures are among the most important fish ladders that help fish overcome obstacles in streams or rivers and swim upstream [1]. Because they are easy to construct and maintain, this type of fish ladder has received considerable attention from researchers and practitioners. Such a fish ladder consists of a sloping-floor channel with series of pools directly separated by a series of weirs [4]. These fish ladders, with or without underwater openings, are generally well-suited for slopes of 10% or less [12]. Within these pools, flow velocities are low and provide resting areas for fish after they enter the fish ladder. After resting in the pools, fish overcome these weirs by blasting or jumping over them [2]. There may also be an opening in the flooded portion of the weir through which the fish can swim instead of jumping over the weir. Design parameters such as the length of the pool, the height of the weir, the slope of the bottom, and the water discharge are the most important factors in determining the hydraulic structure of this type of fish ladder [3]. The flow over the weir depends on the flow depth at a given slope S0 and the pool length, either “plunging” or “streaming.” In plunging flow, the water column h over each weir creates a water jet that releases energy through turbulent mixing and diffusion mechanisms [5]. The dimensionless discharges for plunging (Q+) and streaming (Q*) flows are shown in Fig. 1, where Q is the total discharge, B is the width of the channel, w is the weir height, S0 is the slope of the bottom, h is the water depth above the weir, d is the flow depth, and g is the acceleration due to gravity. The maximum velocity occurs near the top of the weir for plunging flow. At the water’s surface, it drops to about half [6].

figure 1
Fig. 1

Extensive experimental studies have been conducted to investigate flow patterns for various physical geometries (i.e., bed slope, pool length, and weir height) [2]. Guiny et al. [7] modified the standard design by adding vertical slots, orifices, and weirs in fishways. The efficiency of the orifices and vertical slots was related to the velocities at their entrances. In the laboratory experiments of Yagci [8], the three-dimensional (3D) mean flow and turbulence structure of a pool weir fishway combined with an orifice and a slot is investigated. It is shown that the energy dissipation per unit volume and the discharge have a linear relationship.

Considering the beneficial characteristics reported in the limited studies of researchers on the labyrinth weir in the pool-weir-type fishway, and knowing that the characteristics of flow in pool-weir-type fishways are highly dependent on the geometry of the weir, an alternative design of the rectangular labyrinth weir instead of the straight weirs in the pool-weir-type fishway is investigated in this study [79]. Kim [10] conducted experiments to compare the hydraulic characteristics of three different weir types in a pool-weir-type fishway. The results show that a straight, rectangular weir with a notch is preferable to a zigzag or trapezoidal weir. Studies on natural fish passes show that pass ability can be improved by lengthening the weir’s crest [7]. Zhong et al. [11] investigated the semi-rigid weir’s hydraulic performance in the fishway’s flow field with a pool weir. The results showed that this type of fishway performed better with a lower invert slope and a smaller radius ratio but with a larger pool spacing.

Considering that an alternative method to study the flow characteristics in a fishway with a pool weir is based on numerical methods and modeling from computational fluid dynamics (CFD), which can easily change the geometry of the fishway for different flow fields, this study uses the powerful package CFD and the software FLOW-3D to evaluate the proposed weir design and compare it with the conventional one to extend the application of the fishway. The main objective of this study was to evaluate the hydraulic performance of the rectangular labyrinth pool and the weir with submerged openings in different hydraulic configurations. The primary objective of creating a new weir configuration for suitable flow patterns is evaluated based on the swimming capabilities of different fish species. Specifically, the following questions will be answered: (a) How do the various hydraulic and geometric parameters relate to the effects of water velocity and turbulence, expressed as turbulent kinetic energy (TKE) and turbulence intensity (TI) within the fishway, i.e., are conventional weirs more affected by hydraulics than rectangular labyrinth weirs? (b) Which weir configurations have the greatest effect on fish performance in the fishway? (c) In the presence of an orifice plate, does the performance of each weir configuration differ with different weir spacing, bed gradients, and flow regimes from that without an orifice plate?

2 Materials and Methods

2.1 Physical Model Configuration

This paper focuses on Ead et al. [6]’s laboratory experiments as a reference, testing ten pool weirs (Fig. 2). The experimental flume was 6 m long, 0.56 m wide, and 0.6 m high, with a bottom slope of 10%. Field measurements were made at steady flow with a maximum flow rate of 0.165 m3/s. Discharge was measured with magnetic flow meters in the inlets and water level with point meters (see Ead et al. [6]. for more details). Table 1 summarizes the experimental conditions considered for model calibration in this study.

figure 2
Fig. 2

Table 1 Experimental conditions considered for calibration

Full size table

2.2 Numerical Models

Computational fluid dynamics (CFD) simulations were performed using FLOW-3D® v11.2 to validate a series of experimental liner pool weirs by Ead et al. [6] and to investigate the effects of the rectangular labyrinth pool weir with an orifice. The dimensions of the channel and data collection areas in the numerical models are the same as those of the laboratory model. Two types of pool weirs were considered: conventional and labyrinth. The proposed rectangular labyrinth pool weirs have a symmetrical cross section and are sized to fit within the experimental channel. The conventional pool weir model had a pool length of l = 0.685 and 0.342 m, a weir height of w = 0.141 m, a weir width of B = 0.56 m, and a channel slope of S0 = 5 and 10%. The rectangular labyrinth weirs have the same front width as the offset, i.e., a = b = c = 0.186 m. A square underwater opening with a width of 0.05 m and a depth of 0.05 m was created in the middle of the weir. The weir configuration considered in the present study is shown in Fig. 3.

figure 3
Fig. 3

2.3 Governing Equations

FLOW-3D® software solves the Navier–Stokes–Reynolds equations for three-dimensional analysis of incompressible flows using the fluid-volume method on a gridded domain. FLOW -3D® uses an advanced free surface flow tracking algorithm (TruVOF) developed by Hirt and Nichols [12], where fluid configurations are defined in terms of a VOF function F (xyzt). In this case, F (fluid fraction) represents the volume fraction occupied by the fluid: F = 1 in cells filled with fluid and F = 0 in cells without fluid (empty areas) [413]. The free surface area is at an intermediate value of F. (Typically, F = 0.5, but the user can specify a different intermediate value.) The equations in Cartesian coordinates (xyz) applicable to the model are as follows:

�f∂�∂�+∂(���x)∂�+∂(���y)∂�+∂(���z)∂�=�SOR

(1)

∂�∂�+1�f(��x∂�∂�+��y∂�∂�+��z∂�∂�)=−1�∂�∂�+�x+�x

(2)

∂�∂�+1�f(��x∂�∂�+��y∂�∂�+��z∂�∂�)=−1�∂�∂�+�y+�y

(3)

∂�∂�+1�f(��x∂�∂�+��y∂�∂�+��z∂�∂�)=−1�∂�∂�+�z+�z

(4)

where (uvw) are the velocity components, (AxAyAz) are the flow area components, (Gx, Gy, Gz) are the mass accelerations, and (fxfyfz) are the viscous accelerations in the directions (xyz), ρ is the fluid density, RSOR is the spring term, Vf is the volume fraction associated with the flow, and P is the pressure. The kε turbulence model (RNG) was used in this study to solve the turbulence of the flow field. This model is a modified version of the standard kε model that improves performance. The model is a two-equation model; the first equation (Eq. 5) expresses the turbulence’s energy, called turbulent kinetic energy (k) [14]. The second equation (Eq. 6) is the turbulent dissipation rate (ε), which determines the rate of dissipation of kinetic energy [15]. These equations are expressed as follows Dasineh et al. [4]:

∂(��)∂�+∂(����)∂��=∂∂��[������∂�∂��]+��−�ε

(5)

∂(�ε)∂�+∂(�ε��)∂��=∂∂��[�ε�eff∂ε∂��]+�1εε��k−�2ε�ε2�

(6)

In these equations, k is the turbulent kinetic energy, ε is the turbulent energy consumption rate, Gk is the generation of turbulent kinetic energy by the average velocity gradient, with empirical constants αε = αk = 1.39, C1ε = 1.42, and C2ε = 1.68, eff is the effective viscosity, μeff = μ + μt [15]. Here, μ is the hydrodynamic density coefficient, and μt is the turbulent density of the fluid.

2.4 Meshing and the Boundary Conditions in the Model Setup

The numerical area is divided into three mesh blocks in the X-direction. The meshes are divided into different sizes, a containing mesh block for the entire spatial domain and a nested block with refined cells for the domain of interest. Three different sizes were selected for each of the grid blocks. By comparing the accuracy of their results based on the experimental data, the reasonable mesh for the solution domain was finally selected. The convergence index method (GCI) evaluated the mesh sensitivity analysis. Based on this method, many researchers, such as Ahmadi et al. [16] and Ahmadi et al. [15], have studied the independence of numerical results from mesh size. Three different mesh sizes with a refinement ratio (r) of 1.33 were used to perform the convergence index method. The refinement ratio is the ratio between the larger and smaller mesh sizes (r = Gcoarse/Gfine). According to the recommendation of Celik et al. [17], the recommended number for the refinement ratio is 1.3, which gives acceptable results. Table 2 shows the characteristics of the three mesh sizes selected for mesh sensitivity analysis.Table 2 Characteristics of the meshes tested in the convergence analysis

Full size table

The results of u1 = umax (u1 = velocity component along the x1 axis and umax = maximum velocity of u1 in a section perpendicular to the invert of the fishway) at Q = 0.035 m3/s, × 1/l = 0.66, and Y1/b = 0 in the pool of conventional weir No. 4, obtained from the output results of the software, were used to evaluate the accuracy of the calculation range. As shown in Fig. 4x1 = the distance from a given weir in the x-direction, Y1 = the water depth measured in the y-direction, Y0 = the vertical distance in the Cartesian coordinate system, h = the water column at the crest, b = the distance between the two points of maximum velocity umax and zero velocity, and l = the pool length.

figure 4
Fig. 4

The apparent index of convergence (p) in the GCI method is calculated as follows:

�=ln⁡(�3−�2)(�2−�1)/ln⁡(�)

(7)

f1f2, and f3 are the hydraulic parameters obtained from the numerical simulation (f1 corresponds to the small mesh), and r is the refinement ratio. The following equation defines the convergence index of the fine mesh:

GCIfine=1.25|ε|��−1

(8)

Here, ε = (f2 − f1)/f1 is the relative error, and f2 and f3 are the values of hydraulic parameters considered for medium and small grids, respectively. GCI12 and GCI23 dimensionless indices can be calculated as:

GCI12=1.25|�2−�1�1|��−1

(9)

Then, the independence of the network is preserved. The convergence index of the network parameters obtained by Eqs. (7)–(9) for all three network variables is shown in Table 3. Since the GCI values for the smaller grid (GCI12) are lower compared to coarse grid (GCI23), it can be concluded that the independence of the grid is almost achieved. No further change in the grid size of the solution domain is required. The calculated values (GCI23/rpGCI12) are close to 1, which shows that the numerical results obtained are within the convergence range. As a result, the meshing of the solution domain consisting of a block mesh with a mesh size of 0.012 m and a block mesh within a larger block mesh with a mesh size of 0.009 m was selected as the optimal mesh (Fig. 5).Table 3 GCI calculation

Full size table

figure 5
Fig. 5

The boundary conditions applied to the area are shown in Fig. 6. The boundary condition of specific flow rate (volume flow rate-Q) was used for the inlet of the flow. For the downstream boundary, the flow output (outflow-O) condition did not affect the flow in the solution area. For the Zmax boundary, the specified pressure boundary condition was used along with the fluid fraction = 0 (P). This type of boundary condition considers free surface or atmospheric pressure conditions (Ghaderi et al. [19]). The wall boundary condition is defined for the bottom of the channel, which acts like a virtual wall without friction (W). The boundary between mesh blocks and walls were considered a symmetrical condition (S).

figure 6
Fig. 6

The convergence of the steady-state solutions was controlled during the simulations by monitoring the changes in discharge at the inlet boundary conditions. Figure 7 shows the time series plots of the discharge obtained from the Model A for the three main discharges from the numerical results. The 8 s to reach the flow equilibrium is suitable for the case of the fish ladder with pool and weir. Almost all discharge fluctuations in the models are insignificant in time, and the flow has reached relative stability. The computation time for the simulations was between 6 and 8 h using a personal computer with eight cores of a CPU (Intel Core i7-7700K @ 4.20 GHz and 16 GB RAM).

figure 7
Fig. 7

3 Results

3.1 Verification of Numerical Results

Quantitative outcomes, including free surface and normalized velocity profiles obtained using FLOW-3D software, were reviewed and compared with the results of Ead et al. [6]. The fourth pool was selected to present the results and compare the experiment and simulation. For each quantity, the percentage of mean absolute error (MAPE (%)) and root-mean-square error (RMSE) are calculated. Equations (10) and (11) show the method used to calculate the errors.

MAPE(%)100×1�∑1�|�exp−�num�exp|

(10)

RMSE(−)1�∑1�(�exp−�num)2

(11)

Here, Xexp is the value of the laboratory data, Xnum is the numerical data value, and n is the amount of data. As shown in Fig. 8, let x1 = distance from a given weir in the x-direction and Y1 = water depth in the y-direction from the bottom. The trend of the surface profiles for each of the numerical results is the same as that of the laboratory results. The surface profiles of the plunging flows drop after the flow enters and then rises to approach the next weir. The RMSE and MAPE error values for Model A are 0.014 m and 3.11%, respectively, indicating acceptable agreement between numerical and laboratory results. Figure 9 shows the velocity vectors and plunging flow from the numerical results, where x and y are horizontal and vertical to the flow direction, respectively. It can be seen that the jet in the fish ladder pool has a relatively high velocity. The two vortices, i.e., the enclosed vortex rotating clockwise behind the weir and the surface vortex rotating counterclockwise above the jet, are observed for the regime of incident flow. The point where the jet meets the fish passage bed is shown in the figure. The normalized velocity profiles upstream and downstream of the impact points are shown in Fig. 10. The figure shows that the numerical results agree well with the experimental data of Ead et al. [6].

figure 8
Fig. 8
figure 9
Fig. 9
figure 10
Fig. 10

3.2 Flow Regime and Discharge-Depth Relationship

Depending on the geometric shape of the fishway, including the distance of the weir, the slope of the bottom, the height of the weir, and the flow conditions, the flow regime in the fishway is divided into three categories: dipping, transitional, and flow regimes [4]. In the plunging flow regime, the flow enters the pool through the weir, impacts the bottom of the fishway, and forms a hydraulic jump causing two eddies [220]. In the streamwise flow regime, the surface of the flow passing over the weir is almost parallel to the bottom of the channel. The transitional regime has intermediate flow characteristics between the submerged and flow regimes. To predict the flow regime created in the fishway, Ead et al. [6] proposed two dimensionless parameters, Qt* and L/w, where Qt* is the dimensionless discharge, L is the distance between weirs, and w is the height of the weir:

��∗=���0���

(12)

Q is the total discharge, B is the width of the channel, S0 is the slope of the bed, and g is the gravity acceleration. Figure 11 shows different ranges for each flow regime based on the slope of the bed and the distance between the pools in this study. The results of Baki et al. [21], Ead et al. [6] and Dizabadi et al. [22] were used for this comparison. The distance between the pools affects the changes in the regime of the fish ladder. So, if you decrease the distance between weirs, the flow regime more likely becomes. This study determined all three flow regimes in a fish ladder. When the corresponding range of Qt* is less than 0.6, the flow regime can dip at values of L/B = 1.83. If the corresponding range of Qt* is greater than 0.5, transitional flow may occur at L/B = 1.22. On the other hand, when Qt* is greater than 1, streamwise flow can occur at values of L/B = 0.61. These observations agree well with the results of Baki et al. [21], Ead et al. [6] and Dizabadi et al. [22].

figure 11
Fig. 11

For plunging flows, another dimensionless discharge (Q+) versus h/w given by Ead et al. [6] was used for further evaluation:

�+=��ℎ�ℎ=23�d�

(13)

where h is the water depth above the weir, and Cd is the discharge coefficient. Figure 12a compares the numerical and experimental results of Ead et al. [6]. In this figure, Rehbock’s empirical equation is used to estimate the discharge coefficient of Ead et al. [6].

�d=0.57+0.075ℎ�

(14)

figure 12
Fig. 12

The numerical results for the conventional weir (Model A) and the rectangular labyrinth weir (Model B) of this study agree well with the laboratory results of Ead et al. [6]. When comparing models A and B, it is also found that a rectangular labyrinth weir has larger Q + values than the conventional weir as the length of the weir crest increases for a given channel width and fixed headwater elevation. In Fig. 12b, Models A and B’s flow depth plot shows the plunging flow regime. The power trend lines drawn through the data are the best-fit lines. The data shown in Fig. 12b are for different bed slopes and weir geometries. For the conventional weir and the rectangular labyrinth weir at submerged flow, Q can be assumed to be proportional to 1.56 and 1.47h, respectively. In the results of Ead et al. [6], Q is proportional to 1.5h. If we assume that the flow through the orifice is Qo and the total outflow is Q, the change in the ratio of Qo/Q to total outflow for models A and B can be shown in Fig. 13. For both models, the flow through the orifice decreases as the total flow increases. A logarithmic trend line was also found between the total outflow and the dimensionless ratio Qo/Q.

figure 13
Fig. 13

3.3 Depth-Averaged Velocity Distributions

To ensure that the target fish species can pass the fish ladder with maximum efficiency, the average velocity in the fish ladder should be low enough [4]. Therefore, the average velocity in depth should be as much as possible below the critical swimming velocities of the target fishes at a constant flow depth in the pool [20]. The contour plot of depth-averaged velocity was used instead of another direction, such as longitudinal velocity because fish are more sensitive to depth-averaged flow velocity than to its direction under different hydraulic conditions. Figure 14 shows the distribution of depth-averaged velocity in the pool for Models A and B in two cases with and without orifice plates. Model A’s velocity within the pool differs slightly in the spanwise direction. However, no significant variation in velocity was observed. The flow is gradually directed to the sides as it passes through the rectangular labyrinth weir. This increases the velocity at the sides of the channel. Therefore, the high-velocity zone is located at the sides. The low velocity is in the downstream apex of the weir. This area may be suitable for swimming target fish. The presence of an opening in the weir increases the flow velocity at the opening and in the pool’s center, especially in Model A. The flow velocity increase caused by the models’ opening varied from 7.7 to 12.48%. Figure 15 illustrates the effect of the inverted slope on the averaged depth velocity distribution in the pool at low and high discharge. At constant discharge, flow velocity increases with increasing bed slope. In general, high flow velocity was found in the weir toe sidewall and the weir and channel sidewalls.

figure 14
Fig. 14
figure 15
Fig. 15

On the other hand, for a constant bed slope, the high-velocity area of the pool increases due to the increase in runoff. For both bed slopes and different discharges, the most appropriate path for fish to travel from upstream to downstream is through the middle of the cross section and along the top of the rectangular labyrinth weirs. The maximum dominant velocities for Model B at S0 = 5% were 0.83 and 1.01 m/s; at S0 = 10%, they were 1.12 and 1.61 m/s at low and high flows, respectively. The low mean velocities for the same distance and S0 = 5 and 10% were 0.17 and 0.26 m/s, respectively.

Figure 16 shows the contour of the averaged depth velocity for various distances from the weir at low and high discharge. The contour plot shows a large variation in velocity within short distances from the weir. At L/B = 0.61, velocities are low upstream and downstream of the top of the weir. The high velocities occur in the side walls of the weir and the channel. At L/B = 1.22, the low-velocity zone displaces the higher velocity in most of the pool. Higher velocities were found only on the sides of the channel. As the discharge increases, the velocity zone in the pool becomes wider. At L/B = 1.83, there is an area of higher velocities only upstream of the crest and on the sides of the weir. At high discharge, the prevailing maximum velocities for L/B = 0.61, 1.22, and 1.83 were 1.46, 1.65, and 1.84 m/s, respectively. As the distance between weirs increases, the range of maximum velocity increases.

figure 16
Fig. 16

On the other hand, the low mean velocity for these distances was 0.27, 0.44, and 0.72 m/s, respectively. Thus, the low-velocity zone decreases with increasing distance between weirs. Figure 17 shows the pattern distribution of streamlines along with the velocity contour at various distances from the weir for Q = 0.05 m3/s. A stream-like flow is generally formed in the pool at a small distance between weirs (L/B = 0.61). The rotation cell under the jet forms clockwise between the two weirs. At the distances between the spillways (L/B = 1.22), the transition regime of the flow is formed. The transition regime occurs when or shortly after the weir is flooded. The rotation cell under the jet is clockwise smaller than the flow regime and larger than the submergence regime. At a distance L/B = 1.83, a plunging flow is formed so that the plunging jet dips into the pool and extends downstream to the center of the pool. The clockwise rotation of the cell is bounded by the dipping jet of the weir and is located between the bottom and the side walls of the weir and the channel.

figure 17
Fig. 17

Figure 18 shows the average depth velocity bar graph for each weir at different bed slopes and with and without orifice plates. As the distance between weirs increases, all models’ average depth velocity increases. As the slope of the bottom increases and an orifice plate is present, the average depth velocity in the pool increases. In addition, the average pool depth velocity increases as the discharge increases. Among the models, Model A’s average depth velocity is higher than Model B’s. The variation in velocity ranged from 8.11 to 12.24% for the models without an orifice plate and from 10.26 to 16.87% for the models with an orifice plate.

figure 18
Fig. 18

3.4 Turbulence Characteristics

The turbulent kinetic energy is one of the important parameters reflecting the turbulent properties of the flow field [23]. When the k value is high, more energy and a longer transit time are required to migrate the target species. The turbulent kinetic energy is defined as follows:

�=12(�x′2+�y′2+�z′2)

(15)

where uxuy, and uz are fluctuating velocities in the xy, and z directions, respectively. An illustration of the TKE and the effects of the geometric arrangement of the weir and the presence of an opening in the weir is shown in Fig. 19. For a given bed slope, in Model A, the highest TKE values are uniformly distributed in the weir’s upstream portion in the channel’s cross section. In contrast, for the rectangular labyrinth weir (Model B), the highest TKE values are concentrated on the sides of the pool between the crest of the weir and the channel wall. The highest TKE value in Models A and B is 0.224 and 0.278 J/kg, respectively, at the highest bottom slope (S0 = 10%). In the downstream portion of the conventional weir and within the crest of the weir and the walls of the rectangular labyrinth, there was a much lower TKE value that provided the best conditions for fish to recover in the pool between the weirs. The average of the lowest TKE for bottom slopes of 5 and 10% in Model A is 0.041 and 0.056 J/kg, and for Model B, is 0.047 and 0.064 J/kg. The presence of an opening in the weirs reduces the area of the highest TKE within the pool. It also increases the resting areas for fish (lower TKE). The highest TKE at the highest bottom slope in Models A and B with an orifice is 0.208 and 0.191 J/kg, respectively.

figure 19
Fig. 19

Figure 20 shows the effect of slope on the longitudinal distribution of TKE in the pools. TKE values significantly increase for a given discharge with an increasing bottom slope. Thus, for a low bed slope (S0 = 5%), a large pool area has expanded with average values of 0.131 and 0.168 J/kg for low and high discharge, respectively. For a bed slope of S0 = 10%, the average TKE values are 0.176 and 0.234 J/kg. Furthermore, as the discharge increases, the area with high TKE values within the pool increases. Lower TKE values are observed at the apex of the labyrinth weir, at the corner of the wall downstream of the weir, and between the side walls of the weir and the channel wall for both bottom slopes. The effect of distance between weirs on TKE is shown in Fig. 21. Low TKE values were observed at low discharge and short distances between weirs. Low TKE values are located at the top of the rectangular labyrinth weir and the downstream corner of the weir wall. There is a maximum value of TKE at the large distances between weirs, L/B = 1.83, along the center line of the pool, where the dip jet meets the bottom of the bed. At high discharge, the maximum TKE value for the distance L/B = 0.61, 1.22, and 1.83 was 0.246, 0.322, and 0.417 J/kg, respectively. In addition, the maximum TKE range increases with the distance between weirs.

figure 20
Fig. 20
figure 21
Fig. 21

For TKE size, the average value (TKEave) is plotted against q in Fig. 22. For all models, the TKE values increase with increasing q. For example, in models A and B with L/B = 0.61 and a slope of 10%, the TKE value increases by 41.66 and 86.95%, respectively, as q increases from 0.1 to 0.27 m2/s. The TKE values in Model B are higher than Model A for a given discharge, bed slope, and weir distance. The TKEave in Model B is higher compared to Model A, ranging from 31.46 to 57.94%. The presence of an orifice in the weir reduces the TKE values in both weirs. The intensity of the reduction is greater in Model B. For example, in Models A and B with L/B = 0.61 and q = 0.1 m2/s, an orifice reduces TKEave values by 60.35 and 19.04%, respectively. For each model, increasing the bed slope increases the TKEave values in the pool. For example, for Model B with q = 0.18 m2/s, increasing the bed slope from 5 to 10% increases the TKEave value by 14.34%. Increasing the distance between weirs increases the TKEave values in the pool. For example, in Model B with S0 = 10% and q = 0.3 m2/s, the TKEave in the pool increases by 34.22% if you increase the distance between weirs from L/B = 0.61 to L/B = 0.183.

figure 22
Fig. 22

Cotel et al. [24] suggested that turbulence intensity (TI) is a suitable parameter for studying fish swimming performance. Figure 23 shows the plot of TI and the effects of the geometric arrangement of the weir and the presence of an orifice. In Model A, the highest TI values are found upstream of the weirs and are evenly distributed across the cross section of the channel. The TI values increase as you move upstream to downstream in the pool. For the rectangular labyrinth weir, the highest TI values were concentrated on the sides of the pool, between the top of the weir and the side wall of the channel, and along the top of the weir. Downstream of the conventional weir, within the apex of the weir, and at the corners of the walls of the rectangular labyrinth weir, the percentage of TI was low. At the highest discharge, the average range of TI in Models A and B was 24–45% and 15–62%, respectively. The diversity of TI is greater in the rectangular labyrinth weir than the conventional weir. Fish swimming performance is reduced due to higher turbulence intensity. However, fish species may prefer different disturbance intensities depending on their swimming abilities; for example, Salmo trutta prefers a disturbance intensity of 18–53% [25]. Kupferschmidt and Zhu [26] found a higher range of TI for fishways, such as natural rock weirs, of 40–60%. The presence of an orifice in the weir increases TI values within the pool, especially along the middle portion of the cross section of the fishway. With an orifice in the weir, the average range of TI in Models A and B was 28–59% and 22–73%, respectively.

figure 23
Fig. 23

The effect of bed slope on TI variation is shown in Fig. 24. TI increases in different pool areas as the bed slope increases for a given discharge. For a low bed slope (S0 = 5%), a large pool area has increased from 38 to 63% and from 56 to 71% for low and high discharge, respectively. For a bed slope of S0 = 10%, the average values of TI are 45–67% and 61–73% for low and high discharge, respectively. Therefore, as runoff increases, the area with high TI values within the pool increases. A lower TI is observed for both bottom slopes in the corner of the wall, downstream of the crest walls, and between the side walls in the weir and channel. Figure 25 compares weir spacing with the distribution of TI values within the pool. The TI values are low at low flows and short distances between weirs. A maximum value of TI occurs at long spacing and where the plunging stream impinges on the bed and the area around the bed. TI ranges from 36 to 57%, 58–72%, and 47–76% for the highest flow in a wide pool area for L/B = 0.61, 1.22, and 1.83, respectively.

figure 24
Fig. 24
figure 25
Fig. 25

The average value of turbulence intensity (TIave) is plotted against q in Fig. 26. The increase in TI values with the increase in q values is seen in all models. For example, the average values of TI for Models A and B at L/B = 0.61 and slope of 10% increased from 23.9 to 33.5% and from 42 to 51.8%, respectively, with the increase in q from 0.1 to 0.27 m2/s. For a given discharge, a given gradient, and a given spacing of weirs, the TIave is higher in Model B than Model A. The presence of an orifice in the weirs increases the TI values in both types. For example, in Models A and B with L/B = 0.61 and q = 0.1 m2/s, the presence of an orifice increases TIave from 23.9 to 37.1% and from 42 to 48.8%, respectively. For each model, TIave in the pool increases with increasing bed slope. For Model B with q = 0.18 m2/s, TIave increases from 37.5 to 45.8% when you increase the invert slope from 5 to 10%. Increasing the distance between weirs increases the TIave in the pool. In Model B with S0 = 10% and q = 0.3 m2/s, the TIave in the pool increases from 51.8 to 63.7% as the distance between weirs increases from L/B = 0.61 to L/B = 0.183.

figure 26
Fig. 26

3.5 Energy Dissipation

To facilitate the passage of various target species through the pool of fishways, it is necessary to pay attention to the energy dissipation of the flow and to keep the flow velocity in the pool slow. The average volumetric energy dissipation (k) in the pool is calculated using the following basic formula:

�=����0��

(16)

where ρ is the water density, and H is the average water depth of the pool. The change in k versus Q for all models at two bottom slopes, S0 = 5%, and S0 = 10%, is shown in Fig. 27. Like the results of Yagci [8] and Kupferschmidt and Zhu [26], at a constant bottom slope, the energy dissipation in the pool increases with increasing discharge. The trend of change in k as a function of Q from the present study at a bottom gradient of S0 = 5% is also consistent with the results of Kupferschmidt and Zhu [26] for the fishway with rock weir. The only difference between the results is the geometry of the fishway and the combination of boulders instead of a solid wall. Comparison of the models shows that the conventional model has lower energy dissipation than the rectangular labyrinth for a given discharge. Also, increasing the distance between weirs decreases the volumetric energy dissipation for each model with the same bed slope. Increasing the slope of the bottom leads to an increase in volumetric energy dissipation, and an opening in the weir leads to a decrease in volumetric energy dissipation for both models. Therefore, as a guideline for volumetric energy dissipation, if the value within the pool is too high, the increased distance of the weir, the decreased slope of the bed, or the creation of an opening in the weir would decrease the volumetric dissipation rate.

figure 27
Fig. 27

To evaluate the energy dissipation inside the pool, the general method of energy difference in two sections can use:

ε=�1−�2�1

(17)

where ε is the energy dissipation rate, and E1 and E2 are the specific energies in Sects. 1 and 2, respectively. The distance between Sects. 1 and 2 is the same. (L is the distance between two upstream and downstream weirs.) Figure 28 shows the changes in ε relative to q (flow per unit width). The rectangular labyrinth weir (Model B) has a higher energy dissipation rate than the conventional weir (Model A) at a constant bottom gradient. For example, at S0 = 5%, L/B = 0.61, and q = 0.08 m3/s.m, the energy dissipation rate in Model A (conventional weir) was 0.261. In Model B (rectangular labyrinth weir), however, it was 0.338 (22.75% increase). For each model, the energy dissipation rate within the pool increases as the slope of the bottom increases. For Model B with L/B = 1.83 and q = 0.178 m3/s.m, the energy dissipation rate at S0 = 5% and 10% is 0.305 and 0.358, respectively (14.8% increase). Figure 29 shows an orifice’s effect on the pools’ energy dissipation rate. With an orifice in the weir, both models’ energy dissipation rates decreased. Thus, the reduction in energy dissipation rate varied from 7.32 to 9.48% for Model A and from 8.46 to 10.57 for Model B.

figure 28
Fig. 28
figure 29
Fig. 29

4 Discussion

This study consisted of entirely of numerical analysis. Although this study was limited to two weirs, the hydraulic performance and flow characteristics in a pooled fishway are highlighted by the rectangular labyrinth weir and its comparison with the conventional straight weir. The study compared the numerical simulations with laboratory experiments in terms of surface profiles, velocity vectors, and flow characteristics in a fish ladder pool. The results indicate agreement between the numerical and laboratory data, supporting the reliability of the numerical model in capturing the observed phenomena.

When the configuration of the weir changes to a rectangular labyrinth weir, the flow characteristics, the maximum and minimum area, and even the location of each hydraulic parameter change compared to a conventional weir. In the rectangular labyrinth weir, the flow is gradually directed to the sides as it passes the weir. This increases the velocity at the sides of the channel [21]. Therefore, the high-velocity area is located on the sides. In the downstream apex of the weir, the flow velocity is low, and this area may be suitable for swimming target fish. However, no significant change in velocity was observed at the conventional weir within the fish ladder. This resulted in an average increase in TKE of 32% and an average increase in TI of about 17% compared to conventional weirs.

In addition, there is a slight difference in the flow regime for both weir configurations. In addition, the rectangular labyrinth weir has a higher energy dissipation rate for a given discharge and constant bottom slope than the conventional weir. By reducing the distance between the weirs, this becomes even more intense. Finally, the presence of an orifice in both configurations of the weir increased the flow velocity at the orifice and in the middle of the pool, reducing the highest TKE value and increasing the values of TI within the pool of the fish ladder. This resulted in a reduction in volumetric energy dissipation for both weir configurations.

The results of this study will help the reader understand the direct effects of the governing geometric parameters on the hydraulic characteristics of a fishway with a pool and weir. However, due to the limited configurations of the study, further investigation is needed to evaluate the position of the weir’s crest on the flow direction and the difference in flow characteristics when combining boulders instead of a solid wall for this type of labyrinth weir [26]. In addition, hydraulic engineers and biologists must work together to design an effective fishway with rectangular labyrinth configurations. The migration habits of the target species should be considered when designing the most appropriate design [27]. Parametric studies and field observations are recommended to determine the perfect design criteria.

The current study focused on comparing a rectangular labyrinth weir with a conventional straight weir. Further research can explore other weir configurations, such as variations in crest position, different shapes of labyrinth weirs, or the use of boulders instead of solid walls. This would help understand the influence of different geometric parameters on hydraulic characteristics.

5 Conclusions

A new layout of the weir was evaluated, namely a rectangular labyrinth weir compared to a straight weir in a pool and weir system. The differences between the weirs were highlighted, particularly how variations in the geometry of the structures, such as the shape of the weir, the spacing of the weir, the presence of an opening at the weir, and the slope of the bottom, affect the hydraulics within the structures. The main findings of this study are as follows:

  • The calculated dimensionless discharge (Qt*) confirmed three different flow regimes: when the corresponding range of Qt* is smaller than 0.6, the regime of plunging flow occurs for values of L/B = 1.83. (L: distance of the weir; B: channel width). When the corresponding range of Qt* is greater than 0.5, transitional flow occurs at L/B = 1.22. On the other hand, if Qt* is greater than 1, the streaming flow is at values of L/B = 0.61.
  • For the conventional weir and the rectangular labyrinth weir with the plunging flow, it can be assumed that the discharge (Q) is proportional to 1.56 and 1.47h, respectively (h: water depth above the weir). This information is useful for estimating the discharge based on water depth in practical applications.
  • In the rectangular labyrinth weir, the high-velocity zone is located on the side walls between the top of the weir and the channel wall. A high-velocity variation within short distances of the weir. Low velocity occurs within the downstream apex of the weir. This area may be suitable for swimming target fish.
  • As the distance between weirs increased, the zone of maximum velocity increased. However, the zone of low speed decreased. The prevailing maximum velocity for a rectangular labyrinth weir at L/B = 0.61, 1.22, and 1.83 was 1.46, 1.65, and 1.84 m/s, respectively. The low mean velocities for these distances were 0.27, 0.44, and 0.72 m/s, respectively. This finding highlights the importance of weir spacing in determining the flow characteristics within the fishway.
  • The presence of an orifice in the weir increased the flow velocity at the orifice and in the middle of the pool, especially in a conventional weir. The increase ranged from 7.7 to 12.48%.
  • For a given bottom slope, in a conventional weir, the highest values of turbulent kinetic energy (TKE) are uniformly distributed in the upstream part of the weir in the cross section of the channel. In contrast, for the rectangular labyrinth weir, the highest TKE values were concentrated on the sides of the pool between the crest of the weir and the channel wall. The highest TKE value for the conventional and the rectangular labyrinth weir was 0.224 and 0.278 J/kg, respectively, at the highest bottom slope (S0 = 10%).
  • For a given discharge, bottom slope, and weir spacing, the average values of TI are higher for the rectangular labyrinth weir than for the conventional weir. At the highest discharge, the average range of turbulence intensity (TI) for the conventional and rectangular labyrinth weirs was between 24 and 45% and 15% and 62%, respectively. This reveals that the rectangular labyrinth weir may generate more turbulent flow conditions within the fishway.
  • For a given discharge and constant bottom slope, the rectangular labyrinth weir has a higher energy dissipation rate than the conventional weir (22.75 and 34.86%).
  • Increasing the distance between weirs decreased volumetric energy dissipation. However, increasing the gradient increased volumetric energy dissipation. The presence of an opening in the weir resulted in a decrease in volumetric energy dissipation for both model types.

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비선형 파력의 영향에 따른 잔해 언덕 방파제 형상의 효과에 대한 수치 분석

비선형 파력의 영향에 따른 잔해 언덕 방파제 형상의 효과에 대한 수치 분석

Numerical Analysis of the Effects of Rubble Mound Breakwater Geometry Under the Effect of Nonlinear Wave Force

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Abstract

Assessing the interaction of waves and porous offshore structures such as rubble mound breakwaters plays a critical role in designing such structures optimally. This study focused on the effect of the geometric parameters of a sloped rubble mound breakwater, including the shape of the armour, method of its arrangement, and the breakwater slope. Thus, three main design criteria, including the wave reflection coefficient (Kr), transmission coefficient (Kt), and depreciation wave energy coefficient (Kd), are discussed. Based on the results, a decrease in wavelength reduced the Kr and increased the Kt and Kd. The rubble mound breakwater with the Coreloc armour layer could exhibit the lowest Kr compared to other armour geometries. In addition, a decrease in the breakwater slope reduced the Kr and Kd by 3.4 and 1.25%, respectively. In addition, a decrease in the breakwater slope from 33 to 25° increased the wave breaking height by 6.1% on average. Further, a decrease in the breakwater slope reduced the intensity of turbulence depreciation. Finally, the armour geometry and arrangement of armour layers on the breakwater with its different slopes affect the wave behaviour and interaction between the wave and breakwater. Thus, layering on the breakwater and the correct use of the geometric shapes of the armour should be considered when designing such structures.

파도와 잔해 더미 방파제와 같은 다공성 해양 구조물의 상호 작용을 평가하는 것은 이러한 구조물을 최적으로 설계하는 데 중요한 역할을 합니다. 본 연구는 경사진 잔해 둔덕 방파제의 기하학적 매개변수의 효과에 초점을 맞추었는데, 여기에는 갑옷의 형태, 배치 방법, 방파제 경사 등이 포함된다. 따라서 파동 반사 계수(Kr), 투과 계수(Kt) 및 감가상각파 에너지 계수(Kd)에 대해 논의합니다. 결과에 따르면 파장이 감소하면 K가 감소합니다.r그리고 K를 증가시켰습니다t 및 Kd. Coreloc 장갑 층이 있는 잔해 언덕 방파제는 가장 낮은 K를 나타낼 수 있습니다.r 다른 갑옷 형상과 비교했습니다. 또한 방파제 경사가 감소하여 K가 감소했습니다.r 및 Kd 각각 3.4%, 1.25% 증가했다. 또한 방파제 경사가 33°에서 25°로 감소하여 파도 파쇄 높이가 평균 6.1% 증가했습니다. 또한, 방파제 경사의 감소는 난류 감가상각의 강도를 감소시켰다. 마지막으로, 경사가 다른 방파제의 장갑 형상과 장갑 층의 배열은 파도 거동과 파도와 방파제 사이의 상호 작용에 영향을 미칩니다. 따라서 이러한 구조를 설계 할 때 방파제에 층을 쌓고 갑옷의 기하학적 모양을 올바르게 사용하는 것을 고려해야합니다.

Keywords

  • Rubble mound breakwater
  • Computational fluid dynamics
  • Armour layer
  • Wave reflection coefficient
  • Wave transmission coefficient
  • Wave energy dissipation coefficient

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Effects of surface roughness on overflow discharge of embankment weirs

표면 거칠기가 제방 둑의 오버플로 배출에 미치는 영향

Effects of surface roughness on overflow discharge of embankment weirs

Abstract

A numerical study was performed on the embankment weir overflows with various surface roughness and tailwater submergence, to better understand the effects of weir roughness on discharge performances under the free and submerged conditions. The variation of flow regime is captured, from the free overflow, submerged hydraulic jump, to surface flow with increasing tailwater depth. A roughness factor is introduced to reflect the reduction in discharge caused by weir roughness. The roughness factor decreases with the roughness height, and it also depends on the tailwater depth, highlighting various relations of the roughness factor with the roughness height between different flow regimes, which is linear for the free overflow and submerged hydraulic jump while exponential for the surface flow. Accordingly, the effects of weir roughness on overflow discharge appear nonnegligible for the significant roughness height and the surface flow regime occurring under considerable tailwater submergence. The established empirical expressions of discharge coefficient and submergence and roughness factors make it possible to predict the discharge over embankment weirs considering both tailwater submergence and surface roughness.

자유 및 침수 조건에서 방류 성능에 대한 둑 거칠기의 영향을 더 잘 이해하기 위해 다양한 표면 거칠기와 테일워터 침수를 갖는 제방 둑 범람에 대한 수치 연구가 수행되었습니다.

자유 범람, 수중 수압 점프, 테일워터 깊이가 증가하는 표면 유동에 이르기까지 유동 체제의 변화가 캡처됩니다. 위어 거칠기로 인한 배출 감소를 반영하기 위해 거칠기 계수가 도입되었습니다.

조도 계수는 조도 높이와 함께 감소하고, 또한 테일워터 깊이에 따라 달라지며, 서로 다른 흐름 영역 사이의 조도 높이와 조도 계수의 다양한 관계를 강조합니다.

이는 자유 범람 및 수중 수압 점프에 대해 선형인 반면 표면에 대해 지수적입니다. 흐름. 따라서 월류 방류에 대한 웨어 조도의 영향은 상당한 조도 높이와 상당한 방수 침수 하에서 발생하는 표면 흐름 체제에 대해 무시할 수 없는 것으로 보입니다.

방류계수와 침수 및 조도계수의 확립된 실증식은 방류수 침수와 지표조도를 모두 고려한 제방보 위의 방류량을 예측할 수 있게 합니다.

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Figure 2 Modeling the plant with cylindrical tubes at the bottom of the canal.

Optimized Vegetation Density to Dissipate Energy of Flood Flow in Open Canals

열린 운하에서 홍수 흐름의 에너지를 분산시키기 위해 최적화된 식생 밀도

Mahdi Feizbahr,1Navid Tonekaboni,2Guang-Jun Jiang,3,4and Hong-Xia Chen3,4
Academic Editor: Mohammad Yazdi

Abstract

강을 따라 식생은 조도를 증가시키고 평균 유속을 감소시키며, 유동 에너지를 감소시키고 강 횡단면의 유속 프로파일을 변경합니다. 자연의 많은 운하와 강은 홍수 동안 초목으로 덮여 있습니다. 운하의 조도는 식물의 영향을 많이 받기 때문에 홍수시 유동저항에 큰 영향을 미친다. 식물로 인한 흐름에 대한 거칠기 저항은 흐름 조건과 식물에 따라 달라지므로 모델은 유속, 유속 깊이 및 수로를 따라 식생 유형의 영향을 고려하여 유속을 시뮬레이션해야 합니다. 총 48개의 모델을 시뮬레이션하여 근관의 거칠기 효과를 조사했습니다. 결과는 속도를 높임으로써 베드 속도를 감소시키는 식생의 영향이 무시할만하다는 것을 나타냅니다.

Abstract

Vegetation along the river increases the roughness and reduces the average flow velocity, reduces flow energy, and changes the flow velocity profile in the cross section of the river. Many canals and rivers in nature are covered with vegetation during the floods. Canal’s roughness is strongly affected by plants and therefore it has a great effect on flow resistance during flood. Roughness resistance against the flow due to the plants depends on the flow conditions and plant, so the model should simulate the current velocity by considering the effects of velocity, depth of flow, and type of vegetation along the canal. Total of 48 models have been simulated to investigate the effect of roughness in the canal. The results indicated that, by enhancing the velocity, the effect of vegetation in decreasing the bed velocity is negligible, while when the current has lower speed, the effect of vegetation on decreasing the bed velocity is obviously considerable.

1. Introduction

Considering the impact of each variable is a very popular field within the analytical and statistical methods and intelligent systems [114]. This can help research for better modeling considering the relation of variables or interaction of them toward reaching a better condition for the objective function in control and engineering [1527]. Consequently, it is necessary to study the effects of the passive factors on the active domain [2836]. Because of the effect of vegetation on reducing the discharge capacity of rivers [37], pruning plants was necessary to improve the condition of rivers. One of the important effects of vegetation in river protection is the action of roots, which cause soil consolidation and soil structure improvement and, by enhancing the shear strength of soil, increase the resistance of canal walls against the erosive force of water. The outer limbs of the plant increase the roughness of the canal walls and reduce the flow velocity and deplete the flow energy in vicinity of the walls. Vegetation by reducing the shear stress of the canal bed reduces flood discharge and sedimentation in the intervals between vegetation and increases the stability of the walls [3841].

One of the main factors influencing the speed, depth, and extent of flood in this method is Manning’s roughness coefficient. On the other hand, soil cover [42], especially vegetation, is one of the most determining factors in Manning’s roughness coefficient. Therefore, it is expected that those seasonal changes in the vegetation of the region will play an important role in the calculated value of Manning’s roughness coefficient and ultimately in predicting the flood wave behavior [4345]. The roughness caused by plants’ resistance to flood current depends on the flow and plant conditions. Flow conditions include depth and velocity of the plant, and plant conditions include plant type, hardness or flexibility, dimensions, density, and shape of the plant [46]. In general, the issue discussed in this research is the optimization of flood-induced flow in canals by considering the effect of vegetation-induced roughness. Therefore, the effect of plants on the roughness coefficient and canal transmission coefficient and in consequence the flow depth should be evaluated [4748].

Current resistance is generally known by its roughness coefficient. The equation that is mainly used in this field is Manning equation. The ratio of shear velocity to average current velocity  is another form of current resistance. The reason for using the  ratio is that it is dimensionless and has a strong theoretical basis. The reason for using Manning roughness coefficient is its pervasiveness. According to Freeman et al. [49], the Manning roughness coefficient for plants was calculated according to the Kouwen and Unny [50] method for incremental resistance. This method involves increasing the roughness for various surface and plant irregularities. Manning’s roughness coefficient has all the factors affecting the resistance of the canal. Therefore, the appropriate way to more accurately estimate this coefficient is to know the factors affecting this coefficient [51].

To calculate the flow rate, velocity, and depth of flow in canals as well as flood and sediment estimation, it is important to evaluate the flow resistance. To determine the flow resistance in open ducts, Manning, Chézy, and Darcy–Weisbach relations are used [52]. In these relations, there are parameters such as Manning’s roughness coefficient (n), Chézy roughness coefficient (C), and Darcy–Weisbach coefficient (f). All three of these coefficients are a kind of flow resistance coefficient that is widely used in the equations governing flow in rivers [53].

The three relations that express the relationship between the average flow velocity (V) and the resistance and geometric and hydraulic coefficients of the canal are as follows:where nf, and c are Manning, Darcy–Weisbach, and Chézy coefficients, respectively. V = average flow velocity, R = hydraulic radius, Sf = slope of energy line, which in uniform flow is equal to the slope of the canal bed,  = gravitational acceleration, and Kn is a coefficient whose value is equal to 1 in the SI system and 1.486 in the English system. The coefficients of resistance in equations (1) to (3) are related as follows:

Based on the boundary layer theory, the flow resistance for rough substrates is determined from the following general relation:where f = Darcy–Weisbach coefficient of friction, y = flow depth, Ks = bed roughness size, and A = constant coefficient.

On the other hand, the relationship between the Darcy–Weisbach coefficient of friction and the shear velocity of the flow is as follows:

By using equation (6), equation (5) is converted as follows:

Investigation on the effect of vegetation arrangement on shear velocity of flow in laboratory conditions showed that, with increasing the shear Reynolds number (), the numerical value of the  ratio also increases; in other words the amount of roughness coefficient increases with a slight difference in the cases without vegetation, checkered arrangement, and cross arrangement, respectively [54].

Roughness in river vegetation is simulated in mathematical models with a variable floor slope flume by different densities and discharges. The vegetation considered submerged in the bed of the flume. Results showed that, with increasing vegetation density, canal roughness and flow shear speed increase and with increasing flow rate and depth, Manning’s roughness coefficient decreases. Factors affecting the roughness caused by vegetation include the effect of plant density and arrangement on flow resistance, the effect of flow velocity on flow resistance, and the effect of depth [4555].

One of the works that has been done on the effect of vegetation on the roughness coefficient is Darby [56] study, which investigates a flood wave model that considers all the effects of vegetation on the roughness coefficient. There are currently two methods for estimating vegetation roughness. One method is to add the thrust force effect to Manning’s equation [475758] and the other method is to increase the canal bed roughness (Manning-Strickler coefficient) [455961]. These two methods provide acceptable results in models designed to simulate floodplain flow. Wang et al. [62] simulate the floodplain with submerged vegetation using these two methods and to increase the accuracy of the results, they suggested using the effective height of the plant under running water instead of using the actual height of the plant. Freeman et al. [49] provided equations for determining the coefficient of vegetation roughness under different conditions. Lee et al. [63] proposed a method for calculating the Manning coefficient using the flow velocity ratio at different depths. Much research has been done on the Manning roughness coefficient in rivers, and researchers [496366] sought to obtain a specific number for n to use in river engineering. However, since the depth and geometric conditions of rivers are completely variable in different places, the values of Manning roughness coefficient have changed subsequently, and it has not been possible to choose a fixed number. In river engineering software, the Manning roughness coefficient is determined only for specific and constant conditions or normal flow. Lee et al. [63] stated that seasonal conditions, density, and type of vegetation should also be considered. Hydraulic roughness and Manning roughness coefficient n of the plant were obtained by estimating the total Manning roughness coefficient from the matching of the measured water surface curve and water surface height. The following equation is used for the flow surface curve:where  is the depth of water change, S0 is the slope of the canal floor, Sf is the slope of the energy line, and Fr is the Froude number which is obtained from the following equation:where D is the characteristic length of the canal. Flood flow velocity is one of the important parameters of flood waves, which is very important in calculating the water level profile and energy consumption. In the cases where there are many limitations for researchers due to the wide range of experimental dimensions and the variety of design parameters, the use of numerical methods that are able to estimate the rest of the unknown results with acceptable accuracy is economically justified.

FLOW-3D software uses Finite Difference Method (FDM) for numerical solution of two-dimensional and three-dimensional flow. This software is dedicated to computational fluid dynamics (CFD) and is provided by Flow Science [67]. The flow is divided into networks with tubular cells. For each cell there are values of dependent variables and all variables are calculated in the center of the cell, except for the velocity, which is calculated at the center of the cell. In this software, two numerical techniques have been used for geometric simulation, FAVOR™ (Fractional-Area-Volume-Obstacle-Representation) and the VOF (Volume-of-Fluid) method. The equations used at this model for this research include the principle of mass survival and the magnitude of motion as follows. The fluid motion equations in three dimensions, including the Navier–Stokes equations with some additional terms, are as follows:where  are mass accelerations in the directions xyz and  are viscosity accelerations in the directions xyz and are obtained from the following equations:

Shear stresses  in equation (11) are obtained from the following equations:

The standard model is used for high Reynolds currents, but in this model, RNG theory allows the analytical differential formula to be used for the effective viscosity that occurs at low Reynolds numbers. Therefore, the RNG model can be used for low and high Reynolds currents.

Weather changes are high and this affects many factors continuously. The presence of vegetation in any area reduces the velocity of surface flows and prevents soil erosion, so vegetation will have a significant impact on reducing destructive floods. One of the methods of erosion protection in floodplain watersheds is the use of biological methods. The presence of vegetation in watersheds reduces the flow rate during floods and prevents soil erosion. The external organs of plants increase the roughness and decrease the velocity of water flow and thus reduce its shear stress energy. One of the important factors with which the hydraulic resistance of plants is expressed is the roughness coefficient. Measuring the roughness coefficient of plants and investigating their effect on reducing velocity and shear stress of flow is of special importance.

Roughness coefficients in canals are affected by two main factors, namely, flow conditions and vegetation characteristics [68]. So far, much research has been done on the effect of the roughness factor created by vegetation, but the issue of plant density has received less attention. For this purpose, this study was conducted to investigate the effect of vegetation density on flow velocity changes.

In a study conducted using a software model on three density modes in the submerged state effect on flow velocity changes in 48 different modes was investigated (Table 1).

Table 1 

The studied models.

The number of cells used in this simulation is equal to 1955888 cells. The boundary conditions were introduced to the model as a constant speed and depth (Figure 1). At the output boundary, due to the presence of supercritical current, no parameter for the current is considered. Absolute roughness for floors and walls was introduced to the model (Figure 1). In this case, the flow was assumed to be nonviscous and air entry into the flow was not considered. After  seconds, this model reached a convergence accuracy of .

Figure 1 

The simulated model and its boundary conditions.

Due to the fact that it is not possible to model the vegetation in FLOW-3D software, in this research, the vegetation of small soft plants was studied so that Manning’s coefficients can be entered into the canal bed in the form of roughness coefficients obtained from the studies of Chow [69] in similar conditions. In practice, in such modeling, the effect of plant height is eliminated due to the small height of herbaceous plants, and modeling can provide relatively acceptable results in these conditions.

48 models with input velocities proportional to the height of the regular semihexagonal canal were considered to create supercritical conditions. Manning coefficients were applied based on Chow [69] studies in order to control the canal bed. Speed profiles were drawn and discussed.

Any control and simulation system has some inputs that we should determine to test any technology [7077]. Determination and true implementation of such parameters is one of the key steps of any simulation [237881] and computing procedure [8286]. The input current is created by applying the flow rate through the VFR (Volume Flow Rate) option and the output flow is considered Output and for other borders the Symmetry option is considered.

Simulation of the models and checking their action and responses and observing how a process behaves is one of the accepted methods in engineering and science [8788]. For verification of FLOW-3D software, the results of computer simulations are compared with laboratory measurements and according to the values of computational error, convergence error, and the time required for convergence, the most appropriate option for real-time simulation is selected (Figures 2 and 3 ).

Figure 2 

Modeling the plant with cylindrical tubes at the bottom of the canal.

Figure 3 

Velocity profiles in positions 2 and 5.

The canal is 7 meters long, 0.5 meters wide, and 0.8 meters deep. This test was used to validate the application of the software to predict the flow rate parameters. In this experiment, instead of using the plant, cylindrical pipes were used in the bottom of the canal.

The conditions of this modeling are similar to the laboratory conditions and the boundary conditions used in the laboratory were used for numerical modeling. The critical flow enters the simulation model from the upstream boundary, so in the upstream boundary conditions, critical velocity and depth are considered. The flow at the downstream boundary is supercritical, so no parameters are applied to the downstream boundary.

The software well predicts the process of changing the speed profile in the open canal along with the considered obstacles. The error in the calculated speed values can be due to the complexity of the flow and the interaction of the turbulence caused by the roughness of the floor with the turbulence caused by the three-dimensional cycles in the hydraulic jump. As a result, the software is able to predict the speed distribution in open canals.

2. Modeling Results

After analyzing the models, the results were shown in graphs (Figures 414 ). The total number of experiments in this study was 48 due to the limitations of modeling.


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Figure 4 

Flow velocity profiles for canals with a depth of 1 m and flow velocities of 3–3.3 m/s. Canal with a depth of 1 meter and a flow velocity of (a) 3 meters per second, (b) 3.1 meters per second, (c) 3.2 meters per second, and (d) 3.3 meters per second.

Figure 5 

Canal diagram with a depth of 1 meter and a flow rate of 3 meters per second.

Figure 6 

Canal diagram with a depth of 1 meter and a flow rate of 3.1 meters per second.

Figure 7 

Canal diagram with a depth of 1 meter and a flow rate of 3.2 meters per second.

Figure 8 

Canal diagram with a depth of 1 meter and a flow rate of 3.3 meters per second.


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Figure 9 

Flow velocity profiles for canals with a depth of 2 m and flow velocities of 4–4.3 m/s. Canal with a depth of 2 meters and a flow rate of (a) 4 meters per second, (b) 4.1 meters per second, (c) 4.2 meters per second, and (d) 4.3 meters per second.

Figure 10 

Canal diagram with a depth of 2 meters and a flow rate of 4 meters per second.

Figure 11 

Canal diagram with a depth of 2 meters and a flow rate of 4.1 meters per second.

Figure 12 

Canal diagram with a depth of 2 meters and a flow rate of 4.2 meters per second.

Figure 13 

Canal diagram with a depth of 2 meters and a flow rate of 4.3 meters per second.


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Figure 14 

Flow velocity profiles for canals with a depth of 3 m and flow velocities of 5–5.3 m/s. Canal with a depth of 2 meters and a flow rate of (a) 4 meters per second, (b) 4.1 meters per second, (c) 4.2 meters per second, and (d) 4.3 meters per second.

To investigate the effects of roughness with flow velocity, the trend of flow velocity changes at different depths and with supercritical flow to a Froude number proportional to the depth of the section has been obtained.

According to the velocity profiles of Figure 5, it can be seen that, with the increasing of Manning’s coefficient, the canal bed speed decreases.

According to Figures 5 to 8, it can be found that, with increasing the Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of the models 1 to 12, which can be justified by increasing the speed and of course increasing the Froude number.

According to Figure 10, we see that, with increasing Manning’s coefficient, the canal bed speed decreases.

According to Figure 11, we see that, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of Figures 510, which can be justified by increasing the speed and, of course, increasing the Froude number.

With increasing Manning’s coefficient, the canal bed speed decreases (Figure 12). But this deceleration is more noticeable than the deceleration of the higher models (Figures 58 and 1011), which can be justified by increasing the speed and, of course, increasing the Froude number.

According to Figure 13, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of Figures 5 to 12, which can be justified by increasing the speed and, of course, increasing the Froude number.

According to Figure 15, with increasing Manning’s coefficient, the canal bed speed decreases.

Figure 15 

Canal diagram with a depth of 3 meters and a flow rate of 5 meters per second.

According to Figure 16, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of the higher model, which can be justified by increasing the speed and, of course, increasing the Froude number.

Figure 16 

Canal diagram with a depth of 3 meters and a flow rate of 5.1 meters per second.

According to Figure 17, it is clear that, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of the higher models, which can be justified by increasing the speed and, of course, increasing the Froude number.

Figure 17 

Canal diagram with a depth of 3 meters and a flow rate of 5.2 meters per second.

According to Figure 18, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of the higher models, which can be justified by increasing the speed and, of course, increasing the Froude number.

Figure 18 

Canal diagram with a depth of 3 meters and a flow rate of 5.3 meters per second.

According to Figure 19, it can be seen that the vegetation placed in front of the flow input velocity has negligible effect on the reduction of velocity, which of course can be justified due to the flexibility of the vegetation. The only unusual thing is the unexpected decrease in floor speed of 3 m/s compared to higher speeds.


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Figure 19 

Comparison of velocity profiles with the same plant densities (depth 1 m). Comparison of velocity profiles with (a) plant densities of 25%, depth 1 m; (b) plant densities of 50%, depth 1 m; and (c) plant densities of 75%, depth 1 m.

According to Figure 20, by increasing the speed of vegetation, the effect of vegetation on reducing the flow rate becomes more noticeable. And the role of input current does not have much effect in reducing speed.


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Figure 20 

Comparison of velocity profiles with the same plant densities (depth 2 m). Comparison of velocity profiles with (a) plant densities of 25%, depth 2 m; (b) plant densities of 50%, depth 2 m; and (c) plant densities of 75%, depth 2 m.

According to Figure 21, it can be seen that, with increasing speed, the effect of vegetation on reducing the bed flow rate becomes more noticeable and the role of the input current does not have much effect. In general, it can be seen that, by increasing the speed of the input current, the slope of the profiles increases from the bed to the water surface and due to the fact that, in software, the roughness coefficient applies to the channel floor only in the boundary conditions, this can be perfectly justified. Of course, it can be noted that, due to the flexible conditions of the vegetation of the bed, this modeling can show acceptable results for such grasses in the canal floor. In the next directions, we may try application of swarm-based optimization methods for modeling and finding the most effective factors in this research [27815188994]. In future, we can also apply the simulation logic and software of this research for other domains such as power engineering [9599].


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Figure 21 

Comparison of velocity profiles with the same plant densities (depth 3 m). Comparison of velocity profiles with (a) plant densities of 25%, depth 3 m; (b) plant densities of 50%, depth 3 m; and (c) plant densities of 75%, depth 3 m.

3. Conclusion

The effects of vegetation on the flood canal were investigated by numerical modeling with FLOW-3D software. After analyzing the results, the following conclusions were reached:(i)Increasing the density of vegetation reduces the velocity of the canal floor but has no effect on the velocity of the canal surface.(ii)Increasing the Froude number is directly related to increasing the speed of the canal floor.(iii)In the canal with a depth of one meter, a sudden increase in speed can be observed from the lowest speed and higher speed, which is justified by the sudden increase in Froude number.(iv)As the inlet flow rate increases, the slope of the profiles from the bed to the water surface increases.(v)By reducing the Froude number, the effect of vegetation on reducing the flow bed rate becomes more noticeable. And the input velocity in reducing the velocity of the canal floor does not have much effect.(vi)At a flow rate between 3 and 3.3 meters per second due to the shallow depth of the canal and the higher landing number a more critical area is observed in which the flow bed velocity in this area is between 2.86 and 3.1 m/s.(vii)Due to the critical flow velocity and the slight effect of the roughness of the horseshoe vortex floor, it is not visible and is only partially observed in models 1-2-3 and 21.(viii)As the flow rate increases, the effect of vegetation on the rate of bed reduction decreases.(ix)In conditions where less current intensity is passing, vegetation has a greater effect on reducing current intensity and energy consumption increases.(x)In the case of using the flow rate of 0.8 cubic meters per second, the velocity distribution and flow regime show about 20% more energy consumption than in the case of using the flow rate of 1.3 cubic meters per second.

Nomenclature

n:Manning’s roughness coefficient
C:Chézy roughness coefficient
f:Darcy–Weisbach coefficient
V:Flow velocity
R:Hydraulic radius
g:Gravitational acceleration
y:Flow depth
Ks:Bed roughness
A:Constant coefficient
:Reynolds number
y/∂x:Depth of water change
S0:Slope of the canal floor
Sf:Slope of energy line
Fr:Froude number
D:Characteristic length of the canal
G:Mass acceleration
:Shear stresses.

Data Availability

All data are included within the paper.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This work was partially supported by the National Natural Science Foundation of China under Contract no. 71761030 and Natural Science Foundation of Inner Mongolia under Contract no. 2019LH07003.

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Figure 4. Field gate discharge experiment.

FLOW-3D Model Development for the Analysis of the Flow Characteristics of Downstream Hydraulic Structures

하류 유압 구조물의 유동 특성 분석을 위한 FLOW-3D 모델 개발

Beom-Jin Kim 1, Jae-Hong Hwang 2 and Byunghyun Kim 3,*
1 Advanced Structures and Seismic Safety Research Division, Korea Atomic Energy Research Institute,
Daejeon 34057, Korea
2 Korea Water Resources Corporation (K-Water), Daejeon 34350, Korea
3 Department of Civil Engineering, Kyungpook National University, Daegu 41566, Korea

  • Correspondence: bhkimc@knu.ac.kr; Tel.: +82-53-950-7819

Abstract

Hydraulic structures installed in rivers inevitably create a water level difference between upstream and downstream regions. The potential energy due to this difference in water level is converted into kinetic energy, causing high-velocity flow and hydraulic jumps in the river. As a result, problems such as scouring and sloping downstream may occur around the hydraulic structures. In this study, a FLOW-3D model was constructed to perform a numerical analysis of the ChangnyeongHaman weir in the Republic of Korea. The constructed model was verified based on surface velocity measurements from a field gate operation experiment. In the simulation results, the flow discharge differed from the measured value by 9–15 m3/s, from which the accuracy was evaluated to be 82–87%. The flow velocity was evaluated with an accuracy of 92% from a difference of 0.01 to 0.16 m/s. Following this verification, a flow analysis of the hydraulic structures was performed according to boundary conditions and operation conditions for numerous scenarios. Since 2018, the ChangnyeongHaman weir gate has been fully opened due to the implementation of Korea’s eco-environmental policy; therefore, in this study, the actual gate operation history data prior to 2018 was applied and evaluated. The evaluation conditions were a 50% open gate condition and the flow discharge of two cases with a large difference in water level. As a result of the analysis, the actual operating conditions showed that the velocity and the Froude number were lower than the optimal conditions, confirming that the selected design was appropriate. It was also found that in the bed protection section, the average flow velocity was high when the water level difference was large, whereas the bottom velocity was high when the gate opening was large. Ultimately, through the reviewed status survey data in this study, the downstream flow characteristics of hydraulic structures along with adequacy verification techniques, optimal design techniques such as procedures for design, and important considerations were derived. Based on the current results, the constructed FLOW-3D-based model can be applied to creating or updating flow analysis guidelines for future repair and reinforcement measures as well as hydraulic structure design.

하천에 설치되는 수력구조물은 필연적으로 상류와 하류의 수위차를 발생시킨다. 이러한 수위차로 인한 위치에너지는 운동에너지로 변환되어 하천의 고속유동과 수압점프를 일으킨다. 그 결과 수력구조물 주변에서 하류의 세굴, 경사 등의 문제가 발생할 수 있다.

본 연구에서는 대한민국 창녕함안보의 수치해석을 위해 FLOW-3D 모델을 구축하였다. 구축된 모델은 현장 게이트 작동 실험에서 표면 속도 측정을 기반으로 검증되었습니다.

시뮬레이션 결과에서 유량은 측정값과 9~15 m3/s 차이가 나고 정확도는 82~87%로 평가되었다. 유속은 0.01~0.16m/s의 차이에서 92%의 정확도로 평가되었습니다.

검증 후 다양한 시나리오에 대한 경계조건 및 운전조건에 따른 수리구조물의 유동해석을 수행하였다. 2018년부터 창녕함안보 문은 한국의 친환경 정책 시행으로 전면 개방되었습니다.

따라서 본 연구에서는 2018년 이전의 실제 게이트 운영 이력 데이터를 적용하여 평가하였다. 평가조건은 50% open gate 조건과 수위차가 큰 2가지 경우의 유수방류로 하였다. 해석 결과 실제 운전조건은 속도와 Froude수가 최적조건보다 낮아 선정된 설계가 적합함을 확인하였다.

또한 베드보호구간에서는 수위차가 크면 평균유속이 높고, 수문개구가 크면 저저유속이 높은 것으로 나타났다. 최종적으로 본 연구에서 검토한 실태조사 자료를 통해 적정성 검증기법과 함께 수력구조물의 하류 유동특성, 설계절차 등 최적 설계기법 및 중요 고려사항을 도출하였다.

현재의 결과를 바탕으로 구축된 FLOW-3D 기반 모델은 수력구조 설계뿐만 아니라 향후 보수 및 보강 조치를 위한 유동해석 가이드라인 생성 또는 업데이트에 적용할 수 있습니다.

Figure 1. Effect of downstream riverbed erosion according to the type of weir foundation.
Figure 1. Effect of downstream riverbed erosion according to the type of weir foundation.
Figure 2. Changnyeong-Haman weir depth survey results (June 2015)
Figure 2. Changnyeong-Haman weir depth survey results (June 2015)
Figure 4. Field gate discharge experiment.
Figure 4. Field gate discharge experiment.
Figure 16. Analysis results for Case 7 and Case 8
Figure 16. Analysis results for Case 7 and Case 8

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Numerical analysis of energy dissipator options using computational fluid dynamics modeling — a case study of Mirani Dam

전산 유체 역학 모델링을 사용한 에너지 소산자 옵션의 수치적 해석 — Mirani 댐의 사례 연구

Arabian Journal of Geosciences volume 15, Article number: 1614 (2022) Cite this article

Abstract

이 연구에서 FLOW 3D 전산 유체 역학(CFD) 소프트웨어를 사용하여 파키스탄 Mirani 댐 방수로에 대한 에너지 소산 옵션으로 미국 매립지(USBR) 유형 II 및 USBR 유형 III 유역의 성능을 추정했습니다. 3D Reynolds 평균 Navier-Stokes 방정식이 해결되었으며, 여기에는 여수로 위의 자유 표면 흐름을 캡처하기 위해 공기 유입, 밀도 평가 및 드리프트-플럭스에 대한 하위 그리드 모델이 포함되었습니다. 본 연구에서는 5가지 모델을 고려하였다. 첫 번째 모델에는 길이가 39.5m인 USBR 유형 II 정수기가 있습니다. 두 번째 모델에는 길이가 44.2m인 USBR 유형 II 정수기가 있습니다. 3번째와 4 번째모델에는 길이가 각각 48.8m인 USBR 유형 II 정수조와 39.5m의 USBR 유형 III 정수조가 있습니다. 다섯 번째 모델은 네 번째 모델과 동일하지만 마찰 및 슈트 블록 높이가 0.3m 증가했습니다. 최상의 FLOW 3D 모델 조건을 설정하기 위해 메쉬 민감도 분석을 수행했으며 메쉬 크기 0.9m에서 최소 오차를 산출했습니다. 세 가지 경계 조건 세트가 테스트되었으며 최소 오류를 제공하는 세트가 사용되었습니다. 수치적 검증은 USBR 유형 II( L = 48.8m), USBR 유형 III( L = 35.5m) 및 USBR 유형 III 의 물리적 모델 에너지 소산을 0.3m 블록 단위로 비교하여 수행되었습니다( L= 35.5m). 통계 분석 결과 평균 오차는 2.5%, RMSE(제곱 평균 제곱근 오차) 지수는 3% 미만이었습니다. 수리학적 및 경제성 분석을 바탕으로 4 번째 모델이 최적화된 에너지 소산기로 밝혀졌습니다. 흡수된 에너지 백분율 측면에서 물리적 모델과 수치적 모델 간의 최대 차이는 5% 미만인 것으로 나타났습니다.

In this study, the FLOW 3D computational fluid dynamics (CFD) software was used to estimate the performance of the United States Bureau of Reclamation (USBR) type II and USBR type III stilling basins as energy dissipation options for the Mirani Dam spillway, Pakistan. The 3D Reynolds-averaged Navier–Stokes equations were solved, which included sub-grid models for air entrainment, density evaluation, and drift–flux, to capture free-surface flow over the spillway. Five models were considered in this research. The first model has a USBR type II stilling basin with a length of 39.5 m. The second model has a USBR type II stilling basin with a length of 44.2 m. The 3rd and 4th models have a USBR type II stilling basin with a length of 48.8 m and a 39.5 m USBR type III stilling basin, respectively. The fifth model is identical to the fourth, but the friction and chute block heights have been increased by 0.3 m. To set up the best FLOW 3D model conditions, mesh sensitivity analysis was performed, which yielded a minimum error at a mesh size of 0.9 m. Three sets of boundary conditions were tested and the set that gave the minimum error was employed. Numerical validation was done by comparing the physical model energy dissipation of USBR type II (L = 48.8 m), USBR type III (L =35.5 m), and USBR type III with 0.3-m increments in blocks (L = 35.5 m). The statistical analysis gave an average error of 2.5% and a RMSE (root mean square error) index of less than 3%. Based on hydraulics and economic analysis, the 4th model was found to be an optimized energy dissipator. The maximum difference between the physical and numerical models in terms of percentage energy absorbed was found to be less than 5%.

Keywords

  • Numerical modeling
  • Spillway
  • Hydraulic jump
  • Energy dissipation
  • FLOW 3D

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Flow Field in a Sloped Channel with Damaged and Undamaged Piers: Numerical and Experimental Studies

Flow Field in a Sloped Channel with Damaged and Undamaged Piers: Numerical and Experimental Studies

Ehsan OveiciOmid Tayari & Navid Jalalkamali
KSCE Journal of Civil Engineering volume 25, pages4240–4251 (2021)Cite this article

Abstract

본 논문은 경사가 완만한 수로에서 손상되거나 손상되지 않은 교각 주변의 유동 패턴을 분석했습니다. 실험은 길이가 12m이고 기울기가 0.008인 직선 수로에서 수행되었습니다. Acoustic Doppler Velocimeter(ADV)를 이용하여 3차원 유속 데이터를 수집하였고, 그 결과를 PIV(Particle Image Velocimetry) 데이터와 분석하여 비교하였습니다.

다중 블록 옵션이 있는 취수구의 퇴적물 시뮬레이션(SSIIM)은 이 연구에서 흐름의 수치 시뮬레이션을 위해 통합되었습니다. 일반적으로 비교에서 얻은 결과는 수치 데이터와 실험 데이터 간의 적절한 일치를 나타냅니다. 결과는 모든 경우에 수로 입구에서 2m 거리에서 기복적 수압 점프가 발생했음을 보여주었습니다.

경사진 수로의 최대 베드 전단응력은 2개의 손상 및 손상되지 않은 교각을 설치하기 위한 수평 수로의 12배였습니다. 이와 같은 경사수로 교각의 위치에 따라 상류측 수위는 수평수로의 유사한 조건에 비해 72.5% 감소한 반면, 이 감소량은 경사면에서 다른 경우에 비해 8.3% 감소하였다. 채널 또한 두 교각이 있는 경우 최대 Froude 수는 수평 수로의 5.7배였습니다.

This paper analyzed the flow pattern around damaged and undamaged bridge piers in a channel with a mild slope. The experiments were carried out on a straight channel with a length of 12 meters and a slope of 0.008. Acoustic Doppler velocimeter (ADV) was employed to collect three-dimensional flow velocity data, and the results were analyzed and compared with particle image velocimetry (PIV) data. Sediment Simulation in Intakes with Multiblock option (SSIIM) was incorporated for the numerical simulation of the flow in this study. Generally, the results obtained from the comparisons referred to the appropriate agreement between the numerical and the experimental data. The results showed that an undular hydraulic jump occurred at a distance of two meters from the channel entrance in every case; the maximum bed shear stress in the sloped channel was 12 times that in a horizontal channel for installing two damaged and undamaged piers. With this position of the piers in the sloped channel, the upstream water level underwent a 72.5% reduction compared to similar conditions in a horizontal channel, while the amount of this water level decrease was equal to 8.3% compared to the other cases in a sloped channel. In addition, with the presence of both piers, the maximum Froude number was 5.7 times that in a horizontal channel.

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Figure 8: Instantaneous flow structures extracted using the Q-criterion (Qcriterion=1200) and colored by the magnitude of flow velocity.

Hybrid modeling on 3D hydraulic features of a step-pool unit

Chendi Zhang1
, Yuncheng Xu1,2, Marwan A Hassan3
, Mengzhen Xu1
, Pukang He1
1State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, 100084, China. 2
College of Water Resources and Civil Engineering, China Agricultural University, Beijing, 100081, China.
5 3Department of Geography, University of British Columbia, 1984 West Mall, Vancouver BC, V6T1Z2, Canada.
Correspondence to: Chendi Zhang (chendinorthwest@163.com) and Mengzhen Xu (mzxu@mail.tsinghua.edu.cn)

Abstract

스텝 풀 시스템은 계류의 일반적인 기반이며 전 세계의 하천 복원 프로젝트에 활용되었습니다. 스텝 풀 장치는 스텝 풀 기능의 형태학적 진화 및 안정성과 밀접하게 상호 작용하는 것으로 보고된 매우 균일하지 않은 수력 특성을 나타냅니다.

그러나 스텝 풀 형태에 대한 3차원 수리학의 자세한 정보는 측정의 어려움으로 인해 부족했습니다. 이러한 지식 격차를 메우기 위해 SfM(Structure from Motion) 및 CFD(Computational Fluid Dynamics) 기술을 기반으로 하이브리드 모델을 구축했습니다. 이 모델은 CFD 시뮬레이션을 위한 입력으로 6가지 유속의 자연석으로 만든 인공 스텝 풀 장치가 있는 침대 표면의 3D 재구성을 사용했습니다.

하이브리드 모델은 스텝 풀 장치에 대한 3D 흐름 구조의 고해상도 시각화를 제공하는 데 성공했습니다. 결과는 계단 아래의 흐름 영역의 분할, 즉 수면에서의 통합 점프, 침대 근처의 줄무늬 후류 및 그 사이의 고속 제트를 보여줍니다.

수영장에서 난류 에너지의 매우 불균일한 분포가 밝혀졌으며 비슷한 용량을 가진 두 개의 에너지 소산기가 수영장에 공존하는 것으로 나타났습니다. 흐름 증가에 따른 풀 세굴 개발은 점프 및 후류 와류의 확장으로 이어지지만 이러한 증가는 스텝 풀 실패에 대한 임계 조건에 가까운 높은 흐름에서 점프에 대해 멈춥니다.

음의 경사면에서 발달된 곡물 20 클러스터와 같은 미세 지반은 국부 수력학에 상당한 영향을 주지만 이러한 영향은 수영장 바닥에서 억제됩니다. 스텝 스톤의 항력은 가장 높은 흐름이 사용되기 전에 배출과 함께 증가하는 반면 양력은 더 큰 크기와 더 넓은 범위를 갖습니다. 우리의 결과는 계단 풀 형태의 복잡한 흐름 특성을 조사할 때 물리적 및 수치적 모델링을 결합한 하이브리드 모델 접근 방식의 가능성과 큰 잠재력을 강조합니다.

Step-pool systems are common bedforms in mountain streams and have been utilized in river restoration projects around the world. Step-pool units exhibit highly non-uniform hydraulic characteristics which have been reported to closely 10 interact with the morphological evolution and stability of step-pool features. However, detailed information of the threedimensional hydraulics for step-pool morphology has been scarce due to the difficulty of measurement. To fill in this knowledge gap, we established a hybrid model based on the technologies of Structure from Motion (SfM) and computational fluid dynamics (CFD). The model used 3D reconstructions of bed surfaces with an artificial step-pool unit built by natural stones at six flow rates as inputs for CFD simulations. The hybrid model succeeded in providing high-resolution visualization 15 of 3D flow structures for the step-pool unit. The results illustrate the segmentation of flow regimes below the step, i.e., the integral jump at the water surface, streaky wake vortexes near the bed, and high-speed jets in between. The highly non-uniform distribution of turbulence energy in the pool has been revealed and two energy dissipaters with comparable capacity are found to co-exist in the pool. Pool scour development under flow increase leads to the expansion of the jump and wake vortexes but this increase stops for the jump at high flows close to the critical condition for step-pool failure. The micro-bedforms as grain 20 clusters developed on the negative slope affect the local hydraulics significantly but this influence is suppressed at pool bottom. The drag forces on the step stones increase with discharge before the highest flow is used while the lift force has a larger magnitude and wider varying range. Our results highlight the feasibility and great potential of the hybrid model approach combining physical and numerical modeling in investigating the complex flow characteristics of step-pool morphology.

Figure 1: Workflow of the hybrid modeling. SfM-MVS refers to the technology of Structure from Motion with Multi View Stereo. DSM is short for digital surface model. RNG-VOF is short for Renormalized Group (RNG) k-ε turbulence model coupled with Volume of Fluid method.
Figure 1: Workflow of the hybrid modeling. SfM-MVS refers to the technology of Structure from Motion with Multi View Stereo. DSM is short for digital surface model. RNG-VOF is short for Renormalized Group (RNG) k-ε turbulence model coupled with Volume of Fluid method.
Figure 2: Flume experiment settings in Zhang et al., (2020): (a) the artificially built-up step-pool model using natural stones, with stone number labelled; (b) the unsteady hydrograph of the run of CIFR (continually-increasing-flow-rate) T2 used in this study.
Figure 2: Flume experiment settings in Zhang et al., (2020): (a) the artificially built-up step-pool model using natural stones, with stone number labelled; (b) the unsteady hydrograph of the run of CIFR (continually-increasing-flow-rate) T2 used in this study.
Figure 3: Setup of the CFD model: (a) three-dimensional digital surface model (DSM) of the step-pool unit by structure from motion with multi view stereo (SfM-MVS) method as the input to the 3D computational fluid dynamics (CFD) modeling; (b) extruded bed 160 surface model connected to the extra downstream component (in purple blue) and rectangular columns to fill leaks (in green), with the boundary conditions shown on mesh planes; (c) recognized geometry with mesh grids of two mesh blocks shown where MS is short for mesh size; (d) sampling volumes to capture the flow forces acting on each step stone at X, Y, and Z directions; and (e) an example for the simulated 3D flow over the step-pool unit colored by velocity magnitude at the discharge of 49.9 L/s. The abbreviations for boundary conditions in (b) are: V for specified velocity; C for continuative; P for specific pressure; and W for wall 165 condition. The contraction section in Figure (e) refers to the edge between the jet and jump at water surface.
Figure 3: Setup of the CFD model: (a) three-dimensional digital surface model (DSM) of the step-pool unit by structure from motion with multi view stereo (SfM-MVS) method as the input to the 3D computational fluid dynamics (CFD) modeling; (b) extruded bed 160 surface model connected to the extra downstream component (in purple blue) and rectangular columns to fill leaks (in green), with the boundary conditions shown on mesh planes; (c) recognized geometry with mesh grids of two mesh blocks shown where MS is short for mesh size; (d) sampling volumes to capture the flow forces acting on each step stone at X, Y, and Z directions; and (e) an example for the simulated 3D flow over the step-pool unit colored by velocity magnitude at the discharge of 49.9 L/s. The abbreviations for boundary conditions in (b) are: V for specified velocity; C for continuative; P for specific pressure; and W for wall 165 condition. The contraction section in Figure (e) refers to the edge between the jet and jump at water surface.
Figure 4: Distribution of time-averaged velocity magnitude (VM_mean) and vectors in three longitudinal sections. The section at Y = 0 cm goes across the keystone while the other two (Y = -18 and 13.5 cm) are located at the step stones beside the keystone with 265 lower top elevations. Q refers to the discharge at the inlet of the computational domain. The spacing for X, Y, and Z axes are all 10 cm in the plots.
Figure 4: Distribution of time-averaged velocity magnitude (VM_mean) and vectors in three longitudinal sections. The section at Y = 0 cm goes across the keystone while the other two (Y = -18 and 13.5 cm) are located at the step stones beside the keystone with lower top elevations. Q refers to the discharge at the inlet of the computational domain. The spacing for X, Y, and Z axes are all 10 cm in the plots.
Figure 5: Distribution of time-averaged flow velocity at five cross sections which are set according to the reference section (x0). The reference cross section x0 is located at the downstream end of the keystone (KS). The five sections are located at 18 cm and 6 cm upstream of the reference section (x0-18 and x0-6), and 2 cm, 15 cm and 40 cm downstream of the reference section (x0+2, x0+15, x0+40). The spacing for X, Y, and Z axes are all 10 cm in the plots.
Figure 5: Distribution of time-averaged flow velocity at five cross sections which are set according to the reference section (x0). The reference cross section x0 is located at the downstream end of the keystone (KS). The five sections are located at 18 cm and 6 cm upstream of the reference section (x0-18 and x0-6), and 2 cm, 15 cm and 40 cm downstream of the reference section (x0+2, x0+15, x0+40). The spacing for X, Y, and Z axes are all 10 cm in the plots.
Figure 6: Distribution of the time-averaged turbulence kinetic energy (TKE) at the five cross sections same with Figure 3.
Figure 6: Distribution of the time-averaged turbulence kinetic energy (TKE) at the five cross sections same with Figure 3.
Figure 7: Boxplots for the distributions of the mass-averaged flow kinetic energy (KE, panels a-f), turbulence kinetic energy (TKE, panels g-l), and turbulent dissipation (εT, panels m-r) in the pool for all the six tested discharges (the plots at the same discharge are in the same row). The mass-averaged values were calculated every 2 cm in the streamwise direction. The flow direction is from left to right in all the plots. The general locations of the contraction section for all the flow rates are marked by the dashed lines, except for Q = 5 L/s when the jump is located too close to the step. The longitudinal distance taken up by negative slope in the pool for the inspected range is shown by shaded area in each plot.
Figure 7: Boxplots for the distributions of the mass-averaged flow kinetic energy (KE, panels a-f), turbulence kinetic energy (TKE, panels g-l), and turbulent dissipation (εT, panels m-r) in the pool for all the six tested discharges (the plots at the same discharge are in the same row). The mass-averaged values were calculated every 2 cm in the streamwise direction. The flow direction is from left to right in all the plots. The general locations of the contraction section for all the flow rates are marked by the dashed lines, except for Q = 5 L/s when the jump is located too close to the step. The longitudinal distance taken up by negative slope in the pool for the inspected range is shown by shaded area in each plot.
Figure 8: Instantaneous flow structures extracted using the Q-criterion (Qcriterion=1200) and colored by the magnitude of flow velocity.
Figure 8: Instantaneous flow structures extracted using the Q-criterion (Qcriterion=1200) and colored by the magnitude of flow velocity.
Figure 9: Time-averaged dynamic pressure (DP_mean) on the bed surface in the step-pool model under the two highest discharges, with the step numbers marked. The negative values in the plots result from the setting of standard atmospheric pressure = 0 Pa, whose absolute value is 1.013×105 Pa.
Figure 9: Time-averaged dynamic pressure (DP_mean) on the bed surface in the step-pool model under the two highest discharges, with the step numbers marked. The negative values in the plots result from the setting of standard atmospheric pressure = 0 Pa, whose absolute value is 1.013×105 Pa.
Figure 10: Time-averaged shear stress (SS_mean) on bed surface in the step-pool model, with the step numbers marked. The standard atmospheric pressure is set as 0 Pa.
Figure 10: Time-averaged shear stress (SS_mean) on bed surface in the step-pool model, with the step numbers marked. The standard atmospheric pressure is set as 0 Pa.
Figure 11: Variation of fluid force components and magnitude of resultant flow force acting on step stones with flow rate. The stone 4 is the keystone. Stone numbers are consistent with those in Fig. 9-10. The upper limit of the sampling volumes for flow force calculation is higher than water surface while the lower limit is set at 3 cm lower than the keystone crest.
Figure 11: Variation of fluid force components and magnitude of resultant flow force acting on step stones with flow rate. The stone 4 is the keystone. Stone numbers are consistent with those in Fig. 9-10. The upper limit of the sampling volumes for flow force calculation is higher than water surface while the lower limit is set at 3 cm lower than the keystone crest.
Figure 12: Variation of drag (CD) and lift (CL) coefficient of the step stones along with flow rate. Stone numbers are consistent with those in Fig. 8-9. KS is short for keystone. The negative values of CD correspond to the drag forces towards the upstream while the negative values of CL correspond to lift forces pointing downwards.
Figure 12: Variation of drag (CD) and lift (CL) coefficient of the step stones along with flow rate. Stone numbers are consistent with those in Fig. 8-9. KS is short for keystone. The negative values of CD correspond to the drag forces towards the upstream while the negative values of CL correspond to lift forces pointing downwards.
Figure 13: Longitudinal distributions of section-averaged and -integral turbulent kinetic energy (TKE) for the jump and wake vortexes at the largest three discharges. The flow direction is from left to right in all the plots. The general locations of the contraction sections under the three flow rates are marked by dashed lines in figures (d) to (f).
Figure 13: Longitudinal distributions of section-averaged and -integral turbulent kinetic energy (TKE) for the jump and wake vortexes at the largest three discharges. The flow direction is from left to right in all the plots. The general locations of the contraction sections under the three flow rates are marked by dashed lines in figures (d) to (f).
Figure A1: Water surface profiles of the simulations with different mesh sizes at the discharge of 43.6 L/s at the longitudinal sections at: (a) Y = 24.5 cm (left boundary); (b) Y = 0.3 cm (middle section); (c) Y = -24.5 cm (right boundary). MS is short for mesh size. The flow direction is from left to right in each plot.
Figure A1: Water surface profiles of the simulations with different mesh sizes at the discharge of 43.6 L/s at the longitudinal sections at: (a) Y = 24.5 cm (left boundary); (b) Y = 0.3 cm (middle section); (c) Y = -24.5 cm (right boundary). MS is short for mesh size. The flow direction is from left to right in each plot.
Figure A2: Contours of velocity magnitude in the longitudinal section at Y = 0 cm at different mesh sizes (MSs) under the flow condition with the discharge of 43.6 L/s: (a) 0.50 cm; (b) 0.375 cm; (c) 0.30 cm; (d) 0.27 cm; (e) 0.25 cm; (f) 0.24 cm. The flow direction is from left to right.
Figure A2: Contours of velocity magnitude in the longitudinal section at Y = 0 cm at different mesh sizes (MSs) under the flow condition with the discharge of 43.6 L/s: (a) 0.50 cm; (b) 0.375 cm; (c) 0.30 cm; (d) 0.27 cm; (e) 0.25 cm; (f) 0.24 cm. The flow direction is from left to right.
Figure A3: Measurements of water surfaces (orange lines) used in model verification: (a) water surface profiles from both sides of the flume; (b) upstream edge of the jump regime from top view. KS refers to keystone in figure (b).
Figure A3: Measurements of water surfaces (orange lines) used in model verification: (a) water surface profiles from both sides of the flume; (b) upstream edge of the jump regime from top view. KS refers to keystone in figure (b).
Figure A15. Figure (a) shows the locations of the cross sections and target coarse grains at Q = 49.9 L/s. Figures (b) to (e) show the distribution of velocity magnitude (VM_mean) in the four chosen cross sections: (a) x0+8.0; (b) x0+14.0; (c) x0+21.5; (d) x0+42.5. G1 to G6 refer to 6 protruding grains in the micro-bedforms in the pool.
Figure A15. Figure (a) shows the locations of the cross sections and target coarse grains at Q = 49.9 L/s. Figures (b) to (e) show the distribution of velocity magnitude (VM_mean) in the four chosen cross sections: (a) x0+8.0; (b) x0+14.0; (c) x0+21.5; (d) x0+42.5. G1 to G6 refer to 6 protruding grains in the micro-bedforms in the pool.
Figure A16. The distribution of turbulent kinetic energy (TKE) in the same cross sections as in figure S15: (a) x0+8.0; (b) x0+14.0; (c) x0+21.5; (d) x0+42.5.
Figure A16. The distribution of turbulent kinetic energy (TKE) in the same cross sections as in figure S15: (a) x0+8.0; (b) x0+14.0; (c) x0+21.5; (d) x0+42.5.

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그림 1 하천횡단구조물 하류부 횡단구조물 파괴

유입조건에 따른압력변이로 인한하천횡단구조물 하류물받이공 및 바닥보호공설계인자 도출최종보고서

주관연구기관 / 홍익대학교 산학협력단
공동연구기관 / 한국건설기술연구원
공동연구기관 / 주식회사 지티이

연구의 목적 및 내용

하천횡단구조물이 하천설계기준(2009)대로 설계되었음에도 불구하고, 하류부에서 물받이공 및 바닥보호공의 피해가 발생하여, 구조물 본체에 대한 안전성이 현저하 게 낮아지고 있는 실정이다. 하천설계기준이 상류부의 수리특성을 반영하였다고 하나 하류부의 수리특성인 유속의 변동 성분 또는 압력의 변동성분까지 고려하고 있지는 않다. 현재 많은 선행연구에서 이러한 난류적 특성이 구조물에 미치는 영 향에 대해 제시하고 있는 실정이며, 국내 하천에서의 피해 또한 이와 관련이 있다 고 판단된다. 이에 본 연구에서는 난류성분 특히 압력의 변동성분이 물받이공과 바닥보호공에 미치는 영향을 정량적으로 분석하여, 하천 횡단구조물의 치수 안전 성 증대에 기여하고자 한다. 물받이공과 바닥보호공에 미치는 압력의 변동성분 (pressure fluctuation) 영향을 분석하기 위해 크게 3가지로 연구내용을 분류하였 다. 첫 번째는 압력의 변동으로 순간적인 음압구배(adversed pressure gradient) 가 발생할 경우 바닥보호공의 사석 및 블록이 이탈하는 것이다. 이를 확인하기 위 해 정밀한 압력 측정장치를 통해 압력변이를 측정하여, 사석의 이탈 가능성을 검 토할 것이며, 최종적으로 이탈에 대한 한계조건을 도출할 것이다. 두 번째는 압력 의 변동이 물받이공의 진동을 유발시켜 이를 지지하고 있는 지반에 다짐효과를 가 져와 물받이공과 지반사이에 공극이 발생하는 경우이다. 이러한 공극으로 물받이 공은 자중 및 물의 압력을 받게 되어, 결국 휨에 의한 파괴가 발생할 가능성이 있 게 된다. 본 연구에서는 실험을 통하여 압력의 변동과 물받이공의 진동을 동시에 측정하여, 진동이 발생하지 않을 최소 두께를 제시할 것이다. 세 번째는 압력변이 로 인한 물받이공의 진동이 피로파괴로 연결되는 경우이다. 이 현상 또한 수리실 험을 통해 압력변이-피로파괴의 관계를 정량적으로 분석하여, 한계 조건을 제시할 것이다. 본 연구는 국내 보 및 낙차공에서 발생하는 다양한 Jet의 특성을 수리실 험으로 재현해야 하며, 이를 위해 평면 Jet 분사기(plane Jet injector)를 고안/ 제작하여, 효율적인 수리실험을 수행할 것이다. 또한 3차원 수치해석을 통해 실제 스케일에 적용함으로써 연구결과의 활용도 및 적용성을 높이고자 한다.

Keywords

압력변이, 물받이공, 바닥보호공, 난류, 진동

 그림 1 하천횡단구조물 하류부 횡단구조물 파괴
그림 1 하천횡단구조물 하류부 횡단구조물 파괴
그림 2. 시간에 따른 압력의 변동 양상 및 정의
그림 2. 시간에 따른 압력의 변동 양상 및 정의
 그림 3. 하천횡단구조물 하류부 도수현상시 발생하는 압력변이 분포도, Fr=8.0 상태이며, 바닥(slab)에 양압과 음압이 지속적으로 작용한다. (Fiorotto & Rinaldo, 2010)
그림 3. 하천횡단구조물 하류부 도수현상시 발생하는 압력변이 분포도, Fr=8.0 상태이며, 바닥(slab)에 양압과 음압이 지속적으로 작용한다. (Fiorotto & Rinaldo, 2010)
 그림 4. 파괴 개념
그림 4. 파괴 개념
그림 6. PIV 측정 원리(www.photonics.com)
그림 6. PIV 측정 원리(www.photonics.com)
그림 7. LED회로판 및 BIV기법 기본개념
그림 7. LED회로판 및 BIV기법 기본개념
그림 8. BIV측정기법을 적용한 순간이미지 (Lin et al., 2012)
그림 8. BIV측정기법을 적용한 순간이미지 (Lin et al., 2012)
그림 9. 감세공의 분류
그림 9. 감세공의 분류
그림 17 수리실헐 수로시설: (a) 전체수로전경, (b) Weir 보를 포함한 측면도, (c) 도수조건 실험전경
그림 17 수리실헐 수로시설: (a) 전체수로전경, (b) Weir 보를 포함한 측면도, (c) 도수조건 실험전경
그림 18 수리실험 개요도
그림 18 수리실험 개요도
그림 127 난류모형별 압력 Data (측정위치는 그림 125 참조)
그림 127 난류모형별 압력 Data (측정위치는 그림 125 참조)
그림 128 RNG 모형을 이용한 수치모의 결과
그림 128 RNG 모형을 이용한 수치모의 결과
그림 129 LES 모형을 이용한 수치모의 결과
그림 129 LES 모형을 이용한 수치모의 결과
그림 130 압력 Data의 필터링
그림 130 압력 Data의 필터링
그림 134 Case 1의 흐름특성 분포도 및 그래프
그림 134 Case 1의 흐름특성 분포도 및 그래프

참고문헌

국토기술연구센터 (1998) 하상유지공의 구조설계 지침.

감사원 (2013) 감사원 결과보고서- 4대강살리기 사업 주요시설물 품질 밑 수질관리 실태.

국토해양부 (2009) 전국 하천횡단 구조물 설치현황 및 어도 실태조사 보고서. 국토해양부 (2010). 낙동강 살리기 사업 24공구(성주칠곡지구) 실시설계보고서.

국토해양부 (2012) 보도자료-준공대비 점검결과, 4대강 보 안전 재확인.

국토해양부 (2012) 국가 및 지방하천 종합정비 마스터플랜.

국토교통성 (2008) 하천사방기술기준.

농림부 (1996). 농업생산기반정비사업계획 설계기준. 류권규(역자) (2009). 난류의 수치모의(원저자 : 梶島岳夫, 1999).

류권규, 마리안 머스테, 로버트 에테마, 윤병만 (2006). “난류 중 부유사의 속도 지체 측정.” 한국수자원학회논문집, 제39권, 제2호, pp.99-108.

배재현, 이경훈, 신종근, 양용수, 이주희 (2011). “입자영상유속계를 이용한 은어의 유영능력 측정.” 제47권, 제4호, pp.411-418.

우효섭 (2001). 하천수리학. 청문각.

한국수자원학회 (2009). 하천설계기준해설.

한국건설기술연구원 (2014) 입자영상유속계(PIV)를 이용한 하천구조물 주변 유동해석 기법 개발

한국건설기술연구원 (2017) 보와 하상유지공의 안전성 확보를 위한 물받이와 바닥보호공의 성능평가
기법에 대한 원천기술개발

국토기술연구센터 (1998) 하상유지공의 구조설계 지침.

감사원 (2013) 감사원 결과보고서- 4대강살리기 사업 주요시설물 품질 밑 수질관리 실태. 국토해양부 (2009) 전국 하천횡단 구조물 설치현황 및 어도 실태조사 보고서.

국토해양부 (2012) 보도자료-준공대비 점검결과, 4대강 보 안전 재확인. 국토해양부 (2012) 국가 및 지방하천 종합정비 마스터플랜.

국토교통성 (2008) 하천사방기술기준.

농림부 (1996). 농업생산기반정비사업계획 설계기

류권규(역자) (2009). 난류의 수치모의(원저자 : 梶島岳夫, 1999).
류권규, 마리안 머스테, 로버트 에테마, 윤병만 (2006). “난류 중 부유사의 속도 지체 측정.” 한국수자원학회논문집, 제39권, 제2호, pp.99-108.
배재현, 이경훈, 신종근, 양용수, 이주희 (2011). “입자영상유속계를 이용한 은어의 유영능력 측정.” 제47권, 제4호, pp.411-418.
우효섭 (2001). 하천수리학. 청문각. 한국수자원학회 (2009). 하천설계기준해설. 한국건설기술연구원 (2014) 입자영상유속계(PIV)를 이용한 하천구조물 주변 유동해석 기법 개발
한국건설기술연구원 (2017) 보와 하상유지공의 안전성 확보를 위한 물받이와 바닥보호공의 성능평가
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Figure 10 | Contour lines of the static pressure (Pa) for the standard form of the stepped spillway with discharge of 60 liters/second.

스키밍 흐름 영역에서 계단형 여수로의 수리 성능에 대한 삼각형 프리즘 요소의 영향: 실험 연구 및 수치 모델링

The effect of triangular prismatic elements on the hydraulic performance of stepped spillways in the skimming flow regime: an experimental study and numerical modeling 

Kiyoumars RoushangarSamira AkhgarSaman Shahnazi

계단식 여수로는 댐의 여수로 위로 흐르는 큰 물의 에너지를 분산시키는 비용 효율적인 유압 구조입니다. 이 연구에서는 삼각주형 요소(TPE)가 계단식 배수로의 수력 성능에 미치는 영향에 초점을 맞췄습니다. 9개의 계단식 배수로 모델이 TPE의 다양한 모양과 레이아웃으로 실험 및 수치적으로 조사되었습니다. 적절한 난류 모델을 채택하려면 RNG k – ε 및 표준 k – ε모델을 활용했습니다. 계산 모델 결과는 계단 표면의 속도 분포 및 압력 프로파일을 포함하여 실험 사례의 계단 여수로에 대한 복잡한 흐름을 만족스럽게 시뮬레이션했습니다. 결과는 계단식 여수로에 TPE를 설치하는 것이 캐비테이션 효과를 줄이는 효과적인 방법이 될 수 있음을 나타냅니다. 계단식 여수로에 TPE를 설치하면 에너지 소실률이 최대 54% 증가했습니다. 계단식 배수로의 성능은 TPE가 더 가깝게 배치되었을 때 개선되었습니다. 또한, 실험 데이터를 이용하여 거칠기 계수( f )와 임계 깊이 대 단차 거칠기( yc / k )의 비율 사이의 관계를 높은 정확도로 얻었다.

Keywords

energy dissipationFlow-3Droughness coefficientstepped spillwaytriangular prismatic elements

에너지 소산 , Flow-3D , 거칠기 계수 , 계단식 배수로 , 삼각형 프리즘 요소

Figure 1 | General schematics of laboratory flume facilities.
Figure 1 | General schematics of laboratory flume facilities.
Figure 2 | Different layouts of the selected TPE in the experimental study (y1 and y2 are initial, and sequent depths of hydraulic jump).
Figure 2 | Different layouts of the selected TPE in the experimental study (y1 and y2 are initial, and sequent depths of hydraulic jump).
Figure 3 | Geometry and alignment of TPE in the numerical study.
Figure 3 | Geometry and alignment of TPE in the numerical study.
Figure 5 | Comparison of turbulence models in Flow-3D.
Figure 5 | Comparison of turbulence models in Flow-3D.
Figure 6 | Sequent water depths versus unit flow rate in standard stepped spillways and stepped spillways with triangular TPEs of types A and B.
Figure 6 | Sequent water depths versus unit flow rate in standard stepped spillways and stepped spillways with triangular TPEs of types A and B.
Figure 7 | Energy dissipation for the standard stepped spillway and the stepped spillway with TPEs.
Figure 7 | Energy dissipation for the standard stepped spillway and the stepped spillway with TPEs.
Figure 8 | Positions of measurement points to investigate the pressure and velocity distributions on the stepped spillway
Figure 8 | Positions of measurement points to investigate the pressure and velocity distributions on the stepped spillway
Figure 9 | Velocity distributions on the vertical surface of step number 4.
Figure 9 | Velocity distributions on the vertical surface of step number 4.
Figure 10 | Contour lines of the static pressure (Pa) for the standard form of the stepped spillway with discharge of 60 liters/second.
Figure 10 | Contour lines of the static pressure (Pa) for the standard form of the stepped spillway with discharge of 60 liters/second.
Figure 11 | Pressure distribution on the vertical surface of the fourth step.
Figure 11 | Pressure distribution on the vertical surface of the fourth step.
Figure 12 | Horizontal profile of the pressure distribution on the floor of step 4.
Figure 12 | Horizontal profile of the pressure distribution on the floor of step 4.
Figure 13 | Roughness coefficient changes with various unit discharges for stepped spillways.
Figure 13 | Roughness coefficient changes with various unit discharges for stepped spillways.
Figure 14 | Variations of sequent depth of downstream with various unit discharges for stepped spillways.
Figure 14 | Variations of sequent depth of downstream with various unit discharges for stepped spillways.
Figure 15 | Energy dissipation rate changes with various unit discharges for different stepped spillways.
Figure 15 | Energy dissipation rate changes with various unit discharges for different stepped spillways.
Figure 16 | Roughness coefficients (f ) versus the critical depth to the step roughness ratio (yc/K).
Figure 16 | Roughness coefficients (f ) versus the critical depth to the step roughness ratio (yc/K).

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Figure 15. Localized deformations on revetment due to run-down and sliding of armor from body laboratory model (left) and numerical modeling (right).

지속 가능한 해안 보호 구조로서 굴절식 콘크리트 블록 매트리스의 손상 메커니즘의 수치적 모델링

Numerical Modeling of Failure Mechanisms in Articulated Concrete Block Mattress as a Sustainable Coastal Protection Structure

Author

Ramin Safari Ghaleh(Department of Civil Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran)

Omid Aminoroayaie Yamini(Department of Civil Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran)

S. Hooman Mousavi(Department of Civil Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran)

Mohammad Reza Kavianpour(Department of Civil Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran)

Abstract

해안선 보호는 전 세계적인 우선 순위로 남아 있습니다. 일반적으로 해안 지역은 석회암과 같은 단단하고 비자연적이며 지속 불가능한 재료로 보호됩니다. 시공 속도와 환경 친화성을 높이고 개별 콘크리트 블록 및 보강재의 중량을 줄이기 위해 콘크리트 블록을 ACB 매트(Articulated Concrete Block Mattress)로 설계 및 구현할 수 있습니다. 이 구조물은 필수적인 부분으로 작용하며 방파제 또는 해안선 보호의 둑으로 사용할 수 있습니다. 물리적 모델은 해안 구조물의 현상을 추정하고 조사하는 핵심 도구 중 하나입니다. 그러나 한계와 장애물이 있습니다. 결과적으로, 본 연구에서는 이러한 구조물에 대한 파도의 수치 모델링을 활용하여 방파제에서의 파도 전파를 시뮬레이션하고, VOF가 있는 Flow-3D 소프트웨어를 통해 ACB Mat의 불안정성에 영향을 미치는 요인으로는 파괴파동, 옹벽의 흔들림, 파손으로 인한 인양력으로 인한 장갑의 변위 등이 있다. 본 연구의 가장 중요한 목적은 수치 Flow-3D 모델이 연안 호안의 유체역학적 매개변수를 모사하는 능력을 조사하는 것입니다. 콘크리트 블록 장갑에 대한 파동의 상승 값은 파단 매개변수( 0.5 < ξ m – 1 , 0 < 3.3 )가 증가할 때까지(R u 2 % H m 0 = 1.6) ) 최대값에 도달합니다. 따라서 차단파라미터를 증가시키고 파괴파(ξ m − 1 , 0 > 3.3 ) 유형을 붕괴파/해일파로 변경함으로써 콘크리트 블록 호안의 상대파 상승 변화 경향이 점차 증가합니다. 파동(0.5 < ξ m − 1 , 0 < 3.3 )의 경우 차단기 지수(표면 유사성 매개변수)를 높이면 상대파 런다운의 낮은 값이 크게 감소합니다. 또한, 천이영역에서는 파단파동이 쇄도파에서 붕괴/서징으로의 변화( 3.3 < ξ m – 1 , 0 < 5.0 )에서 상대적 런다운 과정이 더 적은 강도로 발생합니다.

Shoreline protection remains a global priority. Typically, coastal areas are protected by armoring them with hard, non-native, and non-sustainable materials such as limestone. To increase the execution speed and environmental friendliness and reduce the weight of individual concrete blocks and reinforcements, concrete blocks can be designed and implemented as Articulated Concrete Block Mattress (ACB Mat). These structures act as an integral part and can be used as a revetment on the breakwater body or shoreline protection. Physical models are one of the key tools for estimating and investigating the phenomena in coastal structures. However, it does have limitations and obstacles; consequently, in this study, numerical modeling of waves on these structures has been utilized to simulate wave propagation on the breakwater, via Flow-3D software with VOF. Among the factors affecting the instability of ACB Mat are breaking waves as well as the shaking of the revetment and the displacement of the armor due to the uplift force resulting from the failure. The most important purpose of the present study is to investigate the ability of numerical Flow-3D model to simulate hydrodynamic parameters in coastal revetment. The run-up values of the waves on the concrete block armoring will multiply with increasing break parameter ( 0.5 < ξ m − 1 , 0 < 3.3 ) due to the existence of plunging waves until it ( R u 2 % H m 0 = 1.6 ) reaches maximum. Hence, by increasing the breaker parameter and changing breaking waves ( ξ m − 1 , 0 > 3.3 ) type to collapsing waves/surging waves, the trend of relative wave run-up changes on concrete block revetment increases gradually. By increasing the breaker index (surf similarity parameter) in the case of plunging waves ( 0.5 < ξ m − 1 , 0 < 3.3 ), the low values on the relative wave run-down are greatly reduced. Additionally, in the transition region, the change of breaking waves from plunging waves to collapsing/surging ( 3.3 < ξ m − 1 , 0 < 5.0 ), the relative run-down process occurs with less intensity.

Figure 1.  Armor  geometric  characteristics  and  drawing  three-dimensional  geometry  of  a  breakwater section  in SolidWorks software.
Figure 1. Armor geometric characteristics and drawing three-dimensional geometry of a breakwater section in SolidWorks software.
Figure  5.  Wave  overtopping on  concrete block  mattress in (a)  laboratory  and (b)  numerical  model.
Figure 5. Wave overtopping on concrete block mattress in (a) laboratory and (b) numerical model.
Figure  7.  Mesh  block  for  calibrated  numerical  model  with  686,625  cells  and  utilization  of  FAVOR  tab to assess figure geometry.
Figure 7. Mesh block for calibrated numerical model with 686,625 cells and utilization of FAVOR tab to assess figure geometry.
Figure  10.  How to place different layers  (core, filter,  and revetment)  of the structure on slope.
Figure 10. How to place different layers (core, filter, and revetment) of the structure on slope.

Suggested Citation

Figure 11. Wave run-up on ACB Mat blocks in (a) laboratory model and (b) numerical modeling.
Figure 11. Wave run-up on ACB Mat blocks in (a) laboratory model and (b) numerical modeling.
Figure  15.  Localized  deformations  on  revetment  due  to  run-down  and  sliding  of  armor  from  body  laboratory  model  (left) and  numerical  modeling (right).
Figure 15. Localized deformations on revetment due to run-down and sliding of armor from body laboratory model (left) and numerical modeling (right).

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Flow velocity profiles for canals with a depth of 3 m and flow velocities of 5–5.3 m/s.

Optimization Algorithms and Engineering: Recent Advances and Applications

Mahdi Feizbahr,1 Navid Tonekaboni,2Guang-Jun Jiang,3,4 and Hong-Xia Chen3,4Show moreAcademic Editor: Mohammad YazdiReceived08 Apr 2021Revised18 Jun 2021Accepted17 Jul 2021Published11 Aug 2021

Abstract

Vegetation along the river increases the roughness and reduces the average flow velocity, reduces flow energy, and changes the flow velocity profile in the cross section of the river. Many canals and rivers in nature are covered with vegetation during the floods. Canal’s roughness is strongly affected by plants and therefore it has a great effect on flow resistance during flood. Roughness resistance against the flow due to the plants depends on the flow conditions and plant, so the model should simulate the current velocity by considering the effects of velocity, depth of flow, and type of vegetation along the canal. Total of 48 models have been simulated to investigate the effect of roughness in the canal. The results indicated that, by enhancing the velocity, the effect of vegetation in decreasing the bed velocity is negligible, while when the current has lower speed, the effect of vegetation on decreasing the bed velocity is obviously considerable.


강의 식생은 거칠기를 증가시키고 평균 유속을 감소시키며, 유속 에너지를 감소시키고 강의 단면에서 유속 프로파일을 변경합니다. 자연의 많은 운하와 강은 홍수 동안 초목으로 덮여 있습니다. 운하의 조도는 식물의 영향을 많이 받으므로 홍수시 유동저항에 큰 영향을 미칩니다. 식물로 인한 흐름에 대한 거칠기 저항은 흐름 조건 및 식물에 따라 다르므로 모델은 유속, 흐름 깊이 및 운하를 따라 식생 유형의 영향을 고려하여 현재 속도를 시뮬레이션해야 합니다. 근관의 거칠기의 영향을 조사하기 위해 총 48개의 모델이 시뮬레이션되었습니다. 결과는 유속을 높임으로써 유속을 감소시키는 식생의 영향은 무시할 수 있는 반면, 해류가 더 낮은 유속일 때 유속을 감소시키는 식생의 영향은 분명히 상당함을 나타냈다.

1. Introduction

Considering the impact of each variable is a very popular field within the analytical and statistical methods and intelligent systems [114]. This can help research for better modeling considering the relation of variables or interaction of them toward reaching a better condition for the objective function in control and engineering [1527]. Consequently, it is necessary to study the effects of the passive factors on the active domain [2836]. Because of the effect of vegetation on reducing the discharge capacity of rivers [37], pruning plants was necessary to improve the condition of rivers. One of the important effects of vegetation in river protection is the action of roots, which cause soil consolidation and soil structure improvement and, by enhancing the shear strength of soil, increase the resistance of canal walls against the erosive force of water. The outer limbs of the plant increase the roughness of the canal walls and reduce the flow velocity and deplete the flow energy in vicinity of the walls. Vegetation by reducing the shear stress of the canal bed reduces flood discharge and sedimentation in the intervals between vegetation and increases the stability of the walls [3841].

One of the main factors influencing the speed, depth, and extent of flood in this method is Manning’s roughness coefficient. On the other hand, soil cover [42], especially vegetation, is one of the most determining factors in Manning’s roughness coefficient. Therefore, it is expected that those seasonal changes in the vegetation of the region will play an important role in the calculated value of Manning’s roughness coefficient and ultimately in predicting the flood wave behavior [4345]. The roughness caused by plants’ resistance to flood current depends on the flow and plant conditions. Flow conditions include depth and velocity of the plant, and plant conditions include plant type, hardness or flexibility, dimensions, density, and shape of the plant [46]. In general, the issue discussed in this research is the optimization of flood-induced flow in canals by considering the effect of vegetation-induced roughness. Therefore, the effect of plants on the roughness coefficient and canal transmission coefficient and in consequence the flow depth should be evaluated [4748].

Current resistance is generally known by its roughness coefficient. The equation that is mainly used in this field is Manning equation. The ratio of shear velocity to average current velocity  is another form of current resistance. The reason for using the  ratio is that it is dimensionless and has a strong theoretical basis. The reason for using Manning roughness coefficient is its pervasiveness. According to Freeman et al. [49], the Manning roughness coefficient for plants was calculated according to the Kouwen and Unny [50] method for incremental resistance. This method involves increasing the roughness for various surface and plant irregularities. Manning’s roughness coefficient has all the factors affecting the resistance of the canal. Therefore, the appropriate way to more accurately estimate this coefficient is to know the factors affecting this coefficient [51].

To calculate the flow rate, velocity, and depth of flow in canals as well as flood and sediment estimation, it is important to evaluate the flow resistance. To determine the flow resistance in open ducts, Manning, Chézy, and Darcy–Weisbach relations are used [52]. In these relations, there are parameters such as Manning’s roughness coefficient (n), Chézy roughness coefficient (C), and Darcy–Weisbach coefficient (f). All three of these coefficients are a kind of flow resistance coefficient that is widely used in the equations governing flow in rivers [53].

The three relations that express the relationship between the average flow velocity (V) and the resistance and geometric and hydraulic coefficients of the canal are as follows:where nf, and c are Manning, Darcy–Weisbach, and Chézy coefficients, respectively. V = average flow velocity, R = hydraulic radius, Sf = slope of energy line, which in uniform flow is equal to the slope of the canal bed,  = gravitational acceleration, and Kn is a coefficient whose value is equal to 1 in the SI system and 1.486 in the English system. The coefficients of resistance in equations (1) to (3) are related as follows:

Based on the boundary layer theory, the flow resistance for rough substrates is determined from the following general relation:where f = Darcy–Weisbach coefficient of friction, y = flow depth, Ks = bed roughness size, and A = constant coefficient.

On the other hand, the relationship between the Darcy–Weisbach coefficient of friction and the shear velocity of the flow is as follows:

By using equation (6), equation (5) is converted as follows:

Investigation on the effect of vegetation arrangement on shear velocity of flow in laboratory conditions showed that, with increasing the shear Reynolds number (), the numerical value of the  ratio also increases; in other words the amount of roughness coefficient increases with a slight difference in the cases without vegetation, checkered arrangement, and cross arrangement, respectively [54].

Roughness in river vegetation is simulated in mathematical models with a variable floor slope flume by different densities and discharges. The vegetation considered submerged in the bed of the flume. Results showed that, with increasing vegetation density, canal roughness and flow shear speed increase and with increasing flow rate and depth, Manning’s roughness coefficient decreases. Factors affecting the roughness caused by vegetation include the effect of plant density and arrangement on flow resistance, the effect of flow velocity on flow resistance, and the effect of depth [4555].

One of the works that has been done on the effect of vegetation on the roughness coefficient is Darby [56] study, which investigates a flood wave model that considers all the effects of vegetation on the roughness coefficient. There are currently two methods for estimating vegetation roughness. One method is to add the thrust force effect to Manning’s equation [475758] and the other method is to increase the canal bed roughness (Manning-Strickler coefficient) [455961]. These two methods provide acceptable results in models designed to simulate floodplain flow. Wang et al. [62] simulate the floodplain with submerged vegetation using these two methods and to increase the accuracy of the results, they suggested using the effective height of the plant under running water instead of using the actual height of the plant. Freeman et al. [49] provided equations for determining the coefficient of vegetation roughness under different conditions. Lee et al. [63] proposed a method for calculating the Manning coefficient using the flow velocity ratio at different depths. Much research has been done on the Manning roughness coefficient in rivers, and researchers [496366] sought to obtain a specific number for n to use in river engineering. However, since the depth and geometric conditions of rivers are completely variable in different places, the values of Manning roughness coefficient have changed subsequently, and it has not been possible to choose a fixed number. In river engineering software, the Manning roughness coefficient is determined only for specific and constant conditions or normal flow. Lee et al. [63] stated that seasonal conditions, density, and type of vegetation should also be considered. Hydraulic roughness and Manning roughness coefficient n of the plant were obtained by estimating the total Manning roughness coefficient from the matching of the measured water surface curve and water surface height. The following equation is used for the flow surface curve:where  is the depth of water change, S0 is the slope of the canal floor, Sf is the slope of the energy line, and Fr is the Froude number which is obtained from the following equation:where D is the characteristic length of the canal. Flood flow velocity is one of the important parameters of flood waves, which is very important in calculating the water level profile and energy consumption. In the cases where there are many limitations for researchers due to the wide range of experimental dimensions and the variety of design parameters, the use of numerical methods that are able to estimate the rest of the unknown results with acceptable accuracy is economically justified.

FLOW-3D software uses Finite Difference Method (FDM) for numerical solution of two-dimensional and three-dimensional flow. This software is dedicated to computational fluid dynamics (CFD) and is provided by Flow Science [67]. The flow is divided into networks with tubular cells. For each cell there are values of dependent variables and all variables are calculated in the center of the cell, except for the velocity, which is calculated at the center of the cell. In this software, two numerical techniques have been used for geometric simulation, FAVOR™ (Fractional-Area-Volume-Obstacle-Representation) and the VOF (Volume-of-Fluid) method. The equations used at this model for this research include the principle of mass survival and the magnitude of motion as follows. The fluid motion equations in three dimensions, including the Navier–Stokes equations with some additional terms, are as follows:where  are mass accelerations in the directions xyz and  are viscosity accelerations in the directions xyz and are obtained from the following equations:

Shear stresses  in equation (11) are obtained from the following equations:

The standard model is used for high Reynolds currents, but in this model, RNG theory allows the analytical differential formula to be used for the effective viscosity that occurs at low Reynolds numbers. Therefore, the RNG model can be used for low and high Reynolds currents.

Weather changes are high and this affects many factors continuously. The presence of vegetation in any area reduces the velocity of surface flows and prevents soil erosion, so vegetation will have a significant impact on reducing destructive floods. One of the methods of erosion protection in floodplain watersheds is the use of biological methods. The presence of vegetation in watersheds reduces the flow rate during floods and prevents soil erosion. The external organs of plants increase the roughness and decrease the velocity of water flow and thus reduce its shear stress energy. One of the important factors with which the hydraulic resistance of plants is expressed is the roughness coefficient. Measuring the roughness coefficient of plants and investigating their effect on reducing velocity and shear stress of flow is of special importance.

Roughness coefficients in canals are affected by two main factors, namely, flow conditions and vegetation characteristics [68]. So far, much research has been done on the effect of the roughness factor created by vegetation, but the issue of plant density has received less attention. For this purpose, this study was conducted to investigate the effect of vegetation density on flow velocity changes.

In a study conducted using a software model on three density modes in the submerged state effect on flow velocity changes in 48 different modes was investigated (Table 1).Table 1 The studied models.

The number of cells used in this simulation is equal to 1955888 cells. The boundary conditions were introduced to the model as a constant speed and depth (Figure 1). At the output boundary, due to the presence of supercritical current, no parameter for the current is considered. Absolute roughness for floors and walls was introduced to the model (Figure 1). In this case, the flow was assumed to be nonviscous and air entry into the flow was not considered. After  seconds, this model reached a convergence accuracy of .

Figure 1 The simulated model and its boundary conditions.

Due to the fact that it is not possible to model the vegetation in FLOW-3D software, in this research, the vegetation of small soft plants was studied so that Manning’s coefficients can be entered into the canal bed in the form of roughness coefficients obtained from the studies of Chow [69] in similar conditions. In practice, in such modeling, the effect of plant height is eliminated due to the small height of herbaceous plants, and modeling can provide relatively acceptable results in these conditions.

48 models with input velocities proportional to the height of the regular semihexagonal canal were considered to create supercritical conditions. Manning coefficients were applied based on Chow [69] studies in order to control the canal bed. Speed profiles were drawn and discussed.

Any control and simulation system has some inputs that we should determine to test any technology [7077]. Determination and true implementation of such parameters is one of the key steps of any simulation [237881] and computing procedure [8286]. The input current is created by applying the flow rate through the VFR (Volume Flow Rate) option and the output flow is considered Output and for other borders the Symmetry option is considered.

Simulation of the models and checking their action and responses and observing how a process behaves is one of the accepted methods in engineering and science [8788]. For verification of FLOW-3D software, the results of computer simulations are compared with laboratory measurements and according to the values of computational error, convergence error, and the time required for convergence, the most appropriate option for real-time simulation is selected (Figures 2 and 3 ).

Figure 2 Modeling the plant with cylindrical tubes at the bottom of the canal.

Figure 3 Velocity profiles in positions 2 and 5.

The canal is 7 meters long, 0.5 meters wide, and 0.8 meters deep. This test was used to validate the application of the software to predict the flow rate parameters. In this experiment, instead of using the plant, cylindrical pipes were used in the bottom of the canal.

The conditions of this modeling are similar to the laboratory conditions and the boundary conditions used in the laboratory were used for numerical modeling. The critical flow enters the simulation model from the upstream boundary, so in the upstream boundary conditions, critical velocity and depth are considered. The flow at the downstream boundary is supercritical, so no parameters are applied to the downstream boundary.

The software well predicts the process of changing the speed profile in the open canal along with the considered obstacles. The error in the calculated speed values can be due to the complexity of the flow and the interaction of the turbulence caused by the roughness of the floor with the turbulence caused by the three-dimensional cycles in the hydraulic jump. As a result, the software is able to predict the speed distribution in open canals.

2. Modeling Results

After analyzing the models, the results were shown in graphs (Figures 414 ). The total number of experiments in this study was 48 due to the limitations of modeling.(a)
(a)(b)
(b)(c)
(c)(d)
(d)(a)
(a)(b)
(b)(c)
(c)(d)
(d)Figure 4 Flow velocity profiles for canals with a depth of 1 m and flow velocities of 3–3.3 m/s. Canal with a depth of 1 meter and a flow velocity of (a) 3 meters per second, (b) 3.1 meters per second, (c) 3.2 meters per second, and (d) 3.3 meters per second.

Figure 5 Canal diagram with a depth of 1 meter and a flow rate of 3 meters per second.

Figure 6 Canal diagram with a depth of 1 meter and a flow rate of 3.1 meters per second.

Figure 7 Canal diagram with a depth of 1 meter and a flow rate of 3.2 meters per second.

Figure 8 Canal diagram with a depth of 1 meter and a flow rate of 3.3 meters per second.(a)
(a)(b)
(b)(c)
(c)(d)
(d)(a)
(a)(b)
(b)(c)
(c)(d)
(d)Figure 9 Flow velocity profiles for canals with a depth of 2 m and flow velocities of 4–4.3 m/s. Canal with a depth of 2 meters and a flow rate of (a) 4 meters per second, (b) 4.1 meters per second, (c) 4.2 meters per second, and (d) 4.3 meters per second.

Figure 10 Canal diagram with a depth of 2 meters and a flow rate of 4 meters per second.

Figure 11 Canal diagram with a depth of 2 meters and a flow rate of 4.1 meters per second.

Figure 12 Canal diagram with a depth of 2 meters and a flow rate of 4.2 meters per second.

Figure 13 Canal diagram with a depth of 2 meters and a flow rate of 4.3 meters per second.(a)
(a)(b)
(b)(c)
(c)(d)
(d)(a)
(a)(b)
(b)(c)
(c)(d)
(d)Figure 14 Flow velocity profiles for canals with a depth of 3 m and flow velocities of 5–5.3 m/s. Canal with a depth of 2 meters and a flow rate of (a) 4 meters per second, (b) 4.1 meters per second, (c) 4.2 meters per second, and (d) 4.3 meters per second.

To investigate the effects of roughness with flow velocity, the trend of flow velocity changes at different depths and with supercritical flow to a Froude number proportional to the depth of the section has been obtained.

According to the velocity profiles of Figure 5, it can be seen that, with the increasing of Manning’s coefficient, the canal bed speed decreases.

According to Figures 5 to 8, it can be found that, with increasing the Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of the models 1 to 12, which can be justified by increasing the speed and of course increasing the Froude number.

According to Figure 10, we see that, with increasing Manning’s coefficient, the canal bed speed decreases.

According to Figure 11, we see that, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of Figures 510, which can be justified by increasing the speed and, of course, increasing the Froude number.

With increasing Manning’s coefficient, the canal bed speed decreases (Figure 12). But this deceleration is more noticeable than the deceleration of the higher models (Figures 58 and 1011), which can be justified by increasing the speed and, of course, increasing the Froude number.

According to Figure 13, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of Figures 5 to 12, which can be justified by increasing the speed and, of course, increasing the Froude number.

According to Figure 15, with increasing Manning’s coefficient, the canal bed speed decreases.

Figure 15 Canal diagram with a depth of 3 meters and a flow rate of 5 meters per second.

According to Figure 16, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of the higher model, which can be justified by increasing the speed and, of course, increasing the Froude number.

Figure 16 Canal diagram with a depth of 3 meters and a flow rate of 5.1 meters per second.

According to Figure 17, it is clear that, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of the higher models, which can be justified by increasing the speed and, of course, increasing the Froude number.

Figure 17 Canal diagram with a depth of 3 meters and a flow rate of 5.2 meters per second.

According to Figure 18, with increasing Manning’s coefficient, the canal bed speed decreases. But this deceleration is more noticeable than the deceleration of the higher models, which can be justified by increasing the speed and, of course, increasing the Froude number.

Figure 18 Canal diagram with a depth of 3 meters and a flow rate of 5.3 meters per second.

According to Figure 19, it can be seen that the vegetation placed in front of the flow input velocity has negligible effect on the reduction of velocity, which of course can be justified due to the flexibility of the vegetation. The only unusual thing is the unexpected decrease in floor speed of 3 m/s compared to higher speeds.(a)
(a)(b)
(b)(c)
(c)(a)
(a)(b)
(b)(c)
(c)Figure 19 Comparison of velocity profiles with the same plant densities (depth 1 m). Comparison of velocity profiles with (a) plant densities of 25%, depth 1 m; (b) plant densities of 50%, depth 1 m; and (c) plant densities of 75%, depth 1 m.

According to Figure 20, by increasing the speed of vegetation, the effect of vegetation on reducing the flow rate becomes more noticeable. And the role of input current does not have much effect in reducing speed.(a)
(a)(b)
(b)(c)
(c)(a)
(a)(b)
(b)(c)
(c)Figure 20 Comparison of velocity profiles with the same plant densities (depth 2 m). Comparison of velocity profiles with (a) plant densities of 25%, depth 2 m; (b) plant densities of 50%, depth 2 m; and (c) plant densities of 75%, depth 2 m.

According to Figure 21, it can be seen that, with increasing speed, the effect of vegetation on reducing the bed flow rate becomes more noticeable and the role of the input current does not have much effect. In general, it can be seen that, by increasing the speed of the input current, the slope of the profiles increases from the bed to the water surface and due to the fact that, in software, the roughness coefficient applies to the channel floor only in the boundary conditions, this can be perfectly justified. Of course, it can be noted that, due to the flexible conditions of the vegetation of the bed, this modeling can show acceptable results for such grasses in the canal floor. In the next directions, we may try application of swarm-based optimization methods for modeling and finding the most effective factors in this research [27815188994]. In future, we can also apply the simulation logic and software of this research for other domains such as power engineering [9599].(a)
(a)(b)
(b)(c)
(c)(a)
(a)(b)
(b)(c)
(c)Figure 21 Comparison of velocity profiles with the same plant densities (depth 3 m). Comparison of velocity profiles with (a) plant densities of 25%, depth 3 m; (b) plant densities of 50%, depth 3 m; and (c) plant densities of 75%, depth 3 m.

3. Conclusion

The effects of vegetation on the flood canal were investigated by numerical modeling with FLOW-3D software. After analyzing the results, the following conclusions were reached:(i)Increasing the density of vegetation reduces the velocity of the canal floor but has no effect on the velocity of the canal surface.(ii)Increasing the Froude number is directly related to increasing the speed of the canal floor.(iii)In the canal with a depth of one meter, a sudden increase in speed can be observed from the lowest speed and higher speed, which is justified by the sudden increase in Froude number.(iv)As the inlet flow rate increases, the slope of the profiles from the bed to the water surface increases.(v)By reducing the Froude number, the effect of vegetation on reducing the flow bed rate becomes more noticeable. And the input velocity in reducing the velocity of the canal floor does not have much effect.(vi)At a flow rate between 3 and 3.3 meters per second due to the shallow depth of the canal and the higher landing number a more critical area is observed in which the flow bed velocity in this area is between 2.86 and 3.1 m/s.(vii)Due to the critical flow velocity and the slight effect of the roughness of the horseshoe vortex floor, it is not visible and is only partially observed in models 1-2-3 and 21.(viii)As the flow rate increases, the effect of vegetation on the rate of bed reduction decreases.(ix)In conditions where less current intensity is passing, vegetation has a greater effect on reducing current intensity and energy consumption increases.(x)In the case of using the flow rate of 0.8 cubic meters per second, the velocity distribution and flow regime show about 20% more energy consumption than in the case of using the flow rate of 1.3 cubic meters per second.

Nomenclature

n:Manning’s roughness coefficient
C:Chézy roughness coefficient
f:Darcy–Weisbach coefficient
V:Flow velocity
R:Hydraulic radius
g:Gravitational acceleration
y:Flow depth
Ks:Bed roughness
A:Constant coefficient
:Reynolds number
y/∂x:Depth of water change
S0:Slope of the canal floor
Sf:Slope of energy line
Fr:Froude number
D:Characteristic length of the canal
G:Mass acceleration
:Shear stresses.

Data Availability

All data are included within the paper.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This work was partially supported by the National Natural Science Foundation of China under Contract no. 71761030 and Natural Science Foundation of Inner Mongolia under Contract no. 2019LH07003.

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Fig. 1. Hydraulic jump flow structure.

Performance assessment of OpenFOAM and FLOW-3D in the numerical modeling of a low Reynolds number hydraulic jump

낮은 레이놀즈 수 유압 점프의 수치 모델링에서 OpenFOAM 및 FLOW-3D의 성능 평가

ArnauBayona DanielValerob RafaelGarcía-Bartuala Francisco ​JoséVallés-Morána P. AmparoLópez-Jiméneza

Abstract

A comparative performance analysis of the CFD platforms OpenFOAM and FLOW-3D is presented, focusing on a 3D swirling turbulent flow: a steady hydraulic jump at low Reynolds number. Turbulence is treated using RANS approach RNG k-ε. A Volume Of Fluid (VOF) method is used to track the air–water interface, consequently aeration is modeled using an Eulerian–Eulerian approach. Structured meshes of cubic elements are used to discretize the channel geometry. The numerical model accuracy is assessed comparing representative hydraulic jump variables (sequent depth ratio, roller length, mean velocity profiles, velocity decay or free surface profile) to experimental data. The model results are also compared to previous studies to broaden the result validation. Both codes reproduced the phenomenon under study concurring with experimental data, although special care must be taken when swirling flows occur. Both models can be used to reproduce the hydraulic performance of energy dissipation structures at low Reynolds numbers.

CFD 플랫폼 OpenFOAM 및 FLOW-3D의 비교 성능 분석이 3D 소용돌이치는 난류인 낮은 레이놀즈 수에서 안정적인 유압 점프에 초점을 맞춰 제시됩니다. 난류는 RANS 접근법 RNG k-ε을 사용하여 처리됩니다.

VOF(Volume Of Fluid) 방법은 공기-물 계면을 추적하는 데 사용되며 결과적으로 Eulerian-Eulerian 접근 방식을 사용하여 폭기가 모델링됩니다. 입방체 요소의 구조화된 메쉬는 채널 형상을 이산화하는 데 사용됩니다. 수치 모델 정확도는 대표적인 유압 점프 변수(연속 깊이 비율, 롤러 길이, 평균 속도 프로파일, 속도 감쇠 또는 자유 표면 프로파일)를 실험 데이터와 비교하여 평가됩니다.

모델 결과는 또한 결과 검증을 확장하기 위해 이전 연구와 비교됩니다. 소용돌이 흐름이 발생할 때 특별한 주의가 필요하지만 두 코드 모두 실험 데이터와 일치하는 연구 중인 현상을 재현했습니다. 두 모델 모두 낮은 레이놀즈 수에서 에너지 소산 구조의 수리 성능을 재현하는 데 사용할 수 있습니다.

Keywords

CFDRANS, OpenFOAM, FLOW-3D ,Hydraulic jump, Air–water flow, Low Reynolds number

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Figure 17. Longitudinal turbulent kinetic energy distribution on the smooth and triangular macroroughnesses: (A) Y/2; (B) Y/6.

Numerical Simulations of the Flow Field of a Submerged Hydraulic Jump over Triangular Macroroughnesses

Triangular Macroroughnesses 대한 잠긴 수압 점프의 유동장 수치 시뮬레이션

by Amir Ghaderi 1,2,Mehdi Dasineh 3,Francesco Aristodemo 2 andCostanza Aricò 4,*1Department of Civil Engineering, Faculty of Engineering, University of Zanjan, Zanjan 537138791, Iran2Department of Civil Engineering, University of Calabria, Arcavacata, 87036 Rende, Italy3Department of Civil Engineering, Faculty of Engineering, University of Maragheh, Maragheh 8311155181, Iran4Department of Engineering, University of Palermo, Viale delle Scienze, 90128 Palermo, Italy*Author to whom correspondence should be addressed.Academic Editor: Anis YounesWater202113(5), 674; https://doi.org/10.3390/w13050674

Abstract

The submerged hydraulic jump is a sudden change from the supercritical to subcritical flow, specified by strong turbulence, air entrainment and energy loss. Despite recent studies, hydraulic jump characteristics in smooth and rough beds, the turbulence, the mean velocity and the flow patterns in the cavity region of a submerged hydraulic jump in the rough beds, especially in the case of triangular macroroughnesses, are not completely understood. The objective of this paper was to numerically investigate via the FLOW-3D model the effects of triangular macroroughnesses on the characteristics of submerged jump, including the longitudinal profile of streamlines, flow patterns in the cavity region, horizontal velocity profiles, streamwise velocity distribution, thickness of the inner layer, bed shear stress coefficient, Turbulent Kinetic Energy (TKE) and energy loss, in different macroroughness arrangements and various inlet Froude numbers (1.7 < Fr1 < 9.3). To verify the accuracy and reliability of the present numerical simulations, literature experimental data were considered.

Keywords: submerged hydraulic jumptriangular macroroughnessesTKEbed shear stress coefficientvelocityFLOW-3D model

수중 유압 점프는 강한 난류, 공기 동반 및 에너지 손실로 지정된 초임계에서 아임계 흐름으로의 급격한 변화입니다. 최근 연구에도 불구하고, 특히 삼각형 거시적 거칠기의 경우, 평활 및 거친 베드에서의 수압 점프 특성, 거친 베드에서 잠긴 수압 점프의 공동 영역에서 난류, 평균 속도 및 유동 패턴이 완전히 이해되지 않았습니다.

이 논문의 목적은 유선의 종방향 프로파일, 캐비티 영역의 유동 패턴, 수평 속도 프로파일, 스트림 방향 속도 분포, 두께를 포함하여 서브머지드 점프의 특성에 대한 삼각형 거시 거칠기의 영향을 FLOW-3D 모델을 통해 수치적으로 조사하는 것이었습니다.

내부 층의 층 전단 응력 계수, 난류 운동 에너지(TKE) 및 에너지 손실, 다양한 거시 거칠기 배열 및 다양한 입구 Froude 수(1.7 < Fr1 < 9.3). 현재 수치 시뮬레이션의 정확성과 신뢰성을 검증하기 위해 문헌 실험 데이터를 고려했습니다.

 Introduction

격렬한 난류 혼합과 기포 동반이 있는 수압 점프는 초임계에서 아임계 흐름으로의 변화 과정으로 간주됩니다[1]. 자유 및 수중 유압 점프는 일반적으로 게이트, 배수로 및 둑과 같은 수력 구조 아래의 에너지 손실에 적합합니다. 매끄러운 베드에서 유압 점프의 특성은 널리 연구되었습니다[2,3,4,5,6,7,8,9].

베드의 거칠기 요소가 매끄러운 베드와 비교하여 수압 점프의 특성에 어떻게 영향을 미치는지 예측하기 위해 거시적 거칠기에 대한 자유 및 수중 수력 점프에 대해 여러 실험 및 수치 연구가 수행되었습니다. Ead와 Rajaratnam[10]은 사인파 거대 거칠기에 대한 수리학적 점프의 특성을 조사하고 무차원 분석을 통해 수면 프로파일과 배출을 정규화했습니다.

Tokyayet al. [11]은 두 사인 곡선 거대 거칠기에 대한 점프 길이 비율과 에너지 손실이 매끄러운 베드보다 각각 35% 더 작고 6% 더 높다는 것을 관찰했습니다. Abbaspur et al. [12]는 6개의 사인파형 거대 거칠기에 대한 수력학적 점프의 특성을 연구했습니다. 그 결과, 꼬리수심과 점프길이는 평상보다 낮았고 Froude 수는 점프길이에 큰 영향을 미쳤습니다.

Shafai-Bejestan과 Neisi[13]는 수압 점프에 대한 마름모꼴 거대 거칠기의 영향을 조사했습니다. 결과는 마름모꼴 거시 거칠기를 사용하면 매끄러운 침대와 비교하여 꼬리 수심과 점프 길이를 감소시키는 것으로 나타났습니다. Izadjoo와 Shafai-Bejestan[14]은 다양한 사다리꼴 거시 거칠기에 대한 수압 점프를 연구했습니다.

그들은 전단응력계수가 평활층보다 10배 이상 크고 점프길이가 50% 감소하는 것을 관찰하였습니다. Nikmehr과 Aminpour[15]는 Flow-3D 모델 버전 11.2[16]를 사용하여 사다리꼴 블록이 있는 거시적 거칠기에 대한 수력학적 점프의 특성을 조사했습니다. 결과는 거시 거칠기의 높이와 거리가 증가할수록 전단 응력 계수뿐만 아니라 베드 근처에서 속도가 감소하는 것으로 나타났습니다.

Ghaderi et al. [17]은 다양한 형태의 거시 거칠기(삼각형, 정사각형 및 반 타원형)에 대한 자유 및 수중 수력 점프 특성을 연구했습니다. 결과는 Froude 수의 증가에 따라 자유 및 수중 점프에서 전단 응력 계수, 에너지 손실, 수중 깊이, 미수 깊이 및 상대 점프 길이가 증가함을 나타냅니다.

자유 및 수중 점프에서 가장 높은 전단 응력과 에너지 손실은 삼각형의 거시 거칠기가 존재할 때 발생했습니다. Elsebaie와 Shabayek[18]은 5가지 형태의 거시적 거칠기(삼각형, 사다리꼴, 2개의 측면 경사 및 직사각형이 있는 정현파)에 대한 수력학적 점프의 특성을 연구했습니다. 결과는 모든 거시적 거칠기에 대한 에너지 손실이 매끄러운 베드에서보다 15배 이상이라는 것을 보여주었습니다.

Samadi-Boroujeni et al. [19]는 다양한 각도의 6개의 삼각형 거시 거칠기에 대한 수력 점프를 조사한 결과 삼각형 거시 거칠기가 평활 베드에 비해 점프 길이를 줄이고 에너지 손실과 베드 전단 응력 계수를 증가시키는 것으로 나타났습니다.

Ahmed et al. [20]은 매끄러운 베드와 삼각형 거시 거칠기에서 수중 수력 점프 특성을 조사했습니다. 결과는 부드러운 침대와 비교할 때 잠긴 깊이와 점프 길이가 감소했다고 밝혔습니다. 표 1은 다른 연구자들이 제시한 과거의 유압 점프에 대한 실험 및 수치 연구의 세부 사항을 나열합니다.

Table 1. Main characteristics of some past experimental and numerical studies on hydraulic jumps.

ReferenceShape Bed-Channel Type-
Jump Type
Channel Dimension (m)Roughness (mm)Fr1Investigated Flow
Properties
Ead and Rajaratnam [10]-Smooth and rough beds-Rectangular channel-Free jumpCL1 = 7.60
CW2 = 0.44
CH3 = 0.60
-Corrugated sheets (RH4 = 13 and 22)4–10-Upstream and tailwater depths-Jump length-Roller length-Velocity-Water surface profile
Tokyay et al. [11]-Smooth and rough beds-Rectangular channel-Free jumpCL = 10.50
CW = 0.253
CH = 0.432
-Two sinusoidal corrugated (RH = 10 and 13)5–12-Depth ratio-Jump length-Energy loss
Izadjoo and Shafai-Bejestan [14]-Smooth and rough beds-Two rectangular-channel-Free jumpCL = 1.2, 9
CW = 0.25, 0.50
CH = 0.40
Baffle with trapezoidal cross section
(RH: 13 and 26)
6–12-Upstream and tailwater depths-Jump length-Velocity-Bed shear stress coefficient
Abbaspour et al. [12]-Horizontal bed with slope 0.002-Rectangular channel—smooth and rough beds-Free jumpCL = 10
CW = 0.25
CH = 0.50
-Sinusoidal bed (RH = 15,20, 25 and 35)3.80–8.60-Water surface profile-Depth ratio-Jump length-Energy loss-Velocity profiles-Bed shear stress coefficient
Shafai-Bejestan and Neisi [13]-Smooth and rough beds-Rectangular channel-Free jumpCL = 7.50
CW = 0.35
CH = 0.50
Lozenge bed4.50–12-Sequent depth-Jump length
Elsebaie and Shabayek [18]-Smooth and rough beds-Rectangular channel-With side slopes of 45 degrees for two trapezoidal and triangular macroroughnesses and of 60 degrees for other trapezoidal macroroughnesses-Free jumpCL = 9
CW = 0.295
CH = 0.32
-Sinusoidal-Triangular-Trapezoidal with two side-Rectangular-(RH = 18 and corrugation wavelength = 65)50-Water surface profile-Sequent depth-Jump length-Bed shear stress coefficient
Samadi-Boroujeni et al. [19]-Rectangular channel-Smooth and rough beds-Free jumpCL = 12
CW = 0.40
CH = 0.40
-Six triangular corrugated (RH = 2.5)6.10–13.10-Water surface profile-Sequent depth-Jump length-Energy loss-Velocity profiles-Bed shear stress coefficient
Ahmed et al. [20]-Smooth and rough beds-Rectangular channel-Submerged jumpCL = 24.50
CW = 0.75
CH = 0.70
-Triangular corrugated sheet (RH = 40)1.68–9.29-Conjugated and tailwater depths-Submerged ratio-Deficit depth-Relative jump length-Jump length-Relative roller jump length-Jump efficiency-Bed shear stress coefficient
Nikmehr and Aminpour [15]-Horizontal bed with slope 0.002-Rectangular channel-Rough bed-Free jumpCL = 12
CW = 0.25
CH = 0.50
-Trapezoidal blocks (RH = 2, 3 and 4)5.01–13.70-Water surface profile-Sequent depth-Jump length-Roller length-Velocity
Ghaderi et al. [17]-Smooth and rough beds-Rectangular channel-Free and submerged jumpCL = 4.50
CW = 0.75
CH = 0.70
-Triangular, square and semi-oval macroroughnesses (RH = 40 and distance of roughness of I = 40, 80, 120, 160 and 200)1.70–9.30-Horizontal velocity distributions-Bed shear stress coefficient-Sequent depth ratio and submerged depth ratio-Jump length-Energy loss
Present studyRectangular channel
Smooth and rough beds
Submerged jump
CL = 4.50
CW = 0.75
CH = 0.70
-Triangular macroroughnesses (RH = 40 and distance of roughness of I = 40, 80, 120, 160 and 200)1.70–9.30-Longitudinal profile of streamlines-Flow patterns in the cavity region-Horizontal velocity profiles-Streamwise velocity distribution-Bed shear stress coefficient-TKE-Thickness of the inner layer-Energy loss

CL1: channel length, CW2: channel width, CH3: channel height, RH4: roughness height.

이전에 논의된 조사의 주요 부분은 실험실 접근 방식을 기반으로 하며 사인파, 마름모꼴, 사다리꼴, 정사각형, 직사각형 및 삼각형 매크로 거칠기가 공액 깊이, 잠긴 깊이, 점프 길이, 에너지 손실과 같은 일부 자유 및 수중 유압 점프 특성에 어떻게 영향을 미치는지 조사합니다.

베드 및 전단 응력 계수. 더욱이, 저자[17]에 의해 다양한 형태의 거시적 거칠기에 대한 수력학적 점프에 대한 이전 발표된 논문을 참조하면, 삼각형의 거대조도는 가장 높은 층 전단 응력 계수 및 에너지 손실을 가지며 또한 가장 낮은 잠긴 깊이, tailwater를 갖는 것으로 관찰되었습니다.

다른 거친 모양, 즉 정사각형 및 반 타원형과 부드러운 침대에 비해 깊이와 점프 길이. 따라서 본 논문에서는 삼각형 매크로 거칠기를 사용하여(일정한 거칠기 높이가 T = 4cm이고 삼각형 거칠기의 거리가 I = 4, 8, 12, 16 및 20cm인 다른 T/I 비율에 대해), 특정 캐비티 영역의 유동 패턴, 난류 운동 에너지(TKE) 및 흐름 방향 속도 분포와 같은 연구가 필요합니다.

CFD(Computational Fluid Dynamics) 방법은 자유 및 수중 유압 점프[21]와 같은 복잡한 흐름의 모델링 프로세스를 수행하는 중요한 도구로 등장하며 수중 유압 점프의 특성은 CFD 시뮬레이션을 사용하여 정확하게 예측할 수 있습니다 [22,23 ].

본 논문은 초기에 수중 유압 점프의 주요 특성, 수치 모델에 대한 입력 매개변수 및 Ahmed et al.의 참조 실험 조사를 제시합니다. [20], 검증 목적으로 보고되었습니다. 또한, 본 연구에서는 유선의 종방향 프로파일, 캐비티 영역의 유동 패턴, 수평 속도 프로파일, 내부 층의 두께, 베드 전단 응력 계수, TKE 및 에너지 손실과 같은 특성을 조사할 것입니다.

Figure 1. Definition sketch of a submerged hydraulic jump at triangular macroroughnesses.
Figure 1. Definition sketch of a submerged hydraulic jump at triangular macroroughnesses.

Table 2. Effective parameters in the numerical model.

Bed TypeQ
(l/s)
I
(cm)
T (cm)d (cm)y1
(cm)
y4
(cm)
Fr1= u1/(gy1)0.5SRe1= (u1y1)/υ
Smooth30, 4551.62–3.839.64–32.101.7–9.30.26–0.5039,884–59,825
Triangular macroroughnesses30, 454, 8, 12, 16, 20451.62–3.846.82–30.081.7–9.30.21–0.4439,884–59,825
Figure 2. Longitudinal profile of the experimental flume (Ahmed et al. [20]).
Figure 2. Longitudinal profile of the experimental flume (Ahmed et al. [20]).

Table 3. Main flow variables for the numerical and physical models (Ahmed et al. [20]).

ModelsBed TypeQ (l/s)d (cm)y1 (cm)u1 (m/s)Fr1
Numerical and PhysicalSmooth4551.62–3.831.04–3.701.7–9.3
T/I = 0.54551.61–3.831.05–3.711.7–9.3
T/I = 0.254551.60–3.841.04–3.711.7–9.3
Figure 3. The boundary conditions governing the simulations.
Figure 3. The boundary conditions governing the simulations.
Figure 4. Sketch of mesh setup.
Figure 4. Sketch of mesh setup.

Table 4. Characteristics of the computational grids.

MeshNested Block Cell Size (cm)Containing Block Cell Size (cm)
10.551.10
20.651.30
30.851.70

Table 5. The numerical results of mesh convergence analysis.

ParametersAmounts
fs1 (-)7.15
fs2 (-)6.88
fs3 (-)6.19
K (-)5.61
E32 (%)10.02
E21 (%)3.77
GCI21 (%)3.03
GCI32 (%)3.57
GCI32/rp GCI210.98
Figure 5. Time changes of the flow discharge in the inlet and outlet boundaries conditions (A): Q = 0.03 m3/s (B): Q = 0.045 m3/s.
Figure 5. Time changes of the flow discharge in the inlet and outlet boundaries conditions (A): Q = 0.03 m3/s (B): Q = 0.045 m3/s.
Figure 6. The evolutionary process of a submerged hydraulic jump on the smooth bed—Q = 0.03 m3/s.
Figure 6. The evolutionary process of a submerged hydraulic jump on the smooth bed—Q = 0.03 m3/s.
Figure 7. Numerical versus experimental basic parameters of the submerged hydraulic jump. (A): y3/y1; and (B): y4/y1.
Figure 7. Numerical versus experimental basic parameters of the submerged hydraulic jump. (A): y3/y1; and (B): y4/y1.
Figure 8. Velocity vector field and flow pattern through the gate in a submerged hydraulic jump condition: (A) smooth bed; (B) triangular macroroughnesses.
Figure 8. Velocity vector field and flow pattern through the gate in a submerged hydraulic jump condition: (A) smooth bed; (B) triangular macroroughnesses.
Figure 9. Velocity vector distributions in the x–z plane (y = 0) within the cavity region.
Figure 9. Velocity vector distributions in the x–z plane (y = 0) within the cavity region.
Figure 10. Typical vertical distribution of the mean horizontal velocity in a submerged hydraulic jump [46].
Figure 10. Typical vertical distribution of the mean horizontal velocity in a submerged hydraulic jump [46].
Figure 11. Typical horizontal velocity profiles in a submerged hydraulic jump on smooth bed and triangular macroroughnesses.
Figure 11. Typical horizontal velocity profiles in a submerged hydraulic jump on smooth bed and triangular macroroughnesses.
Figure 12. Horizontal velocity distribution at different distances from the sluice gate for the different T/I for Fr1 = 6.1
Figure 12. Horizontal velocity distribution at different distances from the sluice gate for the different T/I for Fr1 = 6.1
Figure 13. Stream-wise velocity distribution for the triangular macroroughnesses with T/I = 0.5 and 0.25.
Figure 13. Stream-wise velocity distribution for the triangular macroroughnesses with T/I = 0.5 and 0.25.
Figure 14. Dimensionless horizontal velocity distribution in the submerged hydraulic jump for different Froude numbers in triangular macroroughnesses.
Figure 14. Dimensionless horizontal velocity distribution in the submerged hydraulic jump for different Froude numbers in triangular macroroughnesses.
Figure 15. Spatial variations of (umax/u1) and (δ⁄y1).
Figure 15. Spatial variations of (umax/u1) and (δ⁄y1).
Figure 16. The shear stress coefficient (ε) versus the inlet Froude number (Fr1).
Figure 16. The shear stress coefficient (ε) versus the inlet Froude number (Fr1).
Figure 17. Longitudinal turbulent kinetic energy distribution on the smooth and triangular macroroughnesses: (A) Y/2; (B) Y/6.
Figure 17. Longitudinal turbulent kinetic energy distribution on the smooth and triangular macroroughnesses: (A) Y/2; (B) Y/6.
Figure 18. The energy loss (EL/E3) of the submerged jump versus inlet Froude number (Fr1).
Figure 18. The energy loss (EL/E3) of the submerged jump versus inlet Froude number (Fr1).

Conclusions

  • 본 논문에서는 유선의 종방향 프로파일, 공동 영역의 유동 패턴, 수평 속도 프로파일, 스트림 방향 속도 분포, 내부 층의 두께, 베드 전단 응력 계수, 난류 운동 에너지(TKE)를 포함하는 수중 유압 점프의 특성을 제시하고 논의했습니다. ) 및 삼각형 거시적 거칠기에 대한 에너지 손실. 이러한 특성은 FLOW-3D® 모델을 사용하여 수치적으로 조사되었습니다. 자유 표면을 시뮬레이션하기 위한 VOF(Volume of Fluid) 방법과 난류 RNG k-ε 모델이 구현됩니다. 본 모델을 검증하기 위해 평활층과 삼각형 거시 거칠기에 대해 수치 시뮬레이션과 실험 결과를 비교했습니다. 본 연구의 다음과 같은 결과를 도출할 수 있다.
  • 개발 및 개발 지역의 삼각형 거시 거칠기의 흐름 패턴은 수중 유압 점프 조건의 매끄러운 바닥과 비교하여 더 작은 영역에서 동일합니다. 삼각형의 거대 거칠기는 거대 거칠기 사이의 공동 영역에서 또 다른 시계 방향 와류의 형성으로 이어집니다.
  • T/I = 1, 0.5 및 0.33과 같은 거리에 대해 속도 벡터 분포는 캐비티 영역에서 시계 방향 소용돌이를 표시하며, 여기서 속도의 크기는 평균 유속보다 훨씬 작습니다. 삼각형 거대 거칠기(T/I = 0.25 및 0.2) 사이의 거리를 늘리면 캐비티 영역에 크기가 다른 두 개의 소용돌이가 형성됩니다.
  • 삼각형 거시조도 사이의 거리가 충분히 길면 흐름이 다음 조도에 도달할 때까지 속도 분포가 회복됩니다. 그러나 짧은 거리에서 흐름은 속도 분포의 적절한 회복 없이 다음 거칠기에 도달합니다. 따라서 거시 거칠기 사이의 거리가 감소함에 따라 마찰 계수의 증가율이 감소합니다.
  • 삼각형의 거시적 거칠기에서, 잠수 점프의 지정된 섹션에서 최대 속도는 자유 점프보다 높은 값으로 이어집니다. 또한, 수중 점프에서 두 가지 유형의 베드(부드러움 및 거친 베드)에 대해 깊이 및 와류 증가로 인해 베드로부터의 최대 속도 거리는 감소합니다. 잠수 점프에서 경계층 두께는 자유 점프보다 얇습니다.
  • 매끄러운 베드의 난류 영역은 게이트로부터의 거리에 따라 생성되고 자유 표면 롤러 영역 근처에서 발생하는 반면, 거시적 거칠기에서는 난류가 게이트 근처에서 시작되어 더 큰 강도와 제한된 스위프 영역으로 시작됩니다. 이는 반시계 방향 순환의 결과입니다. 거시 거칠기 사이의 공간에서 자유 표면 롤러 및 시계 방향 와류.
  • 삼각 거시 거칠기에서 침지 점프의 베드 전단 응력 계수와 에너지 손실은 유입구 Froude 수의 증가에 따라 증가하는 매끄러운 베드에서 발견된 것보다 더 큽니다. T/I = 0.50 및 0.20에서 최고 및 최저 베드 전단 응력 계수 및 에너지 손실이 평활 베드에 비해 거칠기 요소의 거리가 증가함에 따라 발생합니다.
  • 거의 거칠기 요소가 있는 삼각형 매크로 거칠기의 존재에 의해 주어지는 점프 길이와 잠긴 수심 및 꼬리 수심의 감소는 결과적으로 크기, 즉 길이 및 높이가 감소하는 정수조 설계에 사용될 수 있습니다.
  • 일반적으로 CFD 모델은 다양한 수력 조건 및 기하학적 배열을 고려하여 잠수 점프의 특성 예측을 시뮬레이션할 수 있습니다. 캐비티 영역의 흐름 패턴, 흐름 방향 및 수평 속도 분포, 베드 전단 응력 계수, TKE 및 유압 점프의 에너지 손실은 수치적 방법으로 시뮬레이션할 수 있습니다. 그러나 거시적 차원과 유동장 및 공동 유동의 변화에 ​​대한 다양한 배열에 대한 연구는 향후 과제로 남아 있다.

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Flow on the inclined drop with bat-shaped elements: (a) Non-submerged flow

Numerical Methods in Civil Engineering

Rasoul Daneshfaraz*, Ehsan Aminvash**, Silvia Di Francesco***, Amir Najibi**, John Abraham****

토목공학의 수치해석법

Abstract

The main purpose of this study is to provide a method to increase energy dissipation on an inclined drop. Therefore, three types of rough elements with cylindrical, triangular and batshaped geometries are used on the inclined slope in the relative critical depth range of 0.128 to 0.36 and the effect of the geometry of these elements is examined using Flow 3D software. The results showed demonstrate that the downstream relative depth obtained from the numerical analysis is in good agreement with the laboratory results. The application of rough elements on the inclined drop increased the downstream relative depth and also the relative energy dissipation. The application of rough elements on the sloping surface of the drop significantly reduced the downstream Froude number, so that the Froude number in all models ranging from 4.7~7.5 to 1.45~3.36 also decreased compared to the plain drop. Bat-shaped elements are structurally smaller in size, so the use of these elements, in addition to dissipating more energy, is also economically viable.

이 연구의 주요 목적은 경사진 낙하에서 에너지 소산을 증가시키는 방법을 제공하는 것입니다. 따라서 0.128 ~ 0.36의 상대 임계 깊이 범위에서 경사면에 원통형, 삼각형 및 박쥐 모양의 형상을 가진 세 가지 유형의 거친 요소가 사용되며 이러한 요소의 형상의 영향은 Flow 3D 소프트웨어를 사용하여 조사됩니다. 결과는 수치 분석에서 얻은 하류 상대 깊이가 실험실 결과와 잘 일치함을 보여줍니다. 경 사진 낙하에 거친 요소를 적용하면 하류 상대 깊이와 상대 에너지 소산이 증가했습니다. 낙차 경사면에 거친 요소를 적용하면 하류의 Froude 수를 크게 감소시켜 4.7~7.5에서 1.45~3.36 범위의 모든 모델에서 Froude 수도 일반 낙차에 비해 감소했습니다. 박쥐 모양의 요소는 구조적으로 크기가 더 작기 때문에 더 많은 에너지를 분산시키는 것 외에도 이러한 요소를 사용하는 것이 경제적으로도 가능합니다.

Keywords: Downstream depth, Energy dissipation, Froude number, Inclined drop, Roughness elements

Introduction

급수 네트워크 시스템, 침식 수로, 수처리 시스템 및 경사가 큰 경우 흐름 에너지를 더 잘 제어하기 위해 경사 방울을 사용할 수 있습니다. 낙하 구조는 지반의 자연 경사를 설계 경사로 변환하여 에너지 소산, 유속 감소 및 수심 증가를 유발합니다. 따라서 흐름의 하류 에너지를 분산 시키기 위해 에너지 분산 구조를 사용할 수 있습니다. 난기류와 혼합된 물과 공기의 형성은 에너지 소비를 증가 시키는 효과적인 방법입니다. 흐름 경로에서 거칠기 요소를 사용하는 것은 에너지 소산을 위한 알려진 방법입니다. 이러한 요소는 흐름 경로에 배치됩니다. 그들은 종종 에너지 소산을 증가시키기 위해 다른 기하학적 구조와 배열을 가지고 있습니다. 이 연구의 목적은 직사각형 경사 방울에 대한 거칠기 요소의 영향을 조사하는 것입니다.

Fig. 1: Model made in Ardabil, Iran
Fig. 1: Model made in Ardabil, Iran
Fig. 2: Geometric and hydraulic parameters of an inclined drop equipped with roughness elements
Fig. 2: Geometric and hydraulic parameters of an inclined drop equipped with roughness elements
Fig. 3: Views of the incline with (a) Bat-shaped, (b) Cylindrical, (c) Triangular roughness elements
Fig. 3: Views of the incline with (a) Bat-shaped, (b) Cylindrical, (c) Triangular roughness elements
Fig. 4: Geometric profile of inclined drop and boundary conditions with the bat-shape roughness element
Fig. 4: Geometric profile of inclined drop and boundary conditions with the bat-shape roughness element
Fig. 5: Variation of the RMSE varying cell size
Fig. 5: Variation of the RMSE varying cell size
Fig. 6: Numerical and laboratory comparison of the downstream relative depth
Fig. 6: Numerical and laboratory comparison of the downstream relative depth
Fig. 7: Flow profile on inclined drop in discharge of 5 L/s: (a) Without roughness elements; (b) Bat-shaped roughness element; (c) Cylindrical roughness element; (d) Triangular roughness element
Fig. 7: Flow profile on inclined drop in discharge of 5 L/s: (a) Without roughness elements; (b) Bat-shaped roughness element; (c) Cylindrical roughness element; (d) Triangular roughness element
Fig. 8: Relative edge depth versus the relative critical depth
Fig. 8: Relative edge depth versus the relative critical depth
Flow on the inclined drop with bat-shaped elements: (a) Non-submerged flow
Flow on the inclined drop with bat-shaped elements: (a) Non-submerged flow
Fig. 9: Flow on the inclined drop with bat-shaped elements: (b) Submerged flow
Fig. 9: Flow on the inclined drop with bat-shaped elements: (b) Submerged flow
Fig. 10: Relative downstream depth versus the relative critical depth
Fig. 10: Relative downstream depth versus the relative critical depth
Fig. 11: Relative downstream depth versus the relative critical depth
Fig. 11: Relative downstream depth versus the relative critical depth

Conclusions

현재 연구에서 FLOW-3D 소프트웨어를 사용하여 한 높이, 한 각도, 밀도 15% 및 지그재그 배열에서 삼각형, 원통형 및 박쥐 모양의 형상을 가진 세 가지 유형의 거칠기 요소를 사용하여 경사 낙하 수리학적 매개변수에 대한 거칠기 요소 형상의 영향 평가되었다. VOF 방법을 사용하여 자유 표면 흐름을 시뮬레이션하고 초기에 3개의 난류 모델 RNG, k-ɛ 및 kω를 검증에 사용하고 이를 검토한 후 RNG 방법을 사용하여 다른 모델을 시뮬레이션했습니다. 1- 수치 결과에서 얻은 부드러운 경사 방울의 하류 상대 깊이는 실험실 데이터와 매우 좋은 상관 관계가 있으며 원통형 요소가 장착 된 경사 방울의 상대 에지 깊이 값이 가장 높았습니다. 2- 하류 상대깊이는 임계상대깊이가 증가함에 따라 상승하는 경향을 나타내어 박쥐형 요소를 구비한 경사낙하와 완만한 경사낙하가 각각 하류상대깊이가 가장 높고 가장 낮았다. 3- 하류 깊이의 증가로 인해 상대적 임계 깊이가 증가함에 따라 상대적 에너지 소산이 감소합니다. 한편, 가장 높은 에너지 소산은 박쥐 모양의 요소가 장착된 경사 낙하와 관련이 있으며 가장 낮은 에너지 소산은 부드러운 낙하와 관련이 있습니다. 삼각형, 원통형 및 박쥐 모양의 거친 요소가 장착된 드롭은 부드러운 드롭보다 각각 65%, 76% 및 85% 더 많은 흐름 에너지를 소산합니다. 4- 낙차의 경사면에 거친 요소를 적용하여 다운 스트림 Froude 수를 크게 줄여 4.7 ~ 7.5에서 1.45 ~ 3.36까지의 모든 모델에서 Froude 수가 부드러운 낙하에 비해 감소했습니다. 또한, 다른 원소보다 부피가 작은 박쥐 모양의 거칠기의 부피로 인해 이러한 유형의 거칠기를 사용하는 것이 경제적입니다.

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Numerical simulation of energy dissipation in crescent-shaped contraction of the flow path

Numerical simulation of energy dissipation in crescent-shaped contraction of the flow path

Authors

1 Professor, Department of Civil Engineering, Faculty of Engineering, University of Maragheh, Iran.
2 M.sc student, Department of Civil Engineering, Faculty of Engineering, University of Maragheh, Iran.
3 M.sc student, Department of Civil Engineering, Faculty of Engineering, University of Maragheh, Iran

Abstract

One of the methods of controlling and reducing flow energy is the use of energy dissipating structures and the formation of hydraulic jumps. One of these types of structures is the constriction elements in the flow path, which leads to a decrease in the energy of the passing flow. In the present study, the effect of crescent-shaped contraction as an energy dissipating structure in the supercritical flow path has been investigated using FLOW-3D software. Examining the simulation results, the RNG turbulence model due to its higher accuracy and lower relative error and absolute error percentage than other models, among the RNG turbulence models, k-ε, k-ω and LES was selected. In this study, the amplitude of the Froude number after the gate as the most effective dimensionless parameter in energy dissipation varied from 2.8 to 7.5 and the values of stenosis on both sides are 5 and 7.5 cm. The results show that in all cases of using the crescent-shaped contractions, the energy consumption due to the contraction is 5 and 7.5 cm, respectively, based on the energy drop relative to the upstream of 24.62% and 29.84% and compared to the downstream 46.14% and 48.42% more than the classic free jump. Also, by examining the obtained results, it was observed that the crescent-shaped contractions have a better performance in terms of energy loss compared to the sudden contraction, obtained from the studies of previous researchers. Based on the simulation results, with increasing the upstream Froude number, the relative energy dissipation to the upstream and downstream crescent-shaped contraction increased so that the use of contraction elements reduces the downstream Froude number of the contracted section in the range of 1.6 to 3/2.

흐름 에너지를 제어하고 줄이는 방법 중 하나는 에너지 소산 구조를 사용하고 유압 점프를 형성하는 것입니다. 이러한 유형의 구조 중 하나는 흐름 경로의 수축 요소로, 통과하는 흐름의 에너지를 감소시킵니다. 현재 연구에서는 초 임계 유동 경로에서 에너지 소산 구조로서 초승달 모양의 수축 효과가 FLOW-3D 소프트웨어를 사용하여 조사되었습니다. 시뮬레이션 결과를 살펴보면 RNG 난류 모델 중 k-ε, k-ω, LES 중에서 다른 모델보다 정확도가 높고 상대 오차와 절대 오차 비율이 낮은 RNG 난류 모델을 선택했습니다. 이 연구에서 에너지 소산에서 가장 효과적인 무 차원 매개 변수 인 게이트 뒤의 Froude 수의 진폭은 2.8에서 7.5까지 다양했으며 양쪽의 협착 값은 5cm와 7.5cm입니다. 결과는 초승달 모양의 수축을 사용하는 모든 경우에서 수축으로 인한 에너지 소비는 각각 5cm와 7.5cm로 상류에 비해 에너지 강하가 24.62 % 및 29.84 %이고 하류와 비교됩니다. 고전적인 자유 점프보다 46.14 % 및 48.42 % 더 많습니다. 또한 얻어진 결과를 살펴보면 초승달 모양의 수축이 이전 연구자들의 연구에서 얻은 갑작스런 수축에 비해 에너지 손실 측면에서 더 나은 성능을 보이는 것으로 나타났습니다. 시뮬레이션 결과에 따르면 상류 Froude 수를 증가 시키면 상류 및 하류 초승달 모양의 수축에 대한 상대적 에너지 소산이 증가하여 수축 요소를 사용하면 수축 된 부분의 하류 Froude 수가 1.6 ~ 3/2 범위에서 감소합니다. .

Keywords

The 3D computational domain model (50–18.6) slope change, and boundary condition for (50–30 slope change) model.

Numerical investigation of flow characteristics over stepped spillways

Güven, Aytaç
Mahmood, Ahmed Hussein
Water Supply (2021) 21 (3): 1344–1355.
https://doi.org/10.2166/ws.2020.283Article history

Abstract

Spillways are constructed to evacuate flood discharge safely so that a flood wave does not overtop the dam body. There are different types of spillways, with the ogee type being the conventional one. A stepped spillway is an example of a nonconventional spillway. The turbulent flow over a stepped spillway was studied numerically by using the Flow-3D package. Different fluid flow characteristics such as longitudinal flow velocity, temperature distribution, density and chemical concentration can be well simulated by Flow-3D. In this study, the influence of slope changes on flow characteristics such as air entrainment, velocity distribution and dynamic pressures distribution over a stepped spillway was modelled by Flow-3D. The results from the numerical model were compared with an experimental study done by others in the literature. Two models of a stepped spillway with different discharge for each model were simulated. The turbulent flow in the experimental model was simulated by the Renormalized Group (RNG) turbulence scheme in the numerical model. A good agreement was achieved between the numerical results and the observed ones, which are exhibited in terms of graphics and statistical tables.

배수로는 홍수가 댐 몸체 위로 넘치지 않도록 안전하게 홍수를 피할 수 있도록 건설되었습니다. 다른 유형의 배수로가 있으며, ogee 유형이 기존 유형입니다. 계단식 배수로는 비 전통적인 배수로의 예입니다. 계단식 배수로 위의 난류는 Flow-3D 패키지를 사용하여 수치적으로 연구되었습니다.

세로 유속, 온도 분포, 밀도 및 화학 농도와 같은 다양한 유체 흐름 특성은 Flow-3D로 잘 시뮬레이션 할 수 있습니다. 이 연구에서는 계단식 배수로에 대한 공기 혼입, 속도 분포 및 동적 압력 분포와 같은 유동 특성에 대한 경사 변화의 영향을 Flow-3D로 모델링 했습니다.

수치 모델의 결과는 문헌에서 다른 사람들이 수행한 실험 연구와 비교되었습니다. 각 모델에 대해 서로 다른 배출이 있는 계단식 배수로의 두 모델이 시뮬레이션되었습니다. 실험 모델의 난류 흐름은 수치 모델의 Renormalized Group (RNG) 난류 계획에 의해 시뮬레이션되었습니다. 수치 결과와 관찰 된 결과 사이에 좋은 일치가 이루어졌으며, 이는 그래픽 및 통계 테이블로 표시됩니다.

HIGHLIGHTS

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  • A numerical model was developed for stepped spillways.
  • The turbulent flow was simulated by the Renormalized Group (RNG) model.
  • Both numerical and experimental results showed that flow characteristics are greatly affected by abrupt slope change on the steps.

Keyword

CFDnumerical modellingslope changestepped spillwayturbulent flow

INTRODUCTION

댐 구조는 물 보호가 생활의 핵심이기 때문에 물을 저장하거나 물을 운반하는 전 세계에서 가장 중요한 프로젝트입니다. 그리고 여수로는 댐의 가장 중요한 부분 중 하나로 분류됩니다. 홍수로 인한 파괴 나 피해로부터 댐을 보호하기 위해 여수로가 건설됩니다.

수력 발전, 항해, 레크리에이션 및 어업의 중요성을 감안할 때 댐 건설 및 홍수 통제는 전 세계적으로 매우 중요한 문제로 간주 될 수 있습니다. 많은 유형의 배수로가 있지만 가장 일반적인 유형은 다음과 같습니다 : ogee 배수로, 자유 낙하 배수로, 사이펀 배수로, 슈트 배수로, 측면 채널 배수로, 터널 배수로, 샤프트 배수로 및 계단식 배수로.

그리고 모든 여수로는 입구 채널, 제어 구조, 배출 캐리어 및 출구 채널의 네 가지 필수 구성 요소로 구성됩니다. 특히 롤러 압축 콘크리트 (RCC) 댐 건설 기술과 더 쉽고 빠르며 저렴한 건설 기술로 분류 된 계단식 배수로 건설과 관련하여 최근 수십 년 동안 많은 계단식 배수로가 건설되었습니다 (Chanson 2002; Felder & Chanson 2011).

계단식 배수로 구조는 캐비테이션 위험을 감소시키는 에너지 소산 속도를 증가시킵니다 (Boes & Hager 2003b). 계단식 배수로는 다양한 조건에서 더 매력적으로 만드는 장점이 있습니다.

계단식 배수로의 흐름 거동은 일반적으로 낮잠, 천이 및 스키밍 흐름 체제의 세 가지 다른 영역으로 분류됩니다 (Chanson 2002). 유속이 낮을 때 nappe 흐름 체제가 발생하고 자유 낙하하는 낮잠의 시퀀스로 특징 지워지는 반면, 스키밍 흐름 체제에서는 물이 외부 계단 가장자리 위의 유사 바닥에서 일관된 흐름으로 계단 위로 흐릅니다.

또한 주요 흐름에서 3 차원 재순환 소용돌이가 발생한다는 것도 분명합니다 (예 : Chanson 2002; Gonzalez & Chanson 2008). 계단 가장자리 근처의 의사 바닥에서 흐름의 방향은 가상 바닥과 가상으로 정렬됩니다. Takahashi & Ohtsu (2012)에 따르면, 스키밍 흐름 체제에서 주어진 유속에 대해 흐름은 계단 가장자리 근처의 수평 계단면에 영향을 미치고 슈트 경사가 감소하면 충돌 영역의 면적이 증가합니다. 전이 흐름 체제는 나페 흐름과 스키밍 흐름 체제 사이에서 발생합니다. 계단식 배수로를 설계 할 때 스키밍 흐름 체계를 고려해야합니다 (예 : Chanson 1994, Matos 2000, Chanson 2002, Boes & Hager 2003a).

CFD (Computational Fluid Dynamics), 즉 수력 공학의 수치 모델은 일반적으로 물리적 모델에 소요되는 총 비용과 시간을 줄여줍니다. 따라서 수치 모델은 실험 모델보다 빠르고 저렴한 것으로 분류되며 동시에 하나 이상의 목적으로 사용될 수도 있습니다. 사용 가능한 많은 CFD 소프트웨어 패키지가 있지만 가장 널리 사용되는 것은 FLOW-3D입니다. 이 연구에서는 Flow 3D 소프트웨어를 사용하여 유량이 서로 다른 두 모델에 대해 계단식 배수로에서 공기 농도, 속도 분포 및 동적 압력 분포를 시뮬레이션합니다.

Roshan et al. (2010)은 서로 다른 수의 계단 및 배출을 가진 계단식 배수로의 두 가지 물리적 모델에 대한 흐름 체제 및 에너지 소산 조사를 연구했습니다. 실험 모델의 기울기는 각각 19.2 %, 12 단계와 23 단계의 수입니다. 결과는 23 단계 물리적 모델에서 관찰 된 흐름 영역이 12 단계 모델보다 더 수용 가능한 것으로 간주되었음을 보여줍니다. 그러나 12 단계 모델의 에너지 손실은 23 단계 모델보다 더 많았습니다. 그리고 실험은 스키밍 흐름 체제에서 23 단계 모델의 에너지 소산이 12 단계 모델보다 약 12 ​​% 더 적다는 것을 관찰했습니다.

Ghaderi et al. (2020a)는 계단 크기와 유속이 다른 정련 매개 변수의 영향을 조사하기 위해 계단식 배수로에 대한 실험 연구를 수행했습니다. 그 결과, 흐름 체계가 냅페 흐름 체계에서 발생하는 최소 scouring 깊이와 같은 scouring 구멍 치수에 영향을 미친다는 것을 보여주었습니다. 또한 테일 워터 깊이와 계단 크기는 최대 scouring깊이에 대한 실제 매개 변수입니다. 테일 워터의 깊이를 6.31cm에서 8.54 및 11.82cm로 늘림으로써 수세 깊이가 각각 18.56 % 및 11.42 % 증가했습니다. 또한 이 증가하는 테일 워터 깊이는 scouring 길이를 각각 31.43 % 및 16.55 % 감소 시킵니다. 또한 유속을 높이면 Froude 수가 증가하고 흐름의 운동량이 증가하면 scouring이 촉진됩니다. 또한 결과는 중간의 scouring이 횡단면의 측벽보다 적다는 것을 나타냅니다. 계단식 배수로 하류의 최대 scouring 깊이를 예측 한 후 실험 결과와 비교하기 위한 실험식이 제안 되었습니다. 그리고 비교 결과 제안 된 공식은 각각 3.86 %와 9.31 %의 상대 오차와 최대 오차 내에서 scouring 깊이를 예측할 수 있음을 보여주었습니다.

Ghaderi et al. (2020b)는 사다리꼴 미로 모양 (TLS) 단계의 수치 조사를 했습니다. 결과는 이러한 유형의 배수로가 확대 비율 LT / Wt (LT는 총 가장자리 길이, Wt는 배수로의 폭)를 증가시키기 때문에 더 나은 성능을 갖는 것으로 관찰되었습니다. 또한 사다리꼴 미로 모양의 계단식 배수로는 더 큰 마찰 계수와 더 낮은 잔류 수두를 가지고 있습니다. 마찰 계수는 다양한 배율에 대해 0.79에서 1.33까지 다르며 평평한 계단식 배수로의 경우 대략 0.66과 같습니다. 또한 TLS 계단식 배수로에서 잔류 수두의 비율 (Hres / dc)은 약 2.89이고 평평한 계단식 배수로의 경우 약 4.32와 같습니다.

Shahheydari et al. (2015)는 Flow-3D 소프트웨어, RNG k-ε 모델 및 VOF (Volume of Fluid) 방법을 사용하여 배출 계수 및 에너지 소산과 같은 자유 표면 흐름의 프로파일을 연구하여 스키밍 흐름 체제에서 계단식 배수로에 대한 흐름을 조사했습니다. 실험 결과와 비교했습니다. 결과는 에너지 소산 율과 방전 계수율의 관계가 역으로 실험 모델의 결과와 잘 일치 함을 보여 주었다.

Mohammad Rezapour Tabari & Tavakoli (2016)는 계단 높이 (h), 계단 길이 (L), 계단 수 (Ns) 및 단위 폭의 방전 (q)과 같은 다양한 매개 변수가 계단식 에너지 ​​소산에 미치는 영향을 조사했습니다. 방수로. 그들은 해석에 FLOW-3D 소프트웨어를 사용하여 계단식 배수로에서 에너지 손실과 임계 흐름 깊이 사이의 관계를 평가했습니다. 또한 유동 난류에 사용되는 방정식과 표준 k-ɛ 모델을 풀기 위해 유한 체적 방법을 적용했습니다. 결과에 따르면 스텝 수가 증가하고 유량 배출량이 증가하면 에너지 손실이 감소합니다. 얻은 결과를 다른 연구와 비교하고 경험적, 수학적 조사를 수행하여 결국 합격 가능한 결과를 얻었습니다.

METHODOLOGY

ListenReadSpeaker webReader: ListenFor all numerical models the basic principle is very similar: a set of partial differential equations (PDE) present the physical problems. The flow of fluids (gas and liquid) are governed by the conservation laws of mass, momentum and energy. For Computational Fluid Dynamics (CFD), the PDE system is substituted by a set of algebraic equations which can be worked out by using numerical methods (Versteeg & Malalasekera 2007). Flow-3D uses the finite volume approach to solve the Reynolds Averaged Navier-Stokes (RANS) equation, by applying the technique of Fractional Area/Volume Obstacle Representation (FAVOR) to define an obstacle (Flow Science Inc. 2012). Equations (1) and (2) are RANS and continuity equations with FAVOR variables that are applied for incompressible flows.

formula

(1)

formula

(2)where  is the velocity in xi direction, t is the time,  is the fractional area open to flow in the subscript directions,  is the volume fraction of fluid in each cell, p is the hydrostatic pressure,  is the density, is the gravitational force in subscript directions and  is the Reynolds stresses.

Turbulence modelling is one of three key elements in CFD (Gunal 1996). There are many types of turbulence models, but the most common are Zero-equation models, One-equation models, Two-equation models, Reynolds Stress/Flux models and Algebraic Stress/Flux models. In FLOW-3D software, five turbulence models are available. The formulation used in the FLOW-3D software differs slightly from other formulations that includes the influence of the fractional areas/volumes of the FAVORTM method and generalizes the turbulence production (or decay) associated with buoyancy forces. The latter generalization, for example, includes buoyancy effects associated with non-inertial accelerations.

The available turbulence models in Flow-3D software are the Prandtl Mixing Length Model, the One-Equation Turbulent Energy Model, the Two-Equation Standard  Model, the Two-Equation Renormalization-Group (RNG) Model and large Eddy Simulation Model (Flow Science Inc. 2012).In this research the RNG model was selected because this model is more commonly used than other models in dealing with particles; moreover, it is more accurate to work with air entrainment and other particles. In general, the RNG model is classified as a more widely-used application than the standard k-ɛ model. And in particular, the RNG model is more accurate in flows that have strong shear regions than the standard k-ɛ model and it is defined to describe low intensity turbulent flows. For the turbulent dissipation  it solves an additional transport equation:

formula

(3)where CDIS1, CDIS2, and CDIS3 are dimensionless parameters and the user can modify them. The diffusion of dissipation, Diff ɛ, is

formula

(4)where uv and w are the x, y and z coordinates of the fluid velocity; ⁠, ⁠,  and ⁠, are FLOW-3D’s FAVORTM defined terms;  and  are turbulence due to shearing and buoyancy effects, respectively. R and  are related to the cylindrical coordinate system. The default values of RMTKE, CDIS1 and CNU differ, being 1.39, 1.42 and 0.085 respectively. And CDIS2 is calculated from turbulent production (⁠⁠) and turbulent kinetic energy (⁠⁠).The kinematic turbulent viscosity is the same in all turbulence transport models and is calculated from

formula

(5)where ⁠: is the turbulent kinematic viscosity.  is defined as the numerical challenge between the RNG and the two-equation k-ɛ models, found in the equation below. To avoid an unphysically large result for  in Equation (3), since this equation could produce a value for  very close to zero and also because the physical value of  may approach to zero in such cases, the value of  is calculated from the following equation:

formula

(6)where ⁠: the turbulent length scale.

VOF and FAVOR are classifications of volume-fraction methods. In these two methods, firstly the area should be subdivided into a control volume grid or a small element. Each flow parameter like velocity, temperature and pressure values within the element are computed for each element containing liquids. Generally, these values represent the volumetric average of values in the elements.Numerous methods have been used recently to solve free infinite boundaries in the various numerical simulations. VOF is an easy and powerful method created based on the concept of a fractional intensity of fluid. A significant number of studies have confirmed that this method is more flexible and efficient than others dealing with the configurations of a complex free boundary. By using VOF technology the Flow-3D free surface was modelled and first declared in Hirt & Nichols (1981). In the VOF method there are three ingredients: a planner to define the surface, an algorithm for tracking the surface as a net mediator moving over a computational grid, and application of the boundary conditions to the surface. Configurations of the fluids are defined in terms of VOF function, F (x, y, z, t) (Hirt & Nichols 1981). And this VOF function shows the volume of flow per unit volume

formula

(7)

formula

(8)

formula

(9)where  is the density of the fluid, is a turbulent diffusion term,  is a mass source,  is the fractional volume open to flow. The components of velocity (u, v, w) are in the direction of coordinates (x, y, z) or (r, ⁠).  in the x-direction is the fractional area open to flow,  and  are identical area fractions for flow in the y and z directions. The R coefficient is based on the selection of the coordinate system.

The FAVOR method is a different method and uses another volume fraction technique, which is only used to define the geometry, such as the volume of liquid in each cell used to determine the position of fluid surfaces. Another fractional volume can be used to define the solid surface. Then, this information is used to determine the boundary conditions of the wall that the flow should be adapted for.

Case study

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In this study, the experimental results of Ostad Mirza (2016) was simulated. In a channel composed of two 4 m long modules, with a transparent sidewall of height 0.6 m and 0.5 m width. The upstream chute slope (i.e. pseudo-bottom angle) Ɵ1 = 50°, the downstream chute slope Ɵ2 = 30° or 18.6°, the step heights h = 0.06 m, the total number of steps along the 50° chute 41 steps, the total number of steps along the 30° chute 34 steps and the total number of steps along the 18.6° chute 20 steps.

The flume inflow tool contained a jetbox with a maximum opening set to 0.12 meters, designed for passing the maximum unit discharge of 0.48 m2/s. The measurements of the flow properties (i.e. air concentration and velocity) were computed perpendicular to the pseudo-bottom as shown in Figure 1 at the centre of twenty stream-wise cross-sections, along the stepped chute, (i.e. in five steps up on the slope change and fifteen steps down on the slope change, namely from step number −09 to +23 on 50°–30° slope change, or from −09 to +15 on 50°–18.6° slope change, respectively).

Sketch of the air concentration C and velocity V measured perpendicular to the pseudo-bottom used by Mirza (Ostad Mirza 2016).
Sketch of the air concentration C and velocity V measured perpendicular to the pseudo-bottom used by Mirza (Ostad Mirza 2016).

Sketch of the air concentration C and velocity V measured perpendicular to the pseudo-bottom used by Mirza (Ostad Mirza 2016).

Pressure sensors were arranged with the x/l values for different slope change as shown in Table 1, where x is the distance from the step edge, along the horizontal step face, and l is the length of the horizontal step face. The location of pressure sensors is shown in Table 1.Table 1

Location of pressure sensors on horizontal step faces

Θ(°)L(m)x/l (–)
50.0 0.050 0.35 0.64 – – – 
30.0 0.104 0.17 0.50 0.84 – – 
18.6 0.178 0.10 0.30 0.50 0.7 0.88 
Location of pressure sensors on horizontal step faces
Inlet boundary condition for Q = 0.235 m3/s and fluid elevation 4.21834 m.
Inlet boundary condition for Q = 0.235 m3/s and fluid elevation 4.21834 m.

Inlet boundary condition for Q = 0.235 m3/s and fluid elevation 4.21834 m.

Numerical model set-up

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A 3D numerical model of hydraulic phenomena was simulated based on an experimental study by Ostad Mirza (2016). The water surcharge and flow pressure over the stepped spillway was computed for two models of a stepped spillway with different discharge for each model. In this study, the package was used to simulate the flow parameters such as air entrainment, velocity distribution and dynamic pressures. The solver uses the finite volume technique to discretize the computational domain. In every test run, one incompressible fluid flow with a free surface flow selected at 20̊ was used for this simulation model. Table 2 shows the variables used in test runs.Table 2

Variables used in test runs

Test no.Θ1 (°)Θ2 (°)h(m)d0q (m3s1)dc/h (–)
50 18.6 0.06 0.045 0.1 2.6 
50 18.6 0.06 0.082 0.235 4.6 
50 30.0 0.06 0.045 0.1 2.6 
50 30.0 0.06 0.082 0.235 4.6 
Table 2 Variables used in test runs

For stepped spillway simulation, several parameters should be specified to get accurate simulations, which is the scope of this research. Viscosity and turbulent, gravity and non-inertial reference frame, air entrainment, density evaluation and drift-flux should be activated for these simulations. There are five different choices in the ‘viscosity and turbulent’ option, in the viscosity flow and Renormalized Group (RNG) model. Then a dynamical model is selected as the second option, the ‘gravity and non-inertial reference frame’. Only the z-component was inputted as a negative 9.81 m/s2 and this value represents gravitational acceleration but in the same option the x and y components will be zero. Air entrainment is selected. Finally, in the drift-flux model, the density of phase one is input as (water) 1,000 kg/m3 and the density of phase two (air) as 1.225 kg/m3. Minimum volume fraction of phase one is input equal to 0.1 and maximum volume fraction of phase two to 1 to allow air concentration to reach 90%, then the option allowing gas to escape at free surface is selected, to obtain closer simulation.

The flow domain is divided into small regions relatively by the mesh in Flow-3D numerical model. Cells are the smallest part of the mesh, in which flow characteristics such as air concentration, velocity and dynamic pressure are calculated. The accuracy of the results and simulation time depends directly on the mesh block size so the cell size is very important. Orthogonal mesh was used in cartesian coordinate systems. A smaller cell size provides more accuracy for results, so we reduced the number of cells whilst including enough accuracy. In this study, the size of cells in x, y and z directions was selected as 0.015 m after several trials.

Figure 3 shows the 3D computational domain model 50–18.6 slope change, that is 6.0 m length, 0.50 m width and 4.23 m height. The 3D model of the computational domain model 50–30 slope changes this to 6.0 m length, 0.50 m width and 5.068 m height and the size of meshes in x, y, and z directions are 0.015 m. For the 50–18.6 slope change model: both total number of active and passive cells = 4,009,952, total number of active cells = 3,352,307, include real cells (used for solving the flow equations) = 3,316,269, open real cells = 3,316,269, fully blocked real cells equal to zero, external boundary cells were 36,038, inter-block boundary cells = 0 (Flow-3D report). For 50–30 slope change model: both total number of active and passive cells = 4,760,002, total number of active cells equal to 4,272,109, including real cells (used for solving the flow equations) were 3,990,878, open real cells = 3,990,878 fully blocked real cells = zero, external boundary cells were 281,231, inter-block boundary cells = 0 (Flow-3D report).

The 3D computational domain model (50–18.6) slope change, and boundary condition for (50–30 slope change) model.
Figure3 The 3D computational domain model (50–18.6) slope change, and boundary condition for (50–30 slope change) model.

Figure 3VIEW LARGEDOWNLOAD SLIDE

The 3D computational domain model (50–18.6) slope change, and boundary condition for (50–30 slope change) model.

When solving the Navier-Stokes equation and continuous equations, boundary conditions should be applied. The most important work of boundary conditions is to create flow conditions similar to physical status. The Flow-3D software has many types of boundary condition; each type can be used for the specific condition of the models. The boundary conditions in Flow-3D are symmetry, continuative, specific pressure, grid overlay, wave, wall, periodic, specific velocity, outflow, and volume flow rate.

There are two options to input finite flow rate in the Flow-3D software either for inlet discharge of the system or for the outlet discharge of the domain: specified velocity and volume flow rate. In this research, the X-minimum boundary condition, volume flow rate, has been chosen. For X-maximum boundary condition, outflow was selected because there is nothing to be calculated at the end of the flume. The volume flow rate and the elevation of surface water was set for Q = 0.1 and 0.235 m3/s respectively (Figure 2).

The bottom (Z-min) is prepared as a wall boundary condition and the top (Z-max) is computed as a pressure boundary condition, and for both (Y-min) and (Y-max) as symmetry.

RESULTS AND DISCUSSION

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The air concentration distribution profiles in two models of stepped spillway were obtained at an acquisition time equal to 25 seconds in skimming flow for both upstream and downstream of a slope change 50°–18.6° and 50°–30° for different discharge as in Table 2, and as shown in Figure 4 for 50°–18.6° slope change and Figure 5 for 50°–30° slope change configuration for dc/h = 4.6. The simulation results of the air concentration are very close to the experimental results in all curves and fairly close to that predicted by the advection-diffusion model for the air bubbles suggested by Chanson (1997) on a constant sloping chute.

Figure 4 Experimental and simulated air concentration distribution for steps number −5, +1, +5, +8, +11 and +15 along the 50°–18.6° slope change for dc/h = 4.6. VIEW LARGEDOWNLOAD SLIDE Experimental and simulated air concentration distribution for steps number −5, +1, +5, +8, +11 and +15 along the 50°–18.6° slope change for dc/h = 4.6.
Figure 4 Experimental and simulated air concentration distribution for steps number −5, +1, +5, +8, +11 and +15 along the 50°–18.6° slope change for dc/h = 4.6. VIEW LARGEDOWNLOAD SLIDE Experimental and simulated air concentration distribution for steps number −5, +1, +5, +8, +11 and +15 along the 50°–18.6° slope change for dc/h = 4.6.

Figure 4VIEW LARGEDOWNLOAD SLIDE

Experimental and simulated air concentration distribution for steps number −5, +1, +5, +8, +11 and +15 along the 50°–18.6° slope change for dc/h = 4.6.

Figure5 Experimental and simulated air concentration distribution for steps number −5, +1, +5, +11, +19 and +22 along the 50°–30° slope change, for dc/h = 4.6.
Figure5 Experimental and simulated air concentration distribution for steps number −5, +1, +5, +11, +19 and +22 along the 50°–30° slope change, for dc/h = 4.6.

Figure 5VIEW LARGEDOWNLOAD SLIDE

Experimental and simulated air concentration distribution for steps number −5, +1, +5, +11, +19 and +22 along the 50°–30° slope change, for dc/h = 4.6.

Figure 6VIEW LARGEDOWNLOAD SLIDE

Figure 6 Experimental and simulated dimensionless velocity distribution for steps number −5, −1, +1, +5, +8, +11 and +15 along the 50°–18.6° slope change for dc/h = 2.6.
Figure 6 Experimental and simulated dimensionless velocity distribution for steps number −5, −1, +1, +5, +8, +11 and +15 along the 50°–18.6° slope change for dc/h = 2.6.

Experimental and simulated dimensionless velocity distribution for steps number −5, −1, +1, +5, +8, +11 and +15 along the 50°–18.6° slope change for dc/h = 2.6.

Figure 7 Experimental and simulated dimensionless velocity distribution for steps number −5, −1, +1, +5. +11, +15 and +22 along the 50°–30° slope change for dc/h = 2.6.
Figure 7 Experimental and simulated dimensionless velocity distribution for steps number −5, −1, +1, +5. +11, +15 and +22 along the 50°–30° slope change for dc/h = 2.6.

Figure 7VIEW LARGEDOWNLOAD SLIDE

Experimental and simulated dimensionless velocity distribution for steps number −5, −1, +1, +5. +11, +15 and +22 along the 50°–30° slope change for dc/h = 2.6.

But as is shown in all above mentioned figures it is clear that at the pseudo-bottom the CFD results of air concentration are less than experimental ones until the depth of water reaches a quarter of the total depth of water. Also the direction of the curves are parallel to each other when going up towards the surface water and are incorporated approximately near the surface water. For all curves, the cross-section is separate between upstream and downstream steps. Therefore the (-) sign for steps represents a step upstream of the slope change cross-section and the (+) sign represents a step downstream of the slope change cross-section.

The dimensionless velocity distribution (V/V90) profile was acquired at an acquisition time equal to 25 seconds in skimming flow of the upstream and downstream slope change for both 50°–18.6° and 50°–30° slope change. The simulation results are compared with the experimental ones showing that for all curves there is close similarity for each point between the observed and experimental results. The curves increase parallel to each other and they merge near at the surface water as shown in Figure 6 for slope change 50°–18.6° configuration and Figure 7 for slope change 50°–30° configuration. However, at step numbers +1 and +5 in Figure 7 there are few differences between the simulated and observed results, namely the simulation curves ascend regularly meaning the velocity increases regularly from the pseudo-bottom up to the surface water.

Figure 8 (50°–18.6° slope change) and Figure 9 (50°–30° slope change) compare the simulation results and the experimental results for the presented dimensionless dynamic pressure distribution for different points on the stepped spillway. The results show a good agreement with the experimental and numerical simulations in all curves. For some points, few discrepancies can be noted in pressure magnitudes between the simulated and the observed ones, but they are in the acceptable range. Although the experimental data do not completely agree with the simulated results, there is an overall agreement.

Figure 8 Comparison between simulated and experimental results for the dimensionless pressure for steps number  −1, −2, −3 and +1, +2 +3 and +20 on the horizontal step faces of 50°–18.6° slope change configuration, for dc/h = 4.6, x is the distance from the step edge.
Figure 8 Comparison between simulated and experimental results for the dimensionless pressure for steps number −1, −2, −3 and +1, +2 +3 and +20 on the horizontal step faces of 50°–18.6° slope change configuration, for dc/h = 4.6, x is the distance from the step edge.

Figure 8VIEW LARGEDOWNLOAD SLIDE

Comparison between simulated and experimental results for the dimensionless pressure for steps number −1, −2, −3 and +1, +2 +3 and +20 on the horizontal step faces of 50°–18.6° slope change configuration, for dc/h = 4.6, x is the distance from the step edge.

Figure 9 Comparison between simulated and experimental results for the dimensionless pressure for steps number  −1, −2, −3 and +1, +2 and +30, +31 on the horizontal step face of 50°–30° slope change configuration, for dc/h = 4.6, x is the distance from the step edge.
Figure 9 Comparison between simulated and experimental results for the dimensionless pressure for steps number −1, −2, −3 and +1, +2 and +30, +31 on the horizontal step face of 50°–30° slope change configuration, for dc/h = 4.6, x is the distance from the step edge.

Figure 9VIEW LARGEDOWNLOAD SLIDE

Comparison between simulated and experimental results for the dimensionless pressure for steps number −1, −2, −3 and +1, +2 and +30, +31 on the horizontal step face of 50°–30° slope change configuration, for dc/h = 4.6, x is the distance from the step edge.

The pressure profiles were acquired at an acquisition time equal to 70 seconds in skimming flow on 50°–18.6°, where p is the measured dynamic pressure, h is step height and ϒ is water specific weight. A negative sign for steps represents a step upstream of the slope change cross-section and a positive sign represents a step downstream of the slope change cross-section.

Figure 10 shows the experimental streamwise development of dimensionless pressure on the 50°–18.6° slope change for dc/h = 4.6, x/l = 0.35 on 50° sloping chute and x/l = 0.3 on 18.6° sloping chute compared with the numerical simulation. It is obvious from Figure 10 that the streamwise development of dimensionless pressure before slope change (steps number −1, −2 and −3) both of the experimental and simulated results are close to each other. However, it is clear that there is a little difference between the results of the streamwise development of dimensionless pressure at step numbers +1, +2 and +3. Moreover, from step number +3 to the end, the curves get close to each other.

Figure 10 Comparison between experimental and simulated results for the streamwise development of the dimensionless pressure on the 50°–18.6° slope change, for dc/h = 4.6, and x/l = 0.35 on 50° sloping chute and x/l = 0.3 on 18.6° sloping chute.
Figure 10 Comparison between experimental and simulated results for the streamwise development of the dimensionless pressure on the 50°–18.6° slope change, for dc/h = 4.6, and x/l = 0.35 on 50° sloping chute and x/l = 0.3 on 18.6° sloping chute.

Figure 10VIEW LARGEDOWNLOAD SLIDE

Comparison between experimental and simulated results for the streamwise development of the dimensionless pressure on the 50°–18.6° slope change, for dc/h = 4.6, and x/l = 0.35 on 50° sloping chute and x/l = 0.3 on 18.6° sloping chute.

Figure 11 compares the experimental and the numerical results for the streamwise development of the dimensionless pressure on the 50°–30° slope change, for dc/h = 4.6, and x/l = 0.35 on 50° sloping chute and x/l = 0.17 on 30° sloping chute. It is apparent that the outcomes of the experimental work are close to the numerical results, however, the results of the simulation are above the experimental ones before the slope change, but the results of the simulation descend below the experimental ones after the slope change till the end.

Figure 11 Comparison between experimental and simulated results for the streamwise development of the dimensionless pressure on the 50°–30° slope change, for dc/h = 4.6, and x/l = 0.35 on 50° sloping chute and x/l = 0.17 on 30° sloping chute.
Figure 11 Comparison between experimental and simulated results for the streamwise development of the dimensionless pressure on the 50°–30° slope change, for dc/h = 4.6, and x/l = 0.35 on 50° sloping chute and x/l = 0.17 on 30° sloping chute.

Figure 11VIEW LARGEDOWNLOAD SLIDE

Comparison between experimental and simulated results for the streamwise development of the dimensionless pressure on the 50°–30° slope change, for dc/h = 4.6, and x/l = 0.35 on 50° sloping chute and x/l = 0.17 on 30° sloping chute.

CONCLUSION

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In this research, numerical modelling was attempted to investigate the effect of abrupt slope change on the flow properties (air entrainment, velocity distribution and dynamic pressure) over a stepped spillway with two different models and various flow rates in a skimming flow regime by using the CFD technique. The numerical model was verified and compared with the experimental results of Ostad Mirza (2016). The same domain of the numerical model was inputted as in experimental models to reduce errors as much as possible.

Flow-3D is a well modelled tool that deals with particles. In this research, the model deals well with air entrainment particles by observing their results with experimental results. And the reason for the small difference between the numerical and the experimental results is that the program deals with particles more accurately than the laboratory. In general, both numerical and experimental results showed that near to the slope change the flow bulking, air entrainment, velocity distribution and dynamic pressure are greatly affected by abrupt slope change on the steps. Although the extent of the slope change was relatively small, the influence of the slope change was major on flow characteristics.

The Renormalized Group (RNG) model was selected as a turbulence solver. For 3D modelling, orthogonal mesh was used as a computational domain and the mesh grid size used for X, Y, and Z direction was equal to 0.015 m. In CFD modelling, air concentration and velocity distribution were recorded for a period of 25 seconds, but dynamic pressure was recorded for a period of 70 seconds. The results showed that there is a good agreement between the numerical and the physical models. So, it can be concluded that the proposed CFD model is very suitable for use in simulating and analysing the design of hydraulic structures.

이 연구에서 수치 모델링은 두 가지 다른 모델과 다양한 유속을 사용하여 스키밍 흐름 영역에서 계단식 배수로에 대한 유동 특성 (공기 혼입, 속도 분포 및 동적 압력)에 대한 급격한 경사 변화의 영향을 조사하기 위해 시도되었습니다. CFD 기술. 수치 모델을 검증하여 Ostad Mirza (2016)의 실험 결과와 비교 하였다. 오차를 최대한 줄이기 위해 실험 모형과 동일한 수치 모형을 입력 하였다.

Flow-3D는 파티클을 다루는 잘 모델링 된 도구입니다. 이 연구에서 모델은 실험 결과를 통해 결과를 관찰하여 공기 혼입 입자를 잘 처리합니다. 그리고 수치와 실험 결과의 차이가 작은 이유는 프로그램이 실험실보다 입자를 더 정확하게 다루기 때문입니다. 일반적으로 수치 및 실험 결과는 경사에 가까워지면 유동 벌킹, 공기 혼입, 속도 분포 및 동적 압력이 계단의 급격한 경사 변화에 크게 영향을받는 것으로 나타났습니다. 사면 변화의 정도는 상대적으로 작았지만 사면 변화의 영향은 유동 특성에 큰 영향을 미쳤다.

Renormalized Group (RNG) 모델이 난류 솔버로 선택되었습니다. 3D 모델링의 경우 계산 영역으로 직교 메쉬가 사용되었으며 X, Y, Z 방향에 사용 된 메쉬 그리드 크기는 0.015m입니다. CFD 모델링에서 공기 농도와 속도 분포는 25 초 동안 기록되었지만 동적 압력은 70 초 동안 기록되었습니다. 결과는 수치 모델과 물리적 모델간에 좋은 일치가 있음을 보여줍니다. 따라서 제안 된 CFD 모델은 수력 구조물의 설계 시뮬레이션 및 해석에 매우 적합하다는 결론을 내릴 수 있습니다.

DATA AVAILABILITY STATEMENT

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All relevant data are included in the paper or its Supplementary Information.

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© 2021 The Authors
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).

Figure 1. Experimental flume used (a) Side view of the flume; (b) Pool detail.

Modelling of Pool-Type Fishways Flows: Efficiency and Scale Effects Assessment

by Ana L. Quaresma *OrcID andAntónio N. PinheiroOrcID
CERIS—Civil Engineering for Research and Innovation for Sustainability, Instituto Superior Técnico (IST), Universidade de Lisboa, 1049-001 Lisboa, Portugal*
Author to whom correspondence should be addressed.
Academic Editor: Bommanna Krishnappan
Water 2021, 13(6), 851; https://doi.org/10.3390/w13060851
Received: 16 January 2021 / Revised: 8 March 2021 / Accepted: 18 March 2021 / Published: 20 March 2021
(This article belongs to the Special Issue Ecohydraulics of Pool-Type Fishways)

Abstract

이 연구에서는 전산 유체 역학 (CFD) 소프트웨어 (FLOW-3D®)를 사용하여 바닥 오리피스가 있는 풀형 어로에서 흐름의 3D 수치 모델링을 수행했습니다. 수치 결과는 음향 도플러 속도계 (ADV) 및 입자 이미지 속도계 (PIV) 측정에서 얻은 실험 데이터와 비교되었습니다.

흐름 깊이, 흐름 패턴, 수속, 난류 운동 에너지, Reynolds 수직 응력 및 바닥 구성 요소에 평행한 Reynolds 전단 응력과 같이 어로 효율에 영향을 미치는 여러 유체 역학적 변수를 정성 및 정량적으로 비교했습니다.

수치 모델은 복잡한 유동장을 정확하게 재현하여 수치 모델 예측과 분석 된 변수에 대한 실험 데이터 사이에 전반적으로 좋은 일치를 보여줍니다. 분석중인 모든 매개 변수에 대한 수치 모델 검증 수행의 중요성이 강조되었습니다.

또한 프로토 타입 어로의 업 스케일 된 수치 모델을 실행하여 스케일링 효과를 분석했습니다. 스케일 효과의 증거없이 실제 모델과 프로토 타입 치수 모두에 대해 유사한 정확도로 모델을 수행했습니다.

현재 연구는 CFD 모델 (즉, FLOW-3D®)이 새로운 수영장 유형 어로 형상을 위한 적절하고 효율적인 설계 및 분석 도구로 사용될 수 있으며 물리적 모델 테스트를 줄이고 보완 할 수 있다고 결론지었습니다.

In this study, the 3D numerical modelling of flow in a pool-type fishway with bottom orifices was performed using computational fluid dynamics (CFD) software (FLOW-3D®). Numerical results were compared with experimental data obtained from acoustic Doppler velocimetry (ADV) and particle image velocimetry (PIV) measurements. Several hydrodynamic variables that influence fishways efficiencies, such as flow depths, flow patterns, water velocity, turbulent kinetic energy, Reynolds normal stresses, and Reynolds shear stress parallel to the bottom component, were qualitatively and quantitatively compared. The numerical model accurately reproduced the complex flow field, showing an overall good agreement between the numerical model predictions and the experimental data for the analysed variables. The importance of performing a numerical model validation for all the parameters under analyses was highlighted. Additionally, scaling effects were analysed by running an upscaled numerical model of the prototype fishway. The model performed with similar accuracy for both physical model and prototype dimensions with no evidence of scale effects. The present study concludes that CFD models (namely FLOW-3D®) may be used as an adequate and efficient design and analysis tool for new pool-type fishways geometries, reducing and complementing physical model testing.Keywords: pool-type fishways3D numerical modellingLESscale effectsflow patternsCFD model assessment

Introduction

강의 종단 연결성을 복원하는 것은 담수 생태계의 회복에있어 여전히 중요한 문제입니다 [1,2]. 잘 설계되고 건설된 경우 어로는 물고기가 댐과 둑을 지나 계속 이동할 수 있는 경로를 제공합니다.

물고기 통과 효율성에 대한 검토에서 Noonan et al. [3]은 기존의 많은 어로의 설계 특성이 어종의 요구를 적절하게 충족시키지 못했지만, 풀형 어로가 모든 어류 그룹에 대해 가장 높은 효율성을 보여 주었다는 것을 발견했습니다.
여러 어종에 적합한 수영 조건을 제공하는 것은 어항의 흐름과 난류 패턴이 성공에 중요한 역할을 하기 때문에 다소 어려운 일입니다 [2,4,5,6,7,8,9,10,11,12].

물리적 모델링은 풀형 유형 어로의 유체 역학을 연구하기 위한 주요 접근 방식이었습니다 (예 : [13,14,15,16,17,18,19,20,21,22]). 그러나 물리적 실험은 비용과 시간이 많이 소요됩니다. 따라서 컴퓨터 기술의 발전으로 인해 물리적 모델 테스트를 줄이기 위해 복잡한 기하학적 구조를 가진 유압 구조의 흐름 패턴을 분석하는 데 전산 유체 역학 (CFD) 3 차원 (3D) 모델이 점점 더 많이 사용되고 있습니다 [23,24].

따라서 이러한 모델은 어로 유체 역학 연구 및 효율적인 어로 설계에 필수적인 역할을 할 수 있습니다.
어로에 대한 수치 모델링 연구는 주로 수직 슬롯 어로에 초점을 맞추고 있습니다 [12,25,26,27,28,29,30,31,32,33,34,35,36,37]. 수영장의 주요 부분에서 수직 슬롯 어로 흐름은 거의 2 차원 (2D)이고 수직 속도 구성 요소가 수평 요소 [26]보다 훨씬 작기 때문에 이러한 연구의 대부분은 2D 모델을 사용했습니다.

바닥 오리피스가있는 수영장 유형 어로에서는 흐름이 매우 복잡하고 3D이므로 정확한 유동장 특성화를 얻기 위해 3D 모델을 사용해야합니다. 이 어로 구성을 모델링하는 것은 높은 속도 구배, 높은 와도 및 높은 전단 영역을 포함하기 때문에 다소 어렵습니다.

이 연구에서는 FLOW-3D® (Flow Science, Inc., Santa Fe, NM, USA)를 사용하여 바닥 오리피스가 있는 수영장 유형 어로의 3D 수치 시뮬레이션을 수행하여 흐름 깊이, 속도 및 난류 패턴을 예측하는 능력을 평가했습니다. .

최근 몇 년 동안 실내에 가까운 프로토 타입 수영장 형 어로가 사이프 린드 종의 행동과 움직임을 연구하는데 사용되었습니다 [1,7,8,11,38,39,40,41,42,43]. Silva et al. [38]은 노치, 급락 및 스트리밍에 대한 두 가지 다른 유동 체제와 관련하여 조정 가능한 치수를 가진 침수된 오리피스와 표면 노치의 동시 존재에 대한 Iberian barbel Luciobarbus bocagei (Steindachner, 1864)의 반응을 평가했습니다.

이 연구의 결과는 이베리아 바벨이 어로를 협상하기 위해 오리피스 (76 %)를 선호했으며 어로에 들어가는 데 걸리는 시간도 오리피스에 비해 훨씬 적다는 것을 보여주었습니다.

Silva et al. [39] 오프셋 및 직선 오리피스가있는 수영장 유형 어로의 이베리아 바벨에 대한 적합성을 테스트했습니다. 이 연구는 오프셋 구성이 직선 오리피스 레이아웃 (28 %)에 비해 물고기 통과 성공률 (68 %)이 훨씬 더 높음을 발견했습니다. 어로를 성공적으로 협상하는 데 걸리는 시간도 오프셋 구성, 특히 작은 성인의 경우 훨씬 더 낮았습니다.

이 연구에서는 유속과 난류 매개 변수가 물고기 수영 성능에 미치는 영향을 분석했습니다. 수영장의 유동장을 특성화하기 위해 음향 도플러 속도계가 사용되었습니다.

이 연구의 결과에 따르면 레이놀즈 전단 응력은 어로 내 이베리아 미늘의 움직임에 가장 큰 영향을 미치는 매개 변수임이 입증되었습니다. Branco et al. [40] 두 가지 다른 흐름을 가진 오리피스와 노치가 있는 풀형 유형 어로에서 형태 학적 및 생태학적 특성이 다른 두 종, 바닥 지향 이베리아 바벨 Luciobarbus bocagei 및 물기둥 수영 자 Iberian chub Squalius pyrenaicus의 거동과 성능을 평가했습니다.

풀의 유체 역학을 특성화하기 위해 음향 도플러 속도계가 사용되었습니다. 결과는 두 종 모두 흐름 흐름이있는 노치를 선호했으며 이 흐름 체제로 상류로 이동하는데 더 성공적이었습니다.
이 연구에서는 이 시설의 1 : 2.5 스케일 어로 모델을 사용하여 Silva et al.에 의해 테스트된 바닥 오리피스 구성이 있는 풀형 유형 어로의 속도와 난류를 측정했습니다.

[7,38] 효과가 입증된 바벨 사용. 2D 입자 이미지 속도계 (PIV) 시스템 및 음향 도플러 속도계 (ADV)를 사용하여 순간 속도의 광범위한 측정을 수행하고, 후 처리하고, 수치 모델 정확도를 평가하는 데 사용했습니다.

Haque et al. [44] 대부분의 경우 수치 모델의 검증에 사용할 수있는 실험 데이터 세트에 높은 측정 오류가 있고 / 또는 측정 메시가 너무 거칠어 서 이들의 예측 기능을 올바르게 평가할 수없는 문제를 언급했습니다.

모델. Blocken과 Gualtieri [23]는 검증 및 검증 연구가 필수적이며 CFD 연구를 검증하기위한 데이터를 제공하기 위해 고품질 실험이 필요하다고 언급합니다.

Fuentes-Pérez et al. [35]는 특히 난류 메트릭에 대한 어로 연구에서 수치 모델 검증 데이터를 찾는 데 어려움을 언급합니다. 두 가지 측정 기술을 사용하고 상당한 양의 실험 데이터를 얻었기 때문에 이 연구에서는 이러한 문제를 극복했습니다.

물리적 모델은 종종 Froude 수 유사성을 기반으로하며, 두 유사성 법칙을 모두 충족하는 데 어려움이있어 무시되는 레이놀즈 수 유사성입니다. 프로토 타입 레이놀즈 수가 일반적으로 훨씬 더 크기 때문에 레이놀즈 수 관련 스케일 효과가 도입될 수 있습니다.

레이놀즈 수 증가는 속도 분포와 경계층 속성에 영향을 미칠 수 있습니다 [45]. 척도 효과를 평가하기 위해 수치 시뮬레이션을 사용할 수 있습니다 [46,47]. 따라서 본 연구에서는 바닥 오리피스 흐름이있는 풀형어도에 대한 스케일 효과를 분석하기 위해 두 가지 크기의 수치 모델을 개발했습니다.

프로토 타입 치수의 대형 모델과 물리적 모델 치수의 스케일 된 소형 모델입니다. .
바닥 오리피스가있는 수영장 형 어로의 유동장은 수직 슬롯 어로 (VSF)의 유동장보다 매우 3 차원 적이며 훨씬 더 복잡합니다. 이는 어로 수치 모델 검증에 대한 이전 연구에서 더 자주 고려 된 설계입니다 [26, 27,28,29,35].

저자가 아는 한, 이것은 바닥 오리피스가있는 풀형 어로에 대한 최초의 CFD 연구이며, 여기에는 실험 속도 데이터와 풀형 어로에 대한 3 차원 수치 모델링 결과 간의 가장 광범위한 비교도 포함됩니다. 두 가지 다른 측정 기술 (PIV 및 ADV)이 사용되어 자세한 비교가 가능하고 이러한 유형의 유동장에 대한 CFD 시뮬레이션 결과에 대한 확신을 제공합니다.

이 연구는 다른 어로 유형의 이전 수치 모델 연구에서 제시되지 않았던 난류 매개 변수를 포함하여 수치 모델 결과와 측정 간의 일치에 대한 통계적 테스트를 통해 정성적 비교 뿐만 아니라 상세한 정량적 비교도 제공합니다. 스케일 효과도 다룹니다.

따라서 이 연구는 전 세계적으로 가장 많이 사용되는 풀 유형 어로의 CFD 모델 검증을 원활하게 할 것이며 [10] 설계자들의 사용을 장려 할 것입니다.
또한 새로운 풀 유형 어로 형상을 위한 설계 도구로 CFD 모델 (즉, FLOW 3D®)을 사용하는 방법에 대해 설명합니다.

Figure 1. Experimental flume used (a) Side view of the flume; (b) Pool detail.
Figure 1. Experimental flume used (a) Side view of the flume; (b) Pool detail.
Figure 2. Three dimensional representations of a pool showing the measurement planes and the acoustic Doppler velocimetry (ADV) measurement grid (a) measurement planes parallel to the flume bottom; (b) vertical measurement planes (ADV measurement grid is only shown in one plane).
Figure 2. Three dimensional representations of a pool showing the measurement planes and the acoustic Doppler velocimetry (ADV) measurement grid (a) measurement planes parallel to the flume bottom; (b) vertical measurement planes (ADV measurement grid is only shown in one plane).
Figure 3. Computational domain, showing Pool 3 mesh block.
Figure 3. Computational domain, showing Pool 3 mesh block.
Figure 4. Streamlines of time-averaged velocities (left: PIV; right: mesh Amodel): (a,b) plane 2 (z = 0.088 m); (c,d) plane 5 (y = 0.20 m).
Figure 4. Streamlines of time-averaged velocities (left: PIV; right: mesh Amodel): (a,b) plane 2 (z = 0.088 m); (c,d) plane 5 (y = 0.20 m).
Figure 5. Longitudinal variation of velocity components: (a,c,e) planes 1 and 6 intersection (y = 0.36 m and z = 0.04 m); (b,d,f) planes 2 and 5 intersection (y = 0.20 m and z = 0.088 m).
Figure 5. Longitudinal variation of velocity components: (a,c,e) planes 1 and 6 intersection (y = 0.36 m and z = 0.04 m); (b,d,f) planes 2 and 5 intersection (y = 0.20 m and z = 0.088 m).
Figure 6. Longitudinal variation of Reynolds normal stress components and Reynolds shear stress parallel to the bottom component: (a,c,e,g) planes 1 and 6 intersection (y = 0.36 m and z = 0.04m); (b,d,f,h) planes 2 and 5 intersection (y = 0.20 m and z = 0.088 m).
Figure 6. Longitudinal variation of Reynolds normal stress components and Reynolds shear stress parallel to the bottom component: (a,c,e,g) planes 1 and 6 intersection (y = 0.36 m and z = 0.04m); (b,d,f,h) planes 2 and 5 intersection (y = 0.20 m and z = 0.088 m).

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Figure 5. Flow pattern of operating condition 1: (a) Physical model flow diagram; (b) Simulation model flow.

Numerical Study of Fluctuating Pressure on Stilling Basin Slab with Sudden Lateral Enlargement and Bottom Drop

급격한 측면 확대 및 바닥 낙하에 따른 정류지(stilling basin) 슬래브의 변동 압력에 대한 수치 연구

by Yangliang Lu,Jinbu Yin *OrcID,Zhou Yang,Kebang Wei andZhiming Liu
College of Water Resources and Architectural Engineering, Northwest A&F University, Weihui Road, Yangling 712100, China*
Author to whom correspondence should be addressed.
Water 2021, 13(2), 238; https://doi.org/10.3390/w13020238
Received: 6 November 2020 / Revised: 7 January 2021 / Accepted: 11 January 2021 / Published: 19 January 2021
(This article belongs to the Special Issue Physical Modelling in Hydraulics Engineering)

Abstract

갑작스런 확장 및 바닥 낙하가 있는 고요한 정류지(stilling basin) 유역은 복잡한 수력 특성, 특히 3D 공간 수력 점프 아래에서 변동하는 압력 분포로 이어집니다.

이 논문은 FLOW-3D 소프트웨어를 기반으로 한 LES (Large Eddy Simulation) 모델과 TruVOF 방법을 사용하여 시간 평균 압력, 변동 압력의 RMS (Root Mean Square), 정물(stilling basin) 조 슬래브의 최대 및 최소 압력을 시뮬레이션했습니다.

실제 모델 결과와 비교하여 시뮬레이션 결과는 LES 모델이 정물 유역의 변동하는 수류 압력을 안정적으로 시뮬레이션 할 수 있음을 보여줍니다. 변동 압력의 RMS의 최대 값은 정수조 전면과 측벽의 연장선 부근에 나타납니다.

이 논문은 변동 압력의 생성 메커니즘과 Navier-Stokes 방정식에서 파생된 Poisson 방정식을 기반으로 영향 요인 (변동 속도, 속도 구배, 변동 와도)의 정량 분석과 특성의 정성 분석을 결합하는 연구 방법을 제공합니다.

변동하는 압력의. 정류 지의 소용돌이 영역과 벽에 부착 된 제트 영역의 변동 압력 분포는 주로 각각 와류 및 변동 유속의 영향을 받으며 충돌 영역의 분포는 변동 속도, 속도 구배 및 변동에 의해 발생합니다.

A stilling basin with sudden enlargement and bottom drop leads to complicated hydraulic characteristics, especially a fluctuating pressure distribution beneath 3D spatial hydraulic jumps. This paper used the large eddy simulation (LES) model and the TruVOF method based on FLOW-3D software to simulate the time-average pressure, root mean square (RMS) of fluctuating pressure, maximum and minimum pressure of a stilling basin slab. Compared with physical model results, the simulation results show that the LES model can simulate the fluctuating water flow pressure in a stilling basin reliably. The maximum value of RMS of fluctuating pressure appears in the vicinity of the front of the stilling basin and the extension line of the side wall. Based on the generating mechanism of fluctuating pressure and the Poisson Equation derived from the Navier–Stokes Equation, this paper provides a research method of combining quantitative analysis of influencing factors (fluctuating velocity, velocity gradient, and fluctuating vorticity) and qualitative analysis of the characteristics of fluctuating pressure. The distribution of fluctuating pressure in the swirling zone of the stilling basin and the wall-attached jet zone is mainly affected by the vortex and fluctuating flow velocity, respectively, and the distribution in the impinging zone is caused by fluctuating velocity, velocity gradient and fluctuating vorticity. 

Keywords: submerged jumpsudden lateral enlargement and bottom droplarge eddy simulationvortexfluctuating pressure

Figure 1. Schematic design of model test: (a) Sectional view; (b) Plan view.
Figure 1. Schematic design of model test: (a) Sectional view; (b) Plan view.
Figure 2. Model layout in laboratory: (a) Discharge chute; (b) The stilling basin.
Figure 2. Model layout in laboratory: (a) Discharge chute; (b) The stilling basin.

Table 1. Operating conditions.

ConditionFlow Discharge
(m3/s)
Inflow Froude NumberInflow Velocity (m/s)Inflow Water Depth (m)
10.9425.2955.6110.114
20.6434.5454.4890.097
30.2324.2273.0180.052
Figure 3. Schematic diagram of fluctuating pressure data-processing process.
Figure 3. Schematic diagram of fluctuating pressure data-processing process.
Figure 4. 3D simulation model: (a) Boundary conditions; (b) Grid mesh.
Figure 4. 3D simulation model: (a) Boundary conditions; (b) Grid mesh.

Table 2. Grid independence test.

GridContaining Block Cell Size (m)Nested Block Cell Size (m)Discharge
(m3/s)
Relative Error (%)
10.0500.0250.9905.10
20.0400.0200.9692.70
30.0300.0150.9561.49
40.0200.0100.9521.06
Figure 5. Flow pattern of operating condition 1: (a) Physical model flow diagram; (b) Simulation model flow.
Figure 5. Flow pattern of operating condition 1: (a) Physical model flow diagram; (b) Simulation model flow.
Figure 6. Numerical simulation of water surface profile and x-z plane flow rate vector.
Figure 6. Numerical simulation of water surface profile and x-z plane flow rate vector.
Figure 7. Comparison of bottom velocity.
Figure 7. Comparison of bottom velocity.
Figure 8. Comparison of pressure at 10 pressure measurement points: (a) Comparison of root mean square (RMS) of fluctuating and time-average pressure; (b) Comparison of maximum and minimum pressure.
Figure 8. Comparison of pressure at 10 pressure measurement points: (a) Comparison of root mean square (RMS) of fluctuating and time-average pressure; (b) Comparison of maximum and minimum pressure.
Figure 9. The distribution diagram of time-average pressure and RMS of fluctuating pressure of bottom of stilling basin under three cases.
Figure 9. The distribution diagram of time-average pressure and RMS of fluctuating pressure of bottom of stilling basin under three cases.
Figure 10. Speed vector in stilling basin at z = 40 cm horizontal plane and bottom plate plane in three cases.
Figure 10. Speed vector in stilling basin at z = 40 cm horizontal plane and bottom plate plane in three cases.
Figure 11. Distribution of fluctuating velocity and vorticity in the horizontal section of the stilling basin slab: (a) Distribution of fluctuating velocity; (b) Distribution of fluctuating vorticity.
Figure 11. Distribution of fluctuating velocity and vorticity in the horizontal section of the stilling basin slab: (a) Distribution of fluctuating velocity; (b) Distribution of fluctuating vorticity.
Figure 12. Distribution of root time-average square fluctuating pressure of x = 50 cm cross-section of bottom plate: (a) Distributions of fluctuating velocity and fluctuating pressure; (b) Distributions of fluctuating vorticity and fluctuating pressure.
Figure 12. Distribution of root time-average square fluctuating pressure of x = 50 cm cross-section of bottom plate: (a) Distributions of fluctuating velocity and fluctuating pressure; (b) Distributions of fluctuating vorticity and fluctuating pressure.
Figure 13. Variance of fluctuating pressure coefficient (Cp′).
Figure 13. Variance of fluctuating pressure coefficient (Cp′).

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ANSI/HI 9.8 Pump Intake Design

Hydraulic Jump in a Trench Type Pump Sump

트렌치 형 펌프 배수 조의 유압 점프

이 기사는 Ibis Group의 대표인 Steve Saunders가 기고했습니다.

유압 점프는 개방형 채널 애플리케이션으로 작업하는 사람들에게 친숙한 흐름 현상입니다. Wikipedia는 수력 점프를 “개방형 채널 흐름이 초-임계에서 아임계로 갑자기 변환되는 조건”으로 정의합니다. 점프가 발생하는 위치에서 속도 헤드가 수면 상승으로 거래되는 것을 관찰 할 수 있습니다. 방수로와 같은 흐름 제어 응용 분야에서 수압 점프는 침식을 완화하기 위해 에너지를 소산하는 수단으로 의도적으로 설정됩니다. 또한 레크리에이션 목적으로 사용됩니다. 유압 점프로 생성된 정상 파도는 어떤 바다에서든 수천 마일 떨어진 서핑 공원에서 타는 방법을 서퍼를 훈련시키는데 사용됩니다. 유압 점프의 새로운 응용 분야는 점프의 에너지 전달이 다시 중단되고 정상적인 펌핑 작업 중에 침전된 고형물을 제거하는 자가 세척 트렌치 유형 펌프 섬프(sump)입니다.

트렌치 유형 집수 펌프 시뮬레이션
FLOW-3D는 유압 점프 시뮬레이션에서 신뢰할 수 있는 도구로 입증되었으며 자가 세척 트렌치 유형 펌프 섬프의 설계 및 시연에 사용되었습니다. 트렌치 형 펌프 섬프는 펌프 흡입 라인이 있는 좁은 채널로 구성됩니다. 일반적인 응용 분야는 들어오는 물에서 모래와 자갈을 걸러내는 입구 스크린이 없는 빗물 수집입니다. 아래 회로도에 예가 나와 있습니다.

ANSI/HI 9.8 Pump Intake Design
ANSI/HI 9.8 Pump Intake Design

이 수치는 ANSI / HI 9.8 펌프 흡기 설계 매뉴얼에서 발췌한 것이며 4 개의 펌프가 설치된 섬프의 평면도 및 입면도를 보여줍니다. 유입 암거, 웅덩이 바닥 및 펌프 흡입 바닥을 벗어난 높이의 배열은 이 설계 유형의 자체 청소 기능에 매우 중요합니다. 유입 암거는 최소 작동 웅덩이 수위보다 높은 고도에 있습니다. 또한 유입단의 ​​트렌치 벽은 Ogee 모양입니다. 마지막으로, 트렌치의 맨 끝에 있는 펌프 흡입 벨은 상류 펌프의 절반 높이에 설정됩니다.

Designing for Storm Events

폭풍이 닥친 후 모래와 자갈이 웅덩이 바닥에 쌓입니다. 그들은 점진적인 유압 점프를 통해 다시 매달리고 빠져 나갑니다. 청소 주기 동안 물은 유입 암거를 통해 유입되는 것보다 더 빠른 속도로 트렌치의 맨 끝에 있는 하부 펌프에 의해 배출됩니다.

이 시퀀스 동안 유압 점프는 두 가지 중요한 역할을 수행합니다. 점프 업스트림의 초임계 부분은 섬프 바닥의 모래와 자갈을 휘감아 펌핑이 되도록 다시 일시 중단합니다. 애니메이션의 색상 스케일을 보면 ogee 바닥의 수색 속도가 약 9ft/sec에 가깝다는 것을 알 수 있습니다. 한편, 점프 하류의 계단식 수면 상승은 하단 펌프에 충분한 잠수를 제공하여 섬프가 펌핑 될 때까지 계속 작동합니다.

물이 최소 정상 작동 수준 아래로 떨어지면 유입이 Ogee 모양의 벽 아래로 가속되어 궁극적으로 초임계가됩니다. 섬프의 수위가 바닥에 가까워지면 수압 점프가 형성되고 하단 원단 펌프가 흡입력을 잃을 때까지 섬프를 따라 진행됩니다. 아래 애니메이션에서 이런 일이 일어나는 것을 관찰 할 수 있습니다.

The Magnolia Storm Water Pumping Station

이 자체 세척 섬프 응용 분야에 FLOW-3D를 사용하면 트렌치 형상을 쉽게 조정하여 유압 점프 동작을 최적화 할 수 있습니다. 텍사스 엘파소에있는 Magnolia Storm Water Pumping Station은 FLOW-3D가 설계 및 평가 도구로 사용 된 예입니다. 2016 년에 시운전 된 Magnolia Storm Water Pumping Station은 폭우시 고속도로 10 번의 홍수를 방지하기 위해 건설되었습니다.

Magnolia 스테이션은자가 세척 트렌치 유형 섬프에 3 개의 대형 수직 터빈 펌프로 구성됩니다. 섬프 설계 과정에서 FLOW-3D를 사용하여 몇 가지 기하학적 변형을 평가하여 자체 세척 기능을 통해 펌프 작동 효율성 및 유지 보수 용이성에 이상적인 구성에 도달했습니다.

수자원/수처리/환경분야

수자원 분야

Water & Environmental

FLOW-3D는 작은 하수 처리 시스템부터 대형 수력 발전 프로젝트까지 수처리 및 환경 산업에 직면한 광범위한 문제를 해결할 수 있는 뛰어난 CFD 소프트웨어 입니다. FLOW-3D는 시뮬레이션의 복잡성을 감소시키고 최적의 솔루션에 대해 노력을 집중할 수 있도록 해줍니다. 이를 통해 통해 파악된 가치 있는 통찰력은 귀하의 상당한 시간과 비용을 절약 할 수 있습니다.

실제 지형을 적용하여 3차원 shallow water hybrid model을 이용한 댐 붕괴 시뮬레이션

FLOW-3D는 자유표면 흐름이 있는 수치해석 알고리듬에 의해 유동의 표면이 시공간적으로 변하는 모사를 위한 이상적인 도구라고 할 수 있습니다. 자유 표면은 물과 공기 같은 높은 비율의 밀도 변화를 가지는 유체들 사이의 특정한 경계를 일컫습니다. 자유 표면 흐름을 모델링하는 것은 일반적인 유동방정식과 난류 모델이 결합된 고급 알고리즘을 필요로 합니다. 이 기능은 FLOW-3D로 하여금 침수 구조에 의해 형성된 방수, 수력 점프 및 수면 변화의 흐름의 궤적을 포착 할 수 있습니다.


Bibliography & Technical Data

Flood

Study of a Tailings Dam Failure Pattern and Post-Failure Effects under Flooding Conditions

폐석댐 붕괴 패턴 및 홍수 조건에서의 붕괴 후 영향 연구 Zhong Gao, Jinpeng Liu, Wen He, Bokai Lu, Manman Wang, ...
F-BW

Determination of Formulae for the Hydrodynamic Performance of a Fixed Box-Type Free Surface Breakwater in the Intermediate Water

중간 수심에서 고정된 박스형 자유 수면 방파제의 유체역학적 성능 공식을 결정하기 위한 연구 Guoxu Niu, Yaoyong Chen, Jiao Lu, Jing ...
Wave

Three-Dimensional Simulations of Subaerial Landslide-Generated Waves: Comparing OpenFOAM and FLOW-3D HYDRO Models

지표 산사태로 발생한 파랑의 3차원 시뮬레이션: OpenFOAM과 FLOW-3D HYDRO 모델 비교 Ramtin Sabeti, Mohammad Heidarzadeh, Alessandro Romano, Gabriel Barajas Ojeda ...
Weir

Discharge Formula and Hydraulics of Rectangular Side Weirs in the Small Channel and Field Inlet

소규모 수로 및 유입구에서의 직사각형 측면 위어의 유량 공식 및 수리학 Yingying Wang, Mouchao Lv, Wen’e Wang, Ming Meng Abstract ...

Three-dimensional flow structure in a confluence-bifurcation unit

합류 분기 유닛의 3차원 유동 구조 Di Wang, Xiaoyong Cheng, Zhixuan Cao, Jinyun Deng Abstract Enhanced understanding of flow structure ...
The Fastest Laptops for 2024

FLOW-3D 수치해석용 노트북 선택 가이드

2024년 가장 빠른 노트북 PCMag이 테스트하는 방법 소개 : 기사 원본 출처: https://www.pcmag.com/picks/the-fastest-laptops CFD를 수행하기 위한 노트북 선정 기준은 별도로 ...

Propagation Velocity of Excitation Waves Caused by Turbidity Currents

혼탁류에 의한 자극파의 전파 속도 Guohui Xu, Shiqing Sun, Yupeng Ren, Meng Li, Zhiyuan Chen Abstract Turbidity currents are important ...
Nozzle Scour

Study on the Sand-Scouring Characteristics of Pulsed Submerged Jets Based on Experiments and Numerical Methods

실험과 수치 해석을 기반으로 한 펄스 잠수 제트의 모래 침식 특성 연구 Hongliang Wang, Xuanwen Jia,Chuan Wang, Bo Hu, Weidong ...
USBR baffle block

Numerical investigation of hydraulic jumps with USBR and wedge-shaped baffle block basins for lower tailwater

하부 테일워터를 위한 USBR 및 쐐기형 배플 블록 분지를 사용한 유압 점프의 수치적 조사 Muhammad Waqas Zaffar; Ishtiaq Hassan; Zulfiqar ...
Overflow water film

Numerical Simulation Study on Characteristics of Airtight Water Film with Flow Deflectors

유동 편향기가 있는 밀폐수막의 특성에 관한 수치해석 연구 Zhang Weikang, Gong Hongwei Abstract In practical use, there is shrinkage in ...


FLOW-3D Water & Environmental Brochure (FSI) Bibliography

Models

  • Air Entrainment
  • Hybrid Shallow Water/3D Flow
  • Sediment Scour
  • Turbulence
  • More Modeling Capabilities

Case Studies

  • Evaluating Hydraulic Energy Losses and Total Hydraulic Head with FLOW-3D‘s Flux Baffles
  • Modeling Commercial Aquaculture Systems
  • Modeling Local Bridge Scour during Flood Event

Conference Proceedings

Design of a Sewer Transition

Design of a Sewer Transition | 하수도 전환 설계

This article was contributed by Daniel Valero, Rafael García-Bartual, Ignacio Andrés and Francisco Valles of the Polytechnic University of Valencia.

2010 년 12 월, 새로운 고속 열차 MADRID-VALENCIA (스페인)가 개통되었습니다. 건설 전에 극복해야 할 많은 기술적 문제 중 하나는 터널로 구성된 도심의 철도 입구로 발렌시아의 주요 남쪽 하수도를 벗어나게 했습니다. 이탈 도달 범위는 길이가 143 미터이며 아래에 자세히 설명된 복잡한 유압 설계를 포함하여 기존 경사와 관련하여 경사 및 단면의 중요한 변경을 포함합니다. 유압 성능은 FLOW-3D를 사용한 수치 시뮬레이션과   발렌시아 폴리 테크닉 대학교의 유압 실험실에서 물리적 모델을 통해 확인되었습니다. 최대 용량 100 m 3 / s에 대한 테스트가 수행되었습니다 .

The Sewer                          

그림 1은 하수도 기하학 설계의 주요 특징을 보여줍니다. 여기에는 철도 터널을 건넌 직후에 위치한 표준 WES 프로파일이 포함됩니다. 이 위어는 높은 유속으로 초 임계 흐름을 강제합니다. 하류에서 바람직하지 않은 흐름 조건이 설정되는 것을 방지하기 위해 둑 바로 하류에 정류 조를 설계했습니다. 이러한 장치는 연결 하류 하수도에서 높은 에너지 손실 및 임계 이하의 흐름 조건을 수반하는 유압 점프를 강제합니다. 서로 다른 배출 조건에서 흐름의 거동을 보장하기 위해 채널에 두 개의 세로 줄의 삼각형 블록이 포함되었으며, 이는 정수 조 길이에서 유압 점프를 국지화하기 위해 에너지 소산 기 역할을했습니다. 그 계단의 길이에서 수압 점프. 새로운 변형 채널과 기존 도달 지점(upstream and downstream)사이는 기하학적 요소로 부드럽게 연결합니다.(그림 2).

Figure 1. Geometry of the sewer

Figure 2. Reach 2 of the sewer

FLOW-3D Simulations

문제의 정확한 해결을 위해 계산 리소스를 최적화하기 위해 하수도를 여러 개의 중첩 된 범위로 분할하여 수력 솔루션의 연속성을 보장하고 고려 된 각 도달 범위에서 더 미세한 메시를 사용할 수 있습니다. 가장 복잡한 흐름이 정수 조에서 발생하기 때문에 이러한 도달 범위는 윤곽선과 바닥 블록에서 중앙 흐름 영역까지 점진적으로 다양한 셀 크기로 가장 높은 해상도 (6.000.000 셀)로 해결되었습니다. 유압 점프 시뮬레이션에 대한 비디오는 이 기사의 끝에 있습니다.

Figure 3. Velocity magnitude distribution

Figure 4. Turbulent kinetic energy distribution.

Figure 5. Air entrained prediction with turbulent air entrainment model

ke RNG 난류 모델이 선택되었으며, 이류에 대한 명시적인 2 차 단 조성 보존 체계가 있습니다. 자유 표면 표현에는 Split Lagrangian 방법이 사용되었습니다. 정상 상태 솔루션 이전의 과도 흐름은 더 거친 메쉬로 시뮬레이션되었습니다. 그림 3과 4는 수치 시뮬레이션의 관련 결과를 보여줍니다. 또한 수력 점프의 수치 시뮬레이션을 보여주는 비디오 가이드 기술 노트에 첨부되어 있습니다.

유압 점프에서 발생하는 공기 혼입, 특히 난류와 자유 표면 간의 상호 작용을 설명하기 위해 추가 시뮬레이션이 수행되었습니다. 그림 5는 가변 밀도 옵션을 선택하고 기본 계수 C air  = 0.5를 사용하는 FLOW-3D 의 공기 혼입 모델을 사용한 결과를 보여줍니다.

Comparison with the Physical Model

발렌시아 Polytechnic University의 수압 실험실에 실물 모형을 구축하였습니다. 모형에 사용된 척도는 1/20이었습니다. 그림 6은 weir 상단 바로 위에 있는 임계 단면의 프로파일을 보여 줍니다. 발견된 평균 깊이의 오차는 1.3% 였습니다. 유동의 다른 구조적 특성은 FLOW-3D에 의해 적절하게 재현되었다. 예를 들어, 예를 들어, 하수도가 만곡된 범위에 따른 자유 표면의 형상과 Weir의 상류로의 흐르는 자유 표면의 현상입니다.

Figure 6. Relative error at the critical section. Comparison between FLOW-3D, physical model, and HEC-RAS (US Army Corps of Engineers).

Conclusions

실험실 결과와 FLOW-3D시뮬레이션 간의 약간의 차이가 확인되지만 연구 결과는 매우 만족스럽습니다. 아래 동영상을 통해 실험 및 수치해석 결과를 비교해 보시길 바랍니다.

FLOW-3D는 가능한 많은 형상 또는 유압 설계를 테스트할 때 실험실의 실험 횟수를 줄일 수 있습니다. 또한 FLOW-3D의 파일이 속도, 와도, 난류 등과 같은 관련 분야의 상세한 시공간 분포를 제공하므로 최종 설계와 관련하여 실험실에서 수행 된 결과와 측정을 확장하는 데 도움이 될 수 있습니다. 결합된 기술은 연구에서 언급한 것과 같은 유압 기반시설의 설계, 검증 및 최적화를 위한 강력한 도구입니다.

FLOW-3D CAST Bibliography

FLOW-3D CAST bibliography

아래는 FSI의 금속 주조 참고 문헌에 수록된 기술 논문 모음입니다. 이 모든 논문에는 FLOW-3D CAST 해석 결과가 수록되어 있습니다. FLOW-3D CAST를 사용하여 금속 주조 산업의 응용 프로그램을 성공적으로 시뮬레이션하는 방법에 대해 자세히 알아보십시오.

Below is a collection of technical papers in our Metal Casting Bibliography. All of these papers feature FLOW-3D CAST results. Learn more about how FLOW-3D CAST can be used to successfully simulate applications for the Metal Casting Industry.

33-20     Eric Riedel, Martin Liepe Stefan Scharf, Simulation of ultrasonic induced cavitation and acoustic streaming in liquid and solidifying aluminum, Metals, 10.4; 476, 2020. doi.org/10.3390/met10040476

20-20   Wu Yue, Li Zhuo and Lu Rong, Simulation and visual tester verification of solid propellant slurry vacuum plate casting, Propellants, Explosives, Pyrotechnics, 2020. doi.org/10.1002/prep.201900411

17-20   C.A. Jones, M.R. Jolly, A.E.W. Jarfors and M. Irwin, An experimental characterization of thermophysical properties of a porous ceramic shell used in the investment casting process, Supplimental Proceedings, pp. 1095-1105, TMS 2020 149th Annual Meeting and Exhibition, San Diego, CA, February 23-27, 2020. doi.org/10.1007/978-3-030-36296-6_102

12-20   Franz Josef Feikus, Paul Bernsteiner, Ricardo Fernández Gutiérrez and Michal Luszczak , Further development of electric motor housings, MTZ Worldwide, 81, pp. 38-43, 2020. doi.org/10.1007/s38313-019-0176-z

09-20   Mingfan Qi, Yonglin Kang, Yuzhao Xu, Zhumabieke Wulabieke and Jingyuan Li, A novel rheological high pressure die-casting process for preparing large thin-walled Al–Si–Fe–Mg–Sr alloy with high heat conductivity, high plasticity and medium strength, Materials Science and Engineering: A, 776, art. no. 139040, 2020. doi.org/10.1016/j.msea.2020.139040

07-20   Stefan Heugenhauser, Erhard Kaschnitz and Peter Schumacher, Development of an aluminum compound casting process – Experiments and numerical simulations, Journal of Materials Processing Technology, 279, art. no. 116578, 2020. doi.org/10.1016/j.jmatprotec.2019.116578

05-20   Michail Papanikolaou, Emanuele Pagone, Mark Jolly and Konstantinos Salonitis, Numerical simulation and evaluation of Campbell running and gating systems, Metals, 10.1, art. no. 68, 2020. doi.org/10.3390/met10010068

102-19   Ferencz Peti and Gabriela Strnad, The effect of squeeze pin dimension and operational parameters on material homogeneity of aluminium high pressure die cast parts, Acta Marisiensis. Seria Technologica, 16.2, 2019. doi.org/0.2478/amset-2019-0010

94-19   E. Riedel, I. Horn, N. Stein, H. Stein, R. Bahr, and S. Scharf, Ultrasonic treatment: a clean technology that supports sustainability incasting processes, Procedia, 26th CIRP Life Cycle Engineering (LCE) Conference, Indianapolis, Indiana, USA, May 7-9, 2019. 

93-19   Adrian V. Catalina, Liping Xue, Charles A. Monroe, Robin D. Foley, and John A. Griffin, Modeling and Simulation of Microstructure and Mechanical Properties of AlSi- and AlCu-based Alloys, Transactions, 123rd Metalcasting Congress, Atlanta, GA, USA, April 27-30, 2019. 

84-19   Arun Prabhakar, Michail Papanikolaou, Konstantinos Salonitis, and Mark Jolly, Sand casting of sheet lead: numerical simulation of metal flow and solidification, The International Journal of Advanced Manufacturing Technology, pp. 1-13, 2019. doi.org/10.1007/s00170-019-04522-3

72-19   Santosh Reddy Sama, Eric Macdonald, Robert Voigt, and Guha Manogharan, Measurement of metal velocity in sand casting during mold filling, Metals, 9:1079, 2019. doi.org/10.3390/met9101079

71-19   Sebastian Findeisen, Robin Van Der Auwera, Michael Heuser, and Franz-Josef Wöstmann, Gießtechnische Fertigung von E-Motorengehäusen mit interner Kühling (Casting production of electric motor housings with internal cooling), Geisserei, 106, pp. 72-78, 2019 (in German).

58-19     Von Malte Leonhard, Matthias Todte, and Jörg Schäffer, Realistic simulation of the combustion of exothermic feeders, Casting, No. 2, pp. 28-32, 2019. In English and German.

52-19     S. Lakkum and P. Kowitwarangkul, Numerical investigations on the effect of gas flow rate in the gas stirred ladle with dual plugs, International Conference on Materials Research and Innovation (ICMARI), Bangkok, Thailand, December 17-21, 2018. IOP Conference Series: Materials Science and Engineering, Vol. 526, 2019. doi.org/10.1088/1757-899X/526/1/012028

47-19     Bing Zhou, Shuai Lu, Kaile Xu, Chun Xu, and Zhanyong Wang, Microstructure and simulation of semisolid aluminum alloy castings in the process of stirring integrated transfer-heat (SIT) with water cooling, International Journal of Metalcasting, Online edition, pp. 1-13, 2019. doi.org/10.1007/s40962-019-00357-6

31-19     Zihao Yuan, Zhipeng Guo, and S.M. Xiong, Skin layer of A380 aluminium alloy die castings and its blistering during solution treatment, Journal of Materials Science & Technology, Vol. 35, No. 9, pp. 1906-1916, 2019. doi.org/10.1016/j.jmst.2019.05.011

25-19     Stefano Mascetti, Raul Pirovano, and Giulio Timelli, Interazione metallo liquido/stampo: Il fenomeno della metallizzazione, La Metallurgia Italiana, No. 4, pp. 44-50, 2019. In Italian.

20-19     Fu-Yuan Hsu, Campbellology for runner system design, Shape Casting: The Minerals, Metals & Materials Series, pp. 187-199, 2019. doi.org/10.1007/978-3-030-06034-3_19

19-19     Chengcheng Lyu, Michail Papanikolaou, and Mark Jolly, Numerical process modelling and simulation of Campbell running systems designs, Shape Casting: The Minerals, Metals & Materials Series, pp. 53-64, 2019. doi.org/10.1007/978-3-030-06034-3_5

18-19     Adrian V. Catalina, Liping Xue, and Charles Monroe, A solidification model with application to AlSi-based alloys, Shape Casting: The Minerals, Metals & Materials Series, pp. 201-213, 2019. doi.org/10.1007/978-3-030-06034-3_20

17-19     Fu-Yuan Hsu and Yu-Hung Chen, The validation of feeder modeling for ductile iron castings, Shape Casting: The Minerals, Metals & Materials Series, pp. 227-238, 2019. doi.org/10.1007/978-3-030-06034-3_22

04-19   Santosh Reddy Sama, Tony Badamo, Paul Lynch and Guha Manogharan, Novel sprue designs in metal casting via 3D sand-printing, Additive Manufacturing, Vol. 25, pp. 563-578, 2019. doi.org/10.1016/j.addma.2018.12.009

02-19   Jingying Sun, Qichi Le, Li Fu, Jing Bai, Johannes Tretter, Klaus Herbold and Hongwei Huo, Gas entrainment behavior of aluminum alloy engine crankcases during the low-pressure-die-casting-process, Journal of Materials Processing Technology, Vol. 266, pp. 274-282, 2019. doi.org/10.1016/j.jmatprotec.2018.11.016

92-18   Fast, Flexible… More Versatile, Foundry Management Technology, March, 2018. 

82-18   Xu Zhao, Ping Wang, Tao Li, Bo-yu Zhang, Peng Wang, Guan-zhou Wang and Shi-qi Lu, Gating system optimization of high pressure die casting thin-wall AlSi10MnMg longitudinal loadbearing beam based on numerical simulation, China Foundry, Vol. 15, no. 6, pp. 436-442, 2018. doi: 10.1007/s41230-018-8052-z

80-18   Michail Papanikolaou, Emanuele Pagone, Konstantinos Salonitis, Mark Jolly and Charalampos Makatsoris, A computational framework towards energy efficient casting processes, Sustainable Design and Manufacturing 2018: Proceedings of the 5th International Conference on Sustainable Design and Manufacturing (KES-SDM-18), Gold Coast, Australia, June 24-26 2018, SIST 130, pp. 263-276, 2019. doi.org/10.1007/978-3-030-04290-5_27

64-18   Vasilios Fourlakidis, Ilia Belov and Attila Diószegi, Strength prediction for pearlitic lamellar graphite iron: Model validation, Metals, Vol. 8, No. 9, 2018. doi.org/10.3390/met8090684

51-18   Xue-feng Zhu, Bao-yi Yu, Li Zheng, Bo-ning Yu, Qiang Li, Shu-ning Lü and Hao Zhang, Influence of pouring methods on filling process, microstructure and mechanical properties of AZ91 Mg alloy pipe by horizontal centrifugal casting, China Foundry, vol. 15, no. 3, pp.196-202, 2018. doi.org/10.1007/s41230-018-7256-6

47-18   Santosh Reddy Sama, Jiayi Wang and Guha Manogharan, Non-conventional mold design for metal casting using 3D sand-printing, Journal of Manufacturing Processes, vol. 34-B, pp. 765-775, 2018. doi.org/10.1016/j.jmapro.2018.03.049

42-18   M. Koru and O. Serçe, The Effects of Thermal and Dynamical Parameters and Vacuum Application on Porosity in High-Pressure Die Casting of A383 Al-Alloy, International Journal of Metalcasting, pp. 1-17, 2018. doi.org/10.1007/s40962-018-0214-7

41-18   Abhilash Viswanath, S. Savithri, U.T.S. Pillai, Similitude analysis on flow characteristics of water, A356 and AM50 alloys during LPC process, Journal of Materials Processing Technology, vol. 257, pp. 270-277, 2018. doi.org/10.1016/j.jmatprotec.2018.02.031

29-18   Seyboldt, Christoph and Liewald, Mathias, Investigation on thixojoining to produce hybrid components with intermetallic phase, AIP Conference Proceedings, vol. 1960, no. 1, 2018. doi.org/10.1063/1.5034992

28-18   Laura Schomer, Mathias Liewald and Kim Rouven Riedmüller, Simulation of the infiltration process of a ceramic open-pore body with a metal alloy in semi-solid state to design the manufacturing of interpenetrating phase composites, AIP Conference Proceedings, vol. 1960, no. 1, 2018. doi.org/10.1063/1.5034991

41-17   Y. N. Wu et al., Numerical Simulation on Filling Optimization of Copper Rotor for High Efficient Electric Motors in Die Casting Process, Materials Science Forum, Vol. 898, pp. 1163-1170, 2017.

12-17   A.M.  Zarubin and O.A. Zarubina, Controlling the flow rate of melt in gravity die casting of aluminum alloys, Liteynoe Proizvodstvo (Casting Manufacturing), pp 16-20, 6, 2017. In Russian.

10-17   A.Y. Korotchenko, Y.V. Golenkov, M.V. Tverskoy and D.E. Khilkov, Simulation of the Flow of Metal Mixtures in the Mold, Liteynoe Proizvodstvo (Casting Manufacturing), pp 18-22, 5, 2017. In Russian.

08-17   Morteza Morakabian Esfahani, Esmaeil Hajjari, Ali Farzadi and Seyed Reza Alavi Zaree, Prediction of the contact time through modeling of heat transfer and fluid flow in compound casting process of Al/Mg light metals, Journal of Materials Research, © Materials Research Society 2017

04-17   Huihui Liu, Xiongwei He and Peng Guo, Numerical simulation on semi-solid die-casting of magnesium matrix composite based on orthogonal experiment, AIP Conference Proceedings 1829, 020037 (2017); doi.org/10.1063/1.4979769.

100-16  Robert Watson, New numerical techniques to quantify and predict the effect of entrainment defects, applied to high pressure die casting, PhD Thesis: University of Birmingham, 2016.

88-16   M.C. Carter, T. Kauffung, L. Weyenberg and C. Peters, Low Pressure Die Casting Simulation Discovery through Short Shot, Cast Expo & Metal Casting Congress, April 16-19, 2016, Minneapolis, MN, Copyright 2016 American Foundry Society.

61-16   M. Koru and O. Serçe, Experimental and numerical determination of casting mold interfacial heat transfer coefficient in the high pressure die casting of a 360 aluminum alloy, ACTA PHYSICA POLONICA A, Vol. 129 (2016)

59-16   R. Pirovano and S. Mascetti, Tracking of collapsed bubbles during a filling simulation, La Metallurgia Italiana – n. 6 2016

43-16   Kevin Lee, Understanding shell cracking during de-wax process in investment casting, Ph.D Thesis: University of Birmingham, School of Engineering, Department of Chemical Engineering, 2016.

35-16   Konstantinos Salonitis, Mark Jolly, Binxu Zeng, and Hamid Mehrabi, Improvements in energy consumption and environmental impact by novel single shot melting process for casting, Journal of Cleaner Production, doi.org/10.1016/j.jclepro.2016.06.165, Open Access funded by Engineering and Physical Sciences Research Council, June 29, 2016

20-16   Fu-Yuan Hsu, Bifilm Defect Formation in Hydraulic Jump of Liquid Aluminum, Metallurgical and Materials Transactions B, 2016, Band: 47, Heft 3, 1634-1648.

15-16   Mingfan Qia, Yonglin Kanga, Bing Zhoua, Wanneng Liaoa, Guoming Zhua, Yangde Lib,and Weirong Li, A forced convection stirring process for Rheo-HPDC aluminum and magnesium alloys, Journal of Materials Processing Technology 234 (2016) 353–367

112-15   José Miguel Gonçalves Ledo Belo da Costa, Optimization of filling systems for low pressure by FLOW-3D, Dissertação de mestrado integrado em Engenharia Mecânica, 2015.

89-15   B.W. Zhu, L.X. Li, X. Liu, L.Q. Zhang and R. Xu, Effect of Viscosity Measurement Method to Simulate High Pressure Die Casting of Thin-Wall AlSi10MnMg Alloy Castings, Journal of Materials Engineering and Performance, Published online, November 2015, doi.org/10.1007/s11665-015-1783-8, © ASM International.

88-15   Peng Zhang, Zhenming Li, Baoliang Liu, Wenjiang Ding and Liming Peng, Improved tensile properties of a new aluminum alloy for high pressure die casting, Materials Science & Engineering A651(2016)376–390, Available online, November 2015.

83-15   Zu-Qi Hu, Xin-Jian Zhang and Shu-Sen Wu, Microstructure, Mechanical Properties and Die-Filling Behavior of High-Performance Die-Cast Al–Mg–Si–Mn Alloy, Acta Metall. Sin. (Engl. Lett.), doi.org/10.1007/s40195-015-0332-7, © The Chinese Society for Metals and Springer-Verlag Berlin Heidelberg 2015.

82-15   J. Müller, L. Xue, M.C. Carter, C. Thoma, M. Fehlbier and M. Todte, A Die Spray Cooling Model for Thermal Die Cycling Simulations, 2015 Die Casting Congress & Exposition, Indianapolis, IN, October 2015

81-15   M. T. Murray, L.F. Hansen, L. Chilcott, E. Li and A.M. Murray, Case Studies in the Use of Simulation- Improved Yield and Reduced Time to Market, 2015 Die Casting Congress & Exposition, Indianapolis, IN, October 2015

80-15   R. Bhola, S. Chandra and D. Souders, Predicting Castability of Thin-Walled Parts for the HPDC Process Using Simulations, 2015 Die Casting Congress & Exposition, Indianapolis, IN, October 2015

76-15   Prosenjit Das, Sudip K. Samanta, Shashank Tiwari and Pradip Dutta, Die Filling Behaviour of Semi Solid A356 Al Alloy Slurry During Rheo Pressure Die Casting, Transactions of the Indian Institute of Metals, pp 1-6, October 2015

74-15   Murat KORU and Orhan SERÇE, Yüksek Basınçlı Döküm Prosesinde Enjeksiyon Parametrelerine Bağlı Olarak Döküm Simülasyon, Cumhuriyet University Faculty of Science, Science Journal (CSJ), Vol. 36, No: 5 (2015) ISSN: 1300-1949, May 2015

69-15   A. Viswanath, S. Sivaraman, U. T. S. Pillai, Computer Simulation of Low Pressure Casting Process Using FLOW-3D, Materials Science Forum, Vols. 830-831, pp. 45-48, September 2015

68-15   J. Aneesh Kumar, K. Krishnakumar and S. Savithri, Computer Simulation of Centrifugal Casting Process Using FLOW-3D, Materials Science Forum, Vols. 830-831, pp. 53-56, September 2015

59-15   F. Hosseini Yekta and S. A. Sadough Vanini, Simulation of the flow of semi-solid steel alloy using an enhanced model, Metals and Materials International, August 2015.

44-15   Ulrich E. Klotz, Tiziana Heiss and Dario Tiberto, Platinum investment casting material properties, casting simulation and optimum process parameters, Jewelry Technology Forum 2015

41-15   M. Barkhudarov and R. Pirovano, Minimizing Air Entrainment in High Pressure Die Casting Shot Sleeves, GIFA 2015, Düsseldorf, Germany

40-15   M. Todte, A. Fent, and H. Lang, Simulation in support of the development of innovative processes in the casting industry, GIFA 2015, Düsseldorf, Germany

19-15   Bruce Morey, Virtual casting improves powertrain design, Automotive Engineering, SAE International, March 2015.

15-15   K.S. Oh, J.D. Lee, S.J. Kim and J.Y. Choi, Development of a large ingot continuous caster, Metall. Res. Technol. 112, 203 (2015) © EDP Sciences, 2015, doi.org/10.1051/metal/2015006, www.metallurgical-research.org

14-15   Tiziana Heiss, Ulrich E. Klotz and Dario Tiberto, Platinum Investment Casting, Part I: Simulation and Experimental Study of the Casting Process, Johnson Matthey Technol. Rev., 2015, 59, (2), 95, doi.org/10.1595/205651315×687399

138-14 Christopher Thoma, Wolfram Volk, Ruben Heid, Klaus Dilger, Gregor Banner and Harald Eibisch, Simulation-based prediction of the fracture elongation as a failure criterion for thin-walled high-pressure die casting components, International Journal of Metalcasting, Vol. 8, No. 4, pp. 47-54, 2014. doi.org/10.1007/BF03355594

107-14  Mehran Seyed Ahmadi, Dissolution of Si in Molten Al with Gas Injection, ProQuest Dissertations And Theses; Thesis (Ph.D.), University of Toronto (Canada), 2014; Publication Number: AAT 3637106; ISBN: 9781321195231; Source: Dissertation Abstracts International, Volume: 76-02(E), Section: B.; 191 p.

99-14   R. Bhola and S. Chandra, Predicting Castability for Thin-Walled HPDC Parts, Foundry Management Technology, December 2014

92-14   Warren Bishenden and Changhua Huang, Venting design and process optimization of die casting process for structural components; Part II: Venting design and process optimization, Die Casting Engineer, November 2014

90-14   Ken’ichi Kanazawa, Ken’ichi Yano, Jun’ichi Ogura, and Yasunori Nemoto, Optimum Runner Design for Die-Casting using CFD Simulations and Verification with Water-Model Experiments, Proceedings of the ASME 2014 International Mechanical Engineering Congress and Exposition, IMECE2014, November 14-20, 2014, Montreal, Quebec, Canada, IMECE2014-37419

89-14   P. Kapranos, C. Carney, A. Pola, and M. Jolly, Advanced Casting Methodologies: Investment Casting, Centrifugal Casting, Squeeze Casting, Metal Spinning, and Batch Casting, In Comprehensive Materials Processing; McGeough, J., Ed.; 2014, Elsevier Ltd., 2014; Vol. 5, pp 39–67.

77-14   Andrei Y. Korotchenko, Development of Scientific and Technological Approaches to Casting Net-Shaped Castings in Sand Molds Free of Shrinkage Defects and Hot Tears, Post-doctoral thesis: Russian State Technological University, 2014. In Russian.

69-14   L. Xue, M.C. Carter, A.V. Catalina, Z. Lin, C. Li, and C. Qiu, Predicting, Preventing Core Gas Defects in Steel Castings, Modern Casting, September 2014

68-14   L. Xue, M.C. Carter, A.V. Catalina, Z. Lin, C. Li, and C. Qiu, Numerical Simulation of Core Gas Defects in Steel Castings, Copyright 2014 American Foundry Society, 118th Metalcasting Congress, April 8 – 11, 2014, Schaumburg, IL

51-14   Jesus M. Blanco, Primitivo Carranza, Rafael Pintos, Pedro Arriaga, and Lakhdar Remaki, Identification of Defects Originated during the Filling of Cast Pieces through Particles Modelling, 11th World Congress on Computational Mechanics (WCCM XI), 5th European Conference on Computational Mechanics (ECCM V), 6th European Conference on Computational Fluid Dynamics (ECFD VI), E. Oñate, J. Oliver and A. Huerta (Eds)

47-14   B. Vijaya Ramnatha, C.Elanchezhiana, Vishal Chandrasekhar, A. Arun Kumarb, S. Mohamed Asif, G. Riyaz Mohamed, D. Vinodh Raj , C .Suresh Kumar, Analysis and Optimization of Gating System for Commutator End Bracket, Procedia Materials Science 6 ( 2014 ) 1312 – 1328, 3rd International Conference on Materials Processing and Characterisation (ICMPC 2014)

42-14  Bing Zhou, Yong-lin Kang, Guo-ming Zhu, Jun-zhen Gao, Ming-fan Qi, and Huan-huan Zhang, Forced convection rheoforming process for preparation of 7075 aluminum alloy semisolid slurry and its numerical simulation, Trans. Nonferrous Met. Soc. China 24(2014) 1109−1116

37-14    A. Karwinski, W. Lesniewski, P. Wieliczko, and M. Malysza, Casting of Titanium Alloys in Centrifugal Induction Furnaces, Archives of Metallurgy and Materials, Volume 59, Issue 1, doi.org/10.2478/amm-2014-0068, 2014.

26-14    Bing Zhou, Yonglin Kang, Mingfan Qi, Huanhuan Zhang and Guoming ZhuR-HPDC Process with Forced Convection Mixing Device for Automotive Part of A380 Aluminum Alloy, Materials 2014, 7, 3084-3105; doi.org/10.3390/ma7043084

20-14  Johannes Hartmann, Tobias Fiegl, Carolin Körner, Aluminum integral foams with tailored density profile by adapted blowing agents, Applied Physics A, doi.org/10.1007/s00339-014-8377-4, March 2014.

19-14    A.Y. Korotchenko, N.A. Nikiforova, E.D. Demjanov, N.C. Larichev, The Influence of the Filling Conditions on the Service Properties of the Part Side Frame, Russian Foundryman, 1 (January), pp 40-43, 2014. In Russian.

11-14 B. Fuchs and C. Körner, Mesh resolution consideration for the viability prediction of lost salt cores in the high pressure die casting process, Progress in Computational Fluid Dynamics, Vol. 14, No. 1, 2014, Copyright © 2014 Inderscience Enterprises Ltd.

08-14 FY Hsu, SW Wang, and HJ Lin, The External and Internal Shrinkages in Aluminum Gravity Castings, Shape Casting: 5th International Symposium 2014. Available online at Google Books

103-13  B. Fuchs, H. Eibisch and C. Körner, Core Viability Simulation for Salt Core Technology in High-Pressure Die Casting, International Journal of Metalcasting, July 2013, Volume 7, Issue 3, pp 39–45

94-13    Randall S. Fielding, J. Crapps, C. Unal, and J.R.Kennedy, Metallic Fuel Casting Development and Parameter Optimization Simulations, International Conference on Fast reators and Related Fuel Cycles (FR13), 4-7 March 2013, Paris France

90-13  A. Karwińskia, M. Małyszaa, A. Tchórza, A. Gila, B. Lipowska, Integration of Computer Tomography and Simulation Analysis in Evaluation of Quality of Ceramic-Carbon Bonded Foam Filter, Archives of Foundry Engineering, doi.org/10.2478/afe-2013-0084, Published quarterly as the organ of the Foundry Commission of the Polish Academy of Sciences, ISSN, (2299-2944), Volume 13, Issue 4/2013

88-13  Litie and Metallurgia (Casting and Metallurgy), 3 (72), 2013, N.V.Sletova, I.N.Volnov, S.P.Zadrutsky, V.A.Chaikin, Modeling of the Process of Removing Non-metallic Inclusions in Aluminum Alloys Using the FLOW-3D program, pp 138-140. In Russian.

85-13    Michał Szucki,Tomasz Goraj, Janusz Lelito, Józef S. Suchy, Numerical Analysis of Solid Particles Flow in Liquid Metal, XXXVII International Scientific Conference Foundryman’ Day 2013, Krakow, 28-29 November 2013

84-13  Körner, C., Schwankl, M., Himmler, D., Aluminum-Aluminum compound castings by electroless deposited zinc layers, Journal of Materials Processing Technology (2014), doi.org/10.1016/j.jmatprotec.2013.12.01483-13.

77-13  Antonio Armillotta & Raffaello Baraggi & Simone Fasoli, SLM tooling for die casting with conformal cooling channels, The International Journal of Advanced Manufacturing Technology, doi.org/10.1007/s00170-013-5523-7, December 2013.

64-13   Johannes Hartmann, Christina Blümel, Stefan Ernst, Tobias Fiegl, Karl-Ernst Wirth, Carolin Körner, Aluminum integral foam castings with microcellular cores by nano-functionalization, J Mater Sci, doi.org/10.1007/s10853-013-7668-z, September 2013.

46-13  Nicholas P. Orenstein, 3D Flow and Temperature Analysis of Filling a Plutonium Mold, LA-UR-13-25537, Approved for public release; distribution is unlimited. Los Alamos Annual Student Symposium 2013, 2013-07-24 (Rev.1)

42-13   Yang Yue, William D. Griffiths, and Nick R. Green, Modelling of the Effects of Entrainment Defects on Mechanical Properties in a Cast Al-Si-Mg Alloy, Materials Science Forum, 765, 225, 2013.

39-13  J. Crapps, D.S. DeCroix, J.D Galloway, D.A. Korzekwa, R. Aikin, R. Fielding, R. Kennedy, C. Unal, Separate effects identification via casting process modeling for experimental measurement of U-Pu-Zr alloys, Journal of Nuclear Materials, 15 July 2013.

35-13   A. Pari, Real Life Problem Solving through Simulations in the Die Casting Industry – Case Studies, © Die Casting Engineer, July 2013.

34-13  Martin Lagler, Use of Simulation to Predict the Viability of Salt Cores in the HPDC Process – Shot Curve as a Decisive Criterion, © Die Casting Engineer, July 2013.

24-13    I.N.Volnov, Optimizatsia Liteynoi Tekhnologii, (Casting Technology Optimization), Liteyshik Rossii (Russian Foundryman), 3, 2013, 27-29. In Russian

23-13  M.R. Barkhudarov, I.N. Volnov, Minimizatsia Zakhvata Vozdukha v Kamere Pressovania pri Litie pod Davleniem, (Minimization of Air Entrainment in the Shot Sleeve During High Pressure Die Casting), Liteyshik Rossii (Russian Foundryman), 3, 2013, 30-34. In Russian

09-13  M.C. Carter and L. Xue, Simulating the Parameters that Affect Core Gas Defects in Metal Castings, Copyright 2012 American Foundry Society, Presented at the 2013 CastExpo, St. Louis, Missouri, April 2013

08-13  C. Reilly, N.R. Green, M.R. Jolly, J.-C. Gebelin, The Modelling Of Oxide Film Entrainment In Casting Systems Using Computational Modelling, Applied Mathematical Modelling, http://dx.doi.org/10.1016/j.apm.2013.03.061, April 2013.

03-13  Alexandre Reikher and Krishna M. Pillai, A fast simulation of transient metal flow and solidification in a narrow channel. Part II. Model validation and parametric study, Int. J. Heat Mass Transfer (2013), http://dx.doi.org/10.1016/j.ijheatmasstransfer.2012.12.061.

02-13  Alexandre Reikher and Krishna M. Pillai, A fast simulation of transient metal flow and solidification in a narrow channel. Part I: Model development using lubrication approximation, Int. J. Heat Mass Transfer (2013), http://dx.doi.org/10.1016/j.ijheatmasstransfer.2012.12.060.

116-12  Jufu Jianga, Ying Wang, Gang Chena, Jun Liua, Yuanfa Li and Shoujing Luo, “Comparison of mechanical properties and microstructure of AZ91D alloy motorcycle wheels formed by die casting and double control forming, Materials & Design, Volume 40, September 2012, Pages 541-549.

107-12  F.K. Arslan, A.H. Hatman, S.Ö. Ertürk, E. Güner, B. Güner, An Evaluation for Fundamentals of Die Casting Materials Selection and Design, IMMC’16 International Metallurgy & Materials Congress, Istanbul, Turkey, 2012.

103-12 WU Shu-sen, ZHONG Gu, AN Ping, WAN Li, H. NAKAE, Microstructural characteristics of Al−20Si−2Cu−0.4Mg−1Ni alloy formed by rheo-squeeze casting after ultrasonic vibration treatment, Transactions of Nonferrous Metals Society of China, 22 (2012) 2863-2870, November 2012. Full paper available online.

109-12 Alexandre Reikher, Numerical Analysis of Die-Casting Process in Thin Cavities Using Lubrication Approximation, Ph.D. Thesis: The University of Wisconsin Milwaukee, Engineering Department (2012) Theses and Dissertations. Paper 65.

97-12 Hong Zhou and Li Heng Luo, Filling Pattern of Step Gating System in Lost Foam Casting Process and its Application, Advanced Materials Research, Volumes 602-604, Progress in Materials and Processes, 1916-1921, December 2012.

93-12  Liangchi Zhang, Chunliang Zhang, Jeng-Haur Horng and Zichen Chen, Functions of Step Gating System in the Lost Foam Casting Process, Advanced Materials Research, 591-593, 940, DOI: 10.4028/www.scientific.net/AMR.591-593.940, November 2012.

91-12  Hong Yan, Jian Bin Zhu, Ping Shan, Numerical Simulation on Rheo-Diecasting of Magnesium Matrix Composites, 10.4028/www.scientific.net/SSP.192-193.287, Solid State Phenomena, 192-193, 287.

89-12  Alexandre Reikher and Krishna M. Pillai, A Fast Numerical Simulation for Modeling Simultaneous Metal Flow and Solidification in Thin Cavities Using the Lubrication Approximation, Numerical Heat Transfer, Part A: Applications: An International Journal of Computation and Methodology, 63:2, 75-100, November 2012.

82-12  Jufu Jiang, Gang Chen, Ying Wang, Zhiming Du, Weiwei Shan, and Yuanfa Li, Microstructure and mechanical properties of thin-wall and high-rib parts of AM60B Mg alloy formed by double control forming and die casting under the optimal conditions, Journal of Alloys and Compounds, http://dx.doi.org/10.1016/j.jallcom.2012.10.086, October 2012.

78-12   A. Pari, Real Life Problem Solving through Simulations in the Die Casting Industry – Case Studies, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012, Indianapolis, IN.

77-12  Y. Wang, K. Kabiri-Bamoradian and R.A. Miller, Rheological behavior models of metal matrix alloys in semi-solid casting process, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012, Indianapolis, IN.

76-12  A. Reikher and H. Gerber, Analysis of Solidification Parameters During the Die Cast Process, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012, Indianapolis, IN.

75-12 R.A. Miller, Y. Wang and K. Kabiri-Bamoradian, Estimating Cavity Fill Time, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012Indianapolis, IN.

65-12  X.H. Yang, T.J. Lu, T. Kim, Influence of non-conducting pore inclusions on phase change behavior of porous media with constant heat flux boundaryInternational Journal of Thermal Sciences, Available online 10 October 2012. Available online at SciVerse.

55-12  Hejun Li, Pengyun Wang, Lehua Qi, Hansong Zuo, Songyi Zhong, Xianghui Hou, 3D numerical simulation of successive deposition of uniform molten Al droplets on a moving substrate and experimental validation, Computational Materials Science, Volume 65, December 2012, Pages 291–301.

52-12 Hongbing Ji, Yixin Chen and Shengzhou Chen, Numerical Simulation of Inner-Outer Couple Cooling Slab Continuous Casting in the Filling Process, Advanced Materials Research (Volumes 557-559), Advanced Materials and Processes II, pp. 2257-2260, July 2012.

47-12    Petri Väyrynen, Lauri Holappa, and Seppo Louhenkilpi, Simulation of Melting of Alloying Materials in Steel Ladle, SCANMET IV – 4th International Conference on Process Development in Iron and Steelmaking, Lulea, Sweden, June 10-13, 2012.

46-12  Bin Zhang and Dave Salee, Metal Flow and Heat Transfer in Billet DC Casting Using Wagstaff® Optifill™ Metal Distribution Systems, 5th International Metal Quality Workshop, United Arab Emirates Dubai, March 18-22, 2012.

45-12 D.R. Gunasegaram, M. Givord, R.G. O’Donnell and B.R. Finnin, Improvements engineered in UTS and elongation of aluminum alloy high pressure die castings through the alteration of runner geometry and plunger velocity, Materials Science & Engineering.

44-12    Antoni Drys and Stefano Mascetti, Aluminum Casting Simulations, Desktop Engineering, September 2012

42-12   Huizhen Duan, Jiangnan Shen and Yanping Li, Comparative analysis of HPDC process of an auto part with ProCAST and FLOW-3D, Applied Mechanics and Materials Vols. 184-185 (2012) pp 90-94, Online available since 2012/Jun/14 at www.scientific.net, © (2012) Trans Tech Publications, Switzerland, doi:10.4028/www.scientific.net/AMM.184-185.90.

41-12    Deniece R. Korzekwa, Cameron M. Knapp, David A. Korzekwa, and John W. Gibbs, Co-Design – Fabrication of Unalloyed Plutonium, LA-UR-12-23441, MDI Summer Research Group Workshop Advanced Manufacturing, 2012-07-25/2012-07-26 (Los Alamos, New Mexico, United States)

29-12  Dario Tiberto and Ulrich E. Klotz, Computer simulation applied to jewellery casting: challenges, results and future possibilities, IOP Conf. Ser.: Mater. Sci. Eng.33 012008. Full paper available at IOP.

28-12  Y Yue and N R Green, Modelling of different entrainment mechanisms and their influences on the mechanical reliability of Al-Si castings, 2012 IOP Conf. Ser.: Mater. Sci. Eng. 33,012072.Full paper available at IOP.

27-12  E Kaschnitz, Numerical simulation of centrifugal casting of pipes, 2012 IOP Conf. Ser.: Mater. Sci. Eng. 33 012031, Issue 1. Full paper available at IOP.

15-12  C. Reilly, N.R Green, M.R. Jolly, The Present State Of Modeling Entrainment Defects In The Shape Casting Process, Applied Mathematical Modelling, Available online 27 April 2012, ISSN 0307-904X, 10.1016/j.apm.2012.04.032.

12-12   Andrei Starobin, Tony Hirt, Hubert Lang, and Matthias Todte, Core drying simulation and validation, International Foundry Research, GIESSEREIFORSCHUNG 64 (2012) No. 1, ISSN 0046-5933, pp 2-5

10-12  H. Vladimir Martínez and Marco F. Valencia (2012). Semisolid Processing of Al/β-SiC Composites by Mechanical Stirring Casting and High Pressure Die Casting, Recent Researches in Metallurgical Engineering – From Extraction to Forming, Dr Mohammad Nusheh (Ed.), ISBN: 978-953-51-0356-1, InTech

07-12     Amir H. G. Isfahani and James M. Brethour, Simulating Thermal Stresses and Cooling Deformations, Die Casting Engineer, March 2012

06-12   Shuisheng Xie, Youfeng He and Xujun Mi, Study on Semi-solid Magnesium Alloys Slurry Preparation and Continuous Roll-casting Process, Magnesium Alloys – Design, Processing and Properties, ISBN: 978-953-307-520-4, InTech.

04-12 J. Spangenberg, N. Roussel, J.H. Hattel, H. Stang, J. Skocek, M.R. Geiker, Flow induced particle migration in fresh concrete: Theoretical frame, numerical simulations and experimental results on model fluids, Cement and Concrete Research, http://dx.doi.org/10.1016/j.cemconres.2012.01.007, February 2012.

01-12   Lee, B., Baek, U., and Han, J., Optimization of Gating System Design for Die Casting of Thin Magnesium Alloy-Based Multi-Cavity LCD Housings, Journal of Materials Engineering and Performance, Springer New York, Issn: 1059-9495, 10.1007/s11665-011-0111-1, Volume 1 / 1992 – Volume 21 / 2012. Available online at Springer Link.

104-11  Fu-Yuan Hsu and Huey Jiuan Lin, Foam Filters Used in Gravity Casting, Metall and Materi Trans B (2011) 42: 1110. doi:10.1007/s11663-011-9548-8.

99-11    Eduardo Trejo, Centrifugal Casting of an Aluminium Alloy, thesis: Doctor of Philosophy, Metallurgy and Materials School of Engineering University of Birmingham, October 2011. Full paper available upon request.

93-11  Olga Kononova, Andrejs Krasnikovs ,Videvuds Lapsa,Jurijs Kalinka and Angelina Galushchak, Internal Structure Formation in High Strength Fiber Concrete during Casting, World Academy of Science, Engineering and Technology 59 2011

76-11  J. Hartmann, A. Trepper, and C. Körner, Aluminum Integral Foams with Near-Microcellular Structure, Advanced Engineering Materials 2011, Volume 13 (2011) No. 11, © Wiley-VCH

71-11  Fu-Yuan Hsu and Yao-Ming Yang Confluence Weld in an Aluminum Gravity Casting, Journal of Materials Processing Technology, Available online 23 November 2011, ISSN 0924-0136, 10.1016/j.jmatprotec.2011.11.006.

65-11     V.A. Chaikin, A.V. Chaikin, I.N.Volnov, A Study of the Process of Late Modification Using Simulation, in Zagotovitelnye Proizvodstva v Mashinostroenii, 10, 2011, 8-12. In Russian.

54-11  Ngadia Taha Niane and Jean-Pierre Michalet, Validation of Foundry Process for Aluminum Parts with FLOW-3D Software, Proceedings of the 2011 International Symposium on Liquid Metal Processing and Casting, 2011.

51-11    A. Reikher and H. Gerber, Calculation of the Die Cast parameters of the Thin Wall Aluminum Cast Part, 2011 Die Casting Congress & Tabletop, Columbus, OH, September 19-21, 2011

50-11   Y. Wang, K. Kabiri-Bamoradian, and R.A. Miller, Runner design optimization based on CFD simulation for a die with multiple cavities, 2011 Die Casting Congress & Tabletop, Columbus, OH, September 19-21, 2011

48-11 A. Karwiński, W. Leśniewski, S. Pysz, P. Wieliczko, The technology of precision casting of titanium alloys by centrifugal process, Archives of Foundry Engineering, ISSN: 1897-3310), Volume 11, Issue 3/2011, 73-80, 2011.

46-11  Daniel Einsiedler, Entwicklung einer Simulationsmethodik zur Simulation von Strömungs- und Trocknungsvorgängen bei Kernfertigungsprozessen mittels CFD (Development of a simulation methodology for simulating flow and drying operations in core production processes using CFD), MSc thesis at Technical University of Aalen in Germany (Hochschule Aalen), 2011.

44-11  Bin Zhang and Craig Shaber, Aluminum Ingot Thermal Stress Development Modeling of the Wagstaff® EpsilonTM Rolling Ingot DC Casting System during the Start-up Phase, Materials Science Forum Vol. 693 (2011) pp 196-207, © 2011 Trans Tech Publications, July, 2011.

43-11 Vu Nguyen, Patrick Rohan, John Grandfield, Alex Levin, Kevin Naidoo, Kurt Oswald, Guillaume Girard, Ben Harker, and Joe Rea, Implementation of CASTfill low-dross pouring system for ingot casting, Materials Science Forum Vol. 693 (2011) pp 227-234, © 2011 Trans Tech Publications, July, 2011.

40-11  A. Starobin, D. Goettsch, M. Walker, D. Burch, Gas Pressure in Aluminum Block Water Jacket Cores, © 2011 American Foundry Society, International Journal of Metalcasting/Summer 2011

37-11 Ferencz Peti, Lucian Grama, Analyze of the Possible Causes of Porosity Type Defects in Aluminum High Pressure Diecast Parts, Scientific Bulletin of the Petru Maior University of Targu Mures, Vol. 8 (XXV) no. 1, 2011, ISSN 1841-9267

31-11  Johannes Hartmann, André Trepper, Carolin Körner, Aluminum Integral Foams with Near-Microcellular Structure, Advanced Engineering Materials, 13: n/a. doi: 10.1002/adem.201100035, June 2011.

27-11  A. Pari, Optimization of HPDC Process using Flow Simulation Case Studies, Die Casting Engineer, July 2011

26-11    A. Reikher, H. Gerber, Calculation of the Die Cast Parameters of the Thin Wall Aluminum Die Casting Part, Die Casting Engineer, July 2011

21-11 Thang Nguyen, Vu Nguyen, Morris Murray, Gary Savage, John Carrig, Modelling Die Filling in Ultra-Thin Aluminium Castings, Materials Science Forum (Volume 690), Light Metals Technology V, pp 107-111, 10.4028/www.scientific.net/MSF.690.107, June 2011.

19-11 Jon Spangenberg, Cem Celal Tutum, Jesper Henri Hattel, Nicolas Roussel, Metter Rica Geiker, Optimization of Casting Process Parameters for Homogeneous Aggregate Distribution in Self-Compacting Concrete: A Feasibility Study, © IEEE Congress on Evolutionary Computation, 2011, New Orleans, USA

16-11  A. Starobin, C.W. Hirt, H. Lang, and M. Todte, Core Drying Simulation and Validations, AFS Proceedings 2011, © American Foundry Society, Presented at the 115th Metalcasting Congress, Schaumburg, Illinois, April 2011.

15-11  J. J. Hernández-Ortega, R. Zamora, J. López, and F. Faura, Numerical Analysis of Air Pressure Effects on the Flow Pattern during the Filling of a Vertical Die Cavity, AIP Conf. Proc., Volume 1353, pp. 1238-1243, The 14th International Esaform Conference on Material Forming: Esaform 2011; doi:10.1063/1.3589686, May 2011. Available online.

10-11 Abbas A. Khalaf and Sumanth Shankar, Favorable Environment for Nondentric Morphology in Controlled Diffusion Solidification, DOI: 10.1007/s11661-011-0641-z, © The Minerals, Metals & Materials Society and ASM International 2011, Metallurgical and Materials Transactions A, March 11, 2011.

08-11 Hai Peng Li, Chun Yong Liang, Li Hui Wang, Hong Shui Wang, Numerical Simulation of Casting Process for Gray Iron Butterfly Valve, Advanced Materials Research, 189-193, 260, February 2011.

04-11  C.W. Hirt, Predicting Core Shooting, Drying and Defect Development, Foundry Management & Technology, January 2011.

76-10  Zhizhong Sun, Henry Hu, Alfred Yu, Numerical Simulation and Experimental Study of Squeeze Casting Magnesium Alloy AM50, Magnesium Technology 2010, 2010 TMS Annual Meeting & ExhibitionFebruary 14-18, 2010, Seattle, WA.

68-10  A. Reikher, H. Gerber, K.M. Pillai, T.-C. Jen, Natural Convection—An Overlooked Phenomenon of the Solidification Process, Die Casting Engineer, January 2010

54-10    Andrea Bernardoni, Andrea Borsi, Stefano Mascetti, Alessandro Incognito and Matteo Corrado, Fonderia Leonardo aveva ragione! L’enorme cavallo dedicato a Francesco Sforza era materialmente realizzabile, A&C – Analisis e Calcolo, Giugno 2010. In  Italian.

48-10  J. J. Hernández-Ortega, R. Zamora, J. Palacios, J. López and F. Faura, An Experimental and Numerical Study of Flow Patterns and Air Entrapment Phenomena During the Filling of a Vertical Die Cavity, J. Manuf. Sci. Eng., October 2010, Volume 132, Issue 5, 05101, doi:10.1115/1.4002535.

47-10  A.V. Chaikin, I.N. Volnov, and V.A. Chaikin, Development of Dispersible Mixed Inoculant Compositions Using the FLOW-3D Program, Liteinoe Proizvodstvo, October, 2010, in Russian.

42-10  H. Lakshmi, M.C. Vinay Kumar, Raghunath, P. Kumar, V. Ramanarayanan, K.S.S. Murthy, P. Dutta, Induction reheating of A356.2 aluminum alloy and thixocasting as automobile component, Transactions of Nonferrous Metals Society of China 20(20101) s961-s967.

41-10  Pamela J. Waterman, Understanding Core-Gas Defects, Desktop Engineering, October 2010. Available online at Desktop Engineering. Also published in the Foundry Trade Journal, November 2010.

39-10  Liu Zheng, Jia Yingying, Mao Pingli, Li Yang, Wang Feng, Wang Hong, Zhou Le, Visualization of Die Casting Magnesium Alloy Steering Bracket, Special Casting & Nonferrous Alloys, ISSN: 1001-2249, CN: 42-1148/TG, 2010-04. In Chinese.

37-10  Morris Murray, Lars Feldager Hansen, and Carl Reinhardt, I Have Defects – Now What, Die Casting Engineer, September 2010

36-10  Stefano Mascetti, Using Flow Analysis Software to Optimize Piston Velocity for an HPDC Process, Die Casting Engineer, September 2010. Also available in Italian: Ottimizzare la velocita del pistone in pressofusione.  A & C, Analisi e Calcolo, Anno XII, n. 42, Gennaio 2011, ISSN 1128-3874.

32-10  Guan Hai Yan, Sheng Dun Zhao, Zheng Hui Sha, Parameters Optimization of Semisolid Diecasting Process for Air-Conditioner’s Triple Valve in HPb59-1 Alloy, Advanced Materials Research (Volumes 129 – 131), Vol. Material and Manufacturing Technology, pp. 936-941, DOI: 10.4028/www.scientific.net/AMR.129-131.936, August 2010.

29-10 Zheng Peng, Xu Jun, Zhang Zhifeng, Bai Yuelong, and Shi Likai, Numerical Simulation of Filling of Rheo-diecasting A357 Aluminum Alloy, Special Casting & Nonferrous Alloys, DOI: CNKI:SUN:TZZZ.0.2010-01-024, 2010.

27-10 For an Aerospace Diecasting, Littler Uses Simulation to Reveal Defects, and Win a New Order, Foundry Management & Technology, July 2010

23-10 Michael R. Barkhudarov, Minimizing Air Entrainment, The Canadian Die Caster, June 2010

15-10 David H. Kirkwood, Michel Suery, Plato Kapranos, Helen V. Atkinson, and Kenneth P. Young, Semi-solid Processing of Alloys, 2010, XII, 172 p. 103 illus., 19 in color., Hardcover ISBN: 978-3-642-00705-7.

09-10  Shannon Wetzel, Fullfilling Da Vinci’s Dream, Modern Casting, April 2010.

08-10 B.I. Semenov, K.M. Kushtarov, Semi-solid Manufacturing of Castings, New Industrial Technologies, Publication of Moscow State Technical University n.a. N.E. Bauman, 2009 (in Russian)

07-10 Carl Reilly, Development Of Quantitative Casting Quality Assessment Criteria Using Process Modelling, thesis: The University of Birmingham, March 2010 (Available upon request)

06-10 A. Pari, Optimization of HPDC Process using Flow Simulation – Case Studies, CastExpo ’10, NADCA, Orlando, Florida, March 2010

05-10 M.C. Carter, S. Palit, and M. Littler, Characterizing Flow Losses Occurring in Air Vents and Ejector Pins in High Pressure Die Castings, CastExpo ’10, NADCA, Orlando, Florida, March 2010

04-10 Pamela Waterman, Simulating Porosity Factors, Foundry Management Technology, March 2010, Article available at Foundry Management Technology

03-10 C. Reilly, M.R. Jolly, N.R. Green, JC Gebelin, Assessment of Casting Filling by Modeling Surface Entrainment Events Using CFD, 2010 TMS Annual Meeting & Exhibition (Jim Evans Honorary Symposium), Seattle, Washington, USA, February 14-18, 2010

02-10 P. Väyrynen, S. Wang, J. Laine and S.Louhenkilpi, Control of Fluid Flow, Heat Transfer and Inclusions in Continuous Casting – CFD and Neural Network Studies, 2010 TMS Annual Meeting & Exhibition (Jim Evans Honorary Symposium), Seattle, Washington, USA, February 14-18, 2010

60-09   Somlak Wannarumon, and Marco Actis Grande, Comparisons of Computer Fluid Dynamic Software Programs applied to Jewelry Investment Casting Process, World Academy of Science, Engineering and Technology 55 2009.

59-09   Marco Actis Grande and Somlak Wannarumon, Numerical Simulation of Investment Casting of Gold Jewelry: Experiments and Validations, World Academy of Science, Engineering and Technology, Vol:3 2009-07-24

56-09  Jozef Kasala, Ondrej Híreš, Rudolf Pernis, Start-up Phase Modeling of Semi Continuous Casting Process of Brass Billets, Metal 2009, 19.-21.5.2009

51-09  In-Ting Hong, Huan-Chien Tung, Chun-Hao Chiu and Hung-Shang Huang, Effect of Casting Parameters on Microstructure and Casting Quality of Si-Al Alloy for Vacuum Sputtering, China Steel Technical Report, No. 22, pp. 33-40, 2009.

42-09  P. Väyrynen, S. Wang, S. Louhenkilpi and L. Holappa, Modeling and Removal of Inclusions in Continuous Casting, Materials Science & Technology 2009 Conference & Exhibition, Pittsburgh, Pennsylvania, USA, October 25-29, 2009

41-09 O.Smirnov, P.Väyrynen, A.Kravchenko and S.Louhenkilpi, Modern Methods of Modeling Fluid Flow and Inclusions Motion in Tundish Bath – General View, Proceedings of Steelsim 2009 – 3rd International Conference on Simulation and Modelling of Metallurgical Processes in Steelmaking, Leoben, Austria, September 8-10, 2009

21-09 A. Pari, Case Studies – Optimization of HPDC Process Using Flow Simulation, Die Casting Engineer, July 2009

20-09 M. Sirvio, M. Wos, Casting directly from a computer model by using advanced simulation software, FLOW-3D Cast, Archives of Foundry Engineering Volume 9, Issue 1/2009, 79-82

19-09 Andrei Starobin, C.W. Hirt, D. Goettsch, A Model for Binder Gas Generation and Transport in Sand Cores and Molds, Modeling of Casting, Welding, and Solidification Processes XII, TMS (The Minerals, Metals & Minerals Society), June 2009

11-09 Michael Barkhudarov, Minimizing Air Entrainment in a Shot Sleeve during Slow-Shot Stage, Die Casting Engineer (The North American Die Casting Association ISSN 0012-253X), May 2009

10-09 A. Reikher, H. Gerber, Application of One-Dimensional Numerical Simulation to Optimize Process Parameters of a Thin-Wall Casting in High Pressure Die Casting, Die Casting Engineer (The North American Die Casting Association ISSN 0012-253X), May 2009

7-09 Andrei Starobin, Simulation of Core Gas Evolution and Flow, presented at the North American Die Casting Association – 113th Metalcasting Congress, April 7-10, 2009, Las Vegas, Nevada, USA

6-09 A.Pari, Optimization of HPDC PROCESS: Case Studies, North American Die Casting Association – 113th Metalcasting Congress, April 7-10, 2009, Las Vegas, Nevada, USA

2-09 C. Reilly, N.R. Green and M.R. Jolly, Oxide Entrainment Structures in Horizontal Running Systems, TMS 2009, San Francisco, California, February 2009

30-08 I.N.Volnov, Computer Modeling of Casting of Pipe Fittings, © 2008, Pipe Fittings, 5 (38), 2008. Russian version

28-08 A.V.Chaikin, I.N.Volnov, V.A.Chaikin, Y.A.Ukhanov, N.R.Petrov, Analysis of the Efficiency of Alloy Modifiers Using Statistics and Modeling, © 2008, Liteyshik Rossii (Russian Foundryman), October, 2008

27-08 P. Scarber, Jr., H. Littleton, Simulating Macro-Porosity in Aluminum Lost Foam Castings, American Foundry Society, © 2008, AFS Lost Foam Conference, Asheville, North Carolina, October, 2008

25-08 FMT Staff, Forecasting Core Gas Pressures with Computer Simulation, Foundry Management and Technology, October 28, 2008 © 2008 Penton Media, Inc. Online article

24-08 Core and Mold Gas Evolution, Foundry Management and Technology, January 24, 2008 (excerpted from the FM&T May 2007 issue) © 2008 Penton Media, Inc.

22-08 Mark Littler, Simulation Eliminates Die Casting Scrap, Modern Casting/September 2008

21-08 X. Chen, D. Penumadu, Permeability Measurement and Numerical Modeling for Refractory Porous Materials, AFS Transactions © 2008 American Foundry Society, CastExpo ’08, Atlanta, Georgia, May 2008

20-08 Rolf Krack, Using Solidification Simulations for Optimising Die Cooling Systems, FTJ July/August 2008

19-08 Mark Littler, Simulation Software Eliminates Die Casting Scrap, ECS Casting Innovations, July/August 2008

13-08 T. Yoshimura, K. Yano, T. Fukui, S. Yamamoto, S. Nishido, M. Watanabe and Y. Nemoto, Optimum Design of Die Casting Plunger Tip Considering Air Entrainment, Proceedings of 10th Asian Foundry Congress (AFC10), Nagoya, Japan, May 2008

08-08 Stephen Instone, Andreas Buchholz and Gerd-Ulrich Gruen, Inclusion Transport Phenomena in Casting Furnaces, Light Metals 2008, TMS (The Minerals, Metals & Materials Society), 2008

07-08 P. Scarber, Jr., H. Littleton, Simulating Macro-Porosity in Aluminum Lost Foam Casting, AFS Transactions 2008 © American Foundry Society, CastExpo ’08, Atlanta, Georgia, May 2008

06-08 A. Reikher, H. Gerber and A. Starobin, Multi-Stage Plunger Deceleration System, CastExpo ’08, NADCA, Atlanta, Georgia, May 2008

05-08 Amol Palekar, Andrei Starobin, Alexander Reikher, Die-casting end-of-fill and drop forge viscometer flow transients examined with a coupled-motion numerical model, 68th World Foundry Congress, Chennai, India, February 2008

03-08 Petri J. Väyrynen, Sami K. Vapalahti and Seppo J. Louhenkilpi, On Validation of Mathematical Fluid Flow Models for Simulation of Tundish Water Models and Industrial Examples, AISTech 2008, May 2008

53-07   A. Kermanpur, Sh. Mahmoudi and A. Hajipour, Three-dimensional Numerical Simulation of Metal Flow and Solidification in the Multi-cavity Casting Moulds of Automotive Components, International Journal of Iron & Steel Society of Iran, Article 2, Volume 4, Issue 1, Summer and Autumn 2007, pages 8-15.

36-07 Duque Mesa A. F., Herrera J., Cruz L.J., Fernández G.P. y Martínez H.V., Caracterización Defectológica de Piezas Fundida por Lost Foam Casting Mediante Simulación Numérica, 8° Congreso Iberoamericano de Ingenieria Mecanica, Cusco, Peru, 23 al 25 de Octubre de 2007 (in Spanish)

27-07 A.Y. Korotchenko, A.M. Zarubin, I.A.Korotchenko, Modeling of High Pressure Die Casting Filling, Russian Foundryman, December 2007, pp 15-19. (in Russian)

26-07 I.N. Volnov, Modeling of Casting Processes with Variable Geometry, Russian Foundryman, November 2007, pp 27-30. (in Russian)

16-07 P. Väyrynen, S. Vapalahti, S. Louhenkilpi, L. Chatburn, M. Clark, T. Wagner, Tundish Flow Model Tuning and Validation – Steady State and Transient Casting Situations, STEELSIM 2007, Graz/Seggau, Austria, September 12-14 2007

11-07 Marco Actis Grande, Computer Simulation of the Investment Casting Process – Widening of the Filling Step, Santa Fe Symposium on Jewelry Manufacturing Technology, May 2007

09-07 Alexandre Reikher and Michael Barkhudarov, Casting: An Analytical Approach, Springer, 1st edition, August 2007, Hardcover ISBN: 978-1-84628-849-4. U.S. Order Form; Europe Order Form.

07-07 I.N. Volnov, Casting Modeling Systems – Current State, Problems and Perspectives, (in Russian), Liteyshik Rossii (Russian Foundryman), June 2007

05-07 A.N. Turchin, D.G. Eskin, and L. Katgerman, Solidification under Forced-Flow Conditions in a Shallow Cavity, DOI: 10.1007/s1161-007-9183-9, © The Minerals, Metals & Materials Society and ASM International 2007

04-07 A.N. Turchin, M. Zuijderwijk, J. Pool, D.G. Eskin, and L. Katgerman, Feathery grain growth during solidification under forced flow conditions, © Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. DOI: 10.1016/j.actamat.2007.02.030, April 2007

03-07 S. Kuyucak, Sponsored Research – Clean Steel Casting Production—Evaluation of Laboratory Castings, Transactions of the American Foundry Society, Volume 115, 111th Metalcasting Congress, May 2007

02-07 Fu-Yuan Hsu, Mark R. Jolly and John Campbell, The Design of L-Shaped Runners for Gravity Casting, Shape Casting: 2nd International Symposium, Edited by Paul N. Crepeau, Murat Tiryakioðlu and John Campbell, TMS (The Minerals, Metals & Materials Society), Orlando, FL, Feb 2007

30-06 X.J. Liu, S.H. Bhavnani, R.A. Overfelt, Simulation of EPS foam decomposition in the lost foam casting process, Journal of Materials Processing Technology 182 (2007) 333–342, © 2006 Elsevier B.V. All rights reserved.

25-06 Michael Barkhudarov and Gengsheng Wei, Modeling Casting on the Move, Modern Casting, August 2006; Modeling of Casting Processes with Variable Geometry, Russian Foundryman, December 2007, pp 10-15. (in Russian)

24-06 P. Scarber, Jr. and C.E. Bates, Simulation of Core Gas Production During Mold Fill, © 2006 American Foundry Society

7-06 M.Y.Smirnov, Y.V.Golenkov, Manufacturing of Cast Iron Bath Tubs Castings using Vacuum-Process in Russia, Russia’s Foundryman, July 2006. In Russian.

6-06 M. Barkhudarov, and G. Wei, Modeling of the Coupled Motion of Rigid Bodies in Liquid Metal, Modeling of Casting, Welding and Advanced Solidification Processes – XI, May 28 – June 2, 2006, Opio, France, eds. Ch.-A. Gandin and M. Bellet, pp 71-78, 2006.

2-06 J.-C. Gebelin, M.R. Jolly and F.-Y. Hsu, ‘Designing-in’ Controlled Filling Using Numerical Simulation for Gravity Sand Casting of Aluminium Alloys, Int. J. Cast Met. Res., 2006, Vol.19 No.1

1-06 Michael Barkhudarov, Using Simulation to Control Microporosity Reduces Die Iterations, Die Casting Engineer, January 2006, pp. 52-54

30-05 H. Xue, K. Kabiri-Bamoradian, R.A. Miller, Modeling Dynamic Cavity Pressure and Impact Spike in Die Casting, Cast Expo ’05, April 16-19, 2005

22-05 Blas Melissari & Stavros A. Argyropoulous, Measurement of Magnitude and Direction of Velocity in High-Temperature Liquid Metals; Part I, Mathematical Modeling, Metallurgical and Materials Transactions B, Volume 36B, October 2005, pp. 691-700

21-05 M.R. Jolly, State of the Art Review of Use of Modeling Software for Casting, TMS Annual Meeting, Shape Casting: The John Campbell Symposium, Eds, M. Tiryakioglu & P.N Crepeau, TMS, Warrendale, PA, ISBN 0-87339-583-2, Feb 2005, pp 337-346

20-05 J-C Gebelin, M.R. Jolly & F-Y Hsu, ‘Designing-in’ Controlled Filling Using Numerical Simulation for Gravity Sand Casting of Aluminium Alloys, TMS Annual Meeting, Shape Casting: The John Campbell Symposium, Eds, M. Tiryakioglu & P.N Crepeau, TMS, Warrendale, PA, ISBN 0-87339-583-2, Feb 2005, pp 355-364

19-05 F-Y Hsu, M.R. Jolly & J Campbell, Vortex Gate Design for Gravity Castings, TMS Annual Meeting, Shape Casting: The John Campbell Symposium, Eds, M. Tiryakioglu & P.N Crepeau, TMS, Warrendale, PA, ISBN 0-87339-583-2, Feb 2005, pp 73-82

18-05 M.R. Jolly, Modelling the Investment Casting Process: Problems and Successes, Japanese Foundry Society, JFS, Tokyo, Sept. 2005

13-05 Xiaogang Yang, Xiaobing Huang, Xiaojun Dai, John Campbell and Joe Tatler, Numerical Modelling of the Entrainment of Oxide Film Defects in Filling of Aluminium Alloy Castings, International Journal of Cast Metals Research, 17 (6), 2004, 321-331

10-05 Carlos Evaristo Esparza, Martha P. Guerro-Mata, Roger Z. Ríos-Mercado, Optimal Design of Gating Systems by Gradient Search Methods, Computational Materials Science, October 2005

6-05 Birgit Hummler-Schaufler, Fritz Hirning, Jurgen Schaufler, A World First for Hatz Diesel and Schaufler Tooling, Die Casting Engineer, May 2005, pp. 18-21

4-05 Rolf Krack, The W35 Topic—A World First, Die Casting World, March 2005, pp. 16-17

3-05 Joerg Frei, Casting Simulations Speed Up Development, Die Casting World, March 2005, p. 14

2-05 David Goettsch and Michael Barkhudarov, Analysis and Optimization of the Transient Stage of Stopper-Rod Pour, Shape Casting: The John Campbell Symposium, The Minerals, Metals & Materials Society, 2005

36-04  Ik Min Park, Il Dong Choi, Yong Ho Park, Development of Light-Weight Al Scroll Compressor for Car Air Conditioner, Materials Science Forum, Designing, Processing and Properties of Advanced Engineering Materials, 449-452, 149, March 2004.

32-04 D.H. Kirkwood and P.J Ward, Numerical Modelling of Semi-Solid Flow under Processing Conditions, steel research int. 75 (2004), No. 8/9

30-04 Haijing Mao, A Numerical Study of Externally Solidified Products in the Cold Chamber Die Casting Process, thesis: The Ohio State University, 2004 (Available upon request)

28-04 Z. Cao, Z. Yang, and X.L. Chen, Three-Dimensional Simulation of Transient GMA Weld Pool with Free Surface, Supplement to the Welding Journal, June 2004.

23-04 State of the Art Use of Computational Modelling in the Foundry Industry, 3rd International Conference Computational Modelling of Materials III, Sicily, Italy, June 2004, Advances in Science and Technology,  Eds P. Vincenzini & A Lami, Techna Group Srl, Italy, ISBN: 88-86538-46-4, Part B, pp 479-490

22-04 Jerry Fireman, Computer Simulation Helps Reduce Scrap, Die Casting Engineer, May 2004, pp. 46-49

21-04 Joerg Frei, Simulation—A Safe and Quick Way to Good Components, Aluminium World, Volume 3, Issue 2, pp. 42-43

20-04 J.-C. Gebelin, M.R. Jolly, A. M. Cendrowicz, J. Cirre and S. Blackburn, Simulation of Die Filling for the Wax Injection Process – Part II Numerical Simulation, Metallurgical and Materials Transactions, Volume 35B, August 2004

14-04 Sayavur I. Bakhtiyarov, Charles H. Sherwin, and Ruel A. Overfelt, Hot Distortion Studies In Phenolic Urethane Cold Box System, American Foundry Society, 108th Casting Congress, June 12-15, 2004, Rosemont, IL, USA

13-04 Sayavur I. Bakhtiyarov and Ruel A. Overfelt, First V-Process Casting of Magnesium, American Foundry Society, 108th Casting Congress, June 12-15, 2004, Rosemont, IL, USA

5-04 C. Schlumpberger & B. Hummler-Schaufler, Produktentwicklung auf hohem Niveau (Product Development on a High Level), Druckguss Praxis, January 2004, pp 39-42 (in German).

3-04 Charles Bates, Dealing with Defects, Foundry Management and Technology, February 2004, pp 23-25

1-04 Laihua Wang, Thang Nguyen, Gary Savage and Cameron Davidson, Thermal and Flow Modeling of Ladling and Injection in High Pressure Die Casting Process, International Journal of Cast Metals Research, vol. 16 No 4 2003, pp 409-417

2-03 J-C Gebelin, AM Cendrowicz, MR Jolly, Modeling of the Wax Injection Process for the Investment Casting Process – Prediction of Defects, presented at the Third International Conference on Computational Fluid Dynamics in the Minerals and Process Industries, December 10-12, 2003, Melbourne, Australia, pp. 415-420

29-03 C. W. Hirt, Modeling Shrinkage Induced Micro-porosity, Flow Science Technical Note (FSI-03-TN66)

28-03 Thixoforming at the University of Sheffield, Diecasting World, September 2003, pp 11-12

26-03 William Walkington, Gas Porosity-A Guide to Correcting the Problems, NADCA Publication: 516

22-03 G F Yao, C W Hirt, and M Barkhudarov, Development of a Numerical Approach for Simulation of Sand Blowing and Core Formation, in Modeling of Casting, Welding, and Advanced Solidification Process-X”, Ed. By Stefanescu et al pp. 633-639, 2003

21-03 E F Brush Jr, S P Midson, W G Walkington, D T Peters, J G Cowie, Porosity Control in Copper Rotor Die Castings, NADCA Indianapolis Convention Center, Indianapolis, IN September 15-18, 2003, T03-046

12-03 J-C Gebelin & M.R. Jolly, Modeling Filters in Light Alloy Casting Processes,  Trans AFS, 2002, 110, pp. 109-120

11-03 M.R. Jolly, Casting Simulation – How Well Do Reality and Virtual Casting Match – A State of the Art Review, Intl. J. Cast Metals Research, 2002, 14, pp. 303-313

10-03 Gebelin., J-C and Jolly, M.R., Modeling of the Investment Casting Process, Journal of  Materials Processing Tech., Vol. 135/2-3, pp. 291 – 300

9-03 Cox, M, Harding, R.A. and Campbell, J., Optimised Running System Design for Bottom Filled Aluminium Alloy 2L99 Investment Castings, J. Mat. Sci. Tech., May 2003, Vol. 19, pp. 613-625

8-03 Von Alexander Schrey and Regina Reek, Numerische Simulation der Kernherstellung, (Numerical Simulation of Core Blowing), Giesserei, June 2003, pp. 64-68 (in German)

7-03 J. Zuidema Jr., L Katgerman, Cyclone separation of particles in aluminum DC Casting, Proceedings from the Tenth International Conference on Modeling of Casting, Welding and Advanced Solidification Processes, Destin, FL, May 2003, pp. 607-614

6-03 Jean-Christophe Gebelin and Mark Jolly, Numerical Modeling of Metal Flow Through Filters, Proceedings from the Tenth International Conference on Modeling of Casting, Welding and Advanced Solidification Processes, Destin, FL, May 2003, pp. 431-438

5-03 N.W. Lai, W.D. Griffiths and J. Campbell, Modelling of the Potential for Oxide Film Entrainment in Light Metal Alloy Castings, Proceedings from the Tenth International Conference on Modeling of Casting, Welding and Advanced Solidification Processes, Destin, FL, May 2003, pp. 415-422

21-02 Boris Lukezic, Case History: Process Modeling Solves Die Design Problems, Modern Casting, February 2003, P 59

20-02 C.W. Hirt and M.R. Barkhudarov, Predicting Defects in Lost Foam Castings, Modern Casting, December 2002, pp 31-33

19-02 Mark Jolly, Mike Cox, Ric Harding, Bill Griffiths and John Campbell, Quiescent Filling Applied to Investment Castings, Modern Casting, December 2002 pp. 36-38

18-02 Simulation Helps Overcome Challenges of Thin Wall Magnesium Diecasting, Foundry Management and Technology, October 2002, pp 13-15

17-02 G Messmer, Simulation of a Thixoforging Process of Aluminum Alloys with FLOW-3D, Institute for Metal Forming Technology, University of Stuttgart

16-02 Barkhudarov, Michael, Computer Simulation of Lost Foam Process, Casting Simulation Background and Examples from Europe and the USA, World Foundrymen Organization, 2002, pp 319-324

15-02 Barkhudarov, Michael, Computer Simulation of Inclusion Tracking, Casting Simulation Background and Examples from Europe and the USA, World Foundrymen Organization, 2002, pp 341-346

14-02 Barkhudarov, Michael, Advanced Simulation of the Flow and Heat Transfer of an Alternator Housing, Casting Simulation Background and Examples from Europe and the USA, World Foundrymen Organization, 2002, pp 219-228

8-02 Sayavur I. Bakhtiyarov, and Ruel A. Overfelt, Experimental and Numerical Study of Bonded Sand-Air Two-Phase Flow in PUA Process, Auburn University, 2002 American Foundry Society, AFS Transactions 02-091, Kansas City, MO

7-02 A Habibollah Zadeh, and J Campbell, Metal Flow Through a Filter System, University of Birmingham, 2002 American Foundry Society, AFS Transactions 02-020, Kansas City, MO

6-02 Phil Ward, and Helen Atkinson, Final Report for EPSRC Project: Modeling of Thixotropic Flow of Metal Alloys into a Die, GR/M17334/01, March 2002, University of Sheffield

5-02 S. I. Bakhtiyarov and R. A. Overfelt, Numerical and Experimental Study of Aluminum Casting in Vacuum-sealed Step Molding, Auburn University, 2002 American Foundry Society, AFS Transactions 02-050, Kansas City, MO

4-02 J. C. Gebelin and M. R. Jolly, Modelling Filters in Light Alloy Casting Processes, University of Birmingham, 2002 American Foundry Society AFS Transactions 02-079, Kansas City, MO

3-02 Mark Jolly, Mike Cox, Jean-Christophe Gebelin, Sam Jones, and Alex Cendrowicz, Fundamentals of Investment Casting (FOCAST), Modelling the Investment Casting Process, Some preliminary results from the UK Research Programme, IRC in Materials, University of Birmingham, UK, AFS2001

49-01   Hua Bai and Brian G. Thomas, Bubble formation during horizontal gas injection into downward-flowing liquid, Metallurgical and Materials Transactions B, Vol. 32, No. 6, pp. 1143-1159, 2001. doi.org/10.1007/s11663-001-0102-y

45-01 Jan Zuidema; Laurens Katgerman; Ivo J. Opstelten;Jan M. Rabenberg, Secondary Cooling in DC Casting: Modelling and Experimental Results, TMS 2001, New Orleans, Louisianna, February 11-15, 2001

43-01 James Andrew Yurko, Fluid Flow Behavior of Semi-Solid Aluminum at High Shear Rates,Ph.D. thesis; Massachusetts Institute of Technology, June 2001. Abstract only; full thesis available at http://dspace.mit.edu/handle/1721.1/8451 (for a fee).

33-01 Juang, S.H., CAE Application on Design of Die Casting Dies, 2001 Conference on CAE Technology and Application, Hsin-Chu, Taiwan, November 2001, (article in Chinese with English-language abstract)

32-01 Juang, S.H. and C. M. Wang, Effect of Feeding Geometry on Flow Characteristics of Magnesium Die Casting by Numerical Analysis, The Preceedings of 6th FADMA Conference, Taipei, Taiwan, July 2001, Chinese language with English abstract

26-01 C. W. Hirt., Predicting Defects in Lost Foam Castings, December 13, 2001

21-01 P. Scarber Jr., Using Liquid Free Surface Areas as a Predictor of Reoxidation Tendency in Metal Alloy Castings, presented at the Steel Founders’ Society of American, Technical and Operating Conference, October 2001

20-01 P. Scarber Jr., J. Griffin, and C. E. Bates, The Effect of Gating and Pouring Practice on Reoxidation of Steel Castings, presented at the Steel Founders’ Society of American, Technical and Operating Conference, October 2001

19-01 L. Wang, T. Nguyen, M. Murray, Simulation of Flow Pattern and Temperature Profile in the Shot Sleeve of a High Pressure Die Casting Process, CSIRO Manufacturing Science and Technology, Melbourne, Victoria, Australia, Presented by North American Die Casting Association, Oct 29-Nov 1, 2001, Cincinnati, To1-014

18-01 Rajiv Shivpuri, Venkatesh Sankararaman, Kaustubh Kulkarni, An Approach at Optimizing the Ingate Design for Reducing Filling and Shrinkage Defects, The Ohio State University, Columbus, OH, Presented by North American Die Casting Association, Oct 29-Nov 1, 2001, Cincinnati, TO1-052

5-01 Michael Barkhudarov, Simulation Helps Overcome Challenges of Thin Wall Magnesium Diecasting, Diecasting World, March 2001, pp. 5-6

2-01 J. Grindling, Customized CFD Codes to Simulate Casting of Thermosets in Full 3D, Electrical Manufacturing and Coil Winding 2000 Conference, October 31-November 2, 20

20-00 Richard Schuhmann, John Carrig, Thang Nguyen, Arne Dahle, Comparison of Water Analogue Modelling and Numerical Simulation Using Real-Time X-Ray Flow Data in Gravity Die Casting, Australian Die Casting Association Die Casting 2000 Conference, September 3-6, 2000, Melbourne, Victoria, Australia

15-00 M. Sirvio, Vainola, J. Vartianinen, M. Vuorinen, J. Orkas, and S. Devenyi, Fluid Flow Analysis for Designing Gating of Aluminum Castings, Proc. NADCA Conf., Rosemont, IL, Nov 6-8, 1999

14-00 X. Yang, M. Jolly, and J. Campbell, Reduction of Surface Turbulence during Filling of Sand Castings Using a Vortex-flow Runner, Conference for Modeling of Casting, Welding, and Advanced Solidification Processes IX, Aachen, Germany, August 2000

13-00 H. S. H. Lo and J. Campbell, The Modeling of Ceramic Foam Filters, Conference for Modeling of Casting, Welding, and Advanced Solidification Processes IX, Aachen, Germany, August 2000

12-00 M. R. Jolly, H. S. H. Lo, M. Turan and J. Campbell, Use of Simulation Tools in the Practical Development of a Method for Manufacture of Cast Iron Camshafts,” Conference for Modeling of Casting, Welding, and Advanced Solidification Processes IX, Aachen, Germany, August, 2000

14-99 J Koke, and M Modigell, Time-Dependent Rheological Properties of Semi-solid Metal Alloys, Institute of Chemical Engineering, Aachen University of Technology, Mechanics of Time-Dependent Materials 3: 15-30, 1999

12-99 Grun, Gerd-Ulrich, Schneider, Wolfgang, Ray, Steven, Marthinusen, Jan-Olaf, Recent Improvements in Ceramic Foam Filter Design by Coupled Heat and Fluid Flow Modeling, Proc TMS Annual Meeting, 1999, pp. 1041-1047

10-99 Bongcheol Park and Jerald R. Brevick, Computer Flow Modeling of Cavity Pre-fill Effects in High Pressure Die Casting, NADCA Proceedings, Cleveland T99-011, November, 1999

8-99 Brad Guthrie, Simulation Reduces Aluminum Die Casting Cost by Reducing Volume, Die Casting Engineer Magazine, September/October 1999, pp. 78-81

7-99 Fred L. Church, Virtual Reality Predicts Cast Metal Flow, Modern Metals, September, 1999, pp. 67F-J

19-98 Grun, Gerd-Ulrich, & Schneider, Wolfgang, Numerical Modeling of Fluid Flow Phenomena in the Launder-integrated Tool Within Casting Unit Development, Proc TMS Annual Meeting, 1998, pp. 1175-1182

18-98 X. Yang & J. Campbell, Liquid Metal Flow in a Pouring Basin, Int. J. Cast Metals Res, 1998, 10, pp. 239-253

15-98 R. Van Tol, Mould Filling of Horizontal Thin-Wall Castings, Delft University Press, The Netherlands, 1998

14-98 J. Daughtery and K. A. Williams, Thermal Modeling of Mold Material Candidates for Copper Pressure Die Casting of the Induction Motor Rotor Structure, Proc. Int’l Workshop on Permanent Mold Casting of Copper-Based Alloys, Ottawa, Ontario, Canada, Oct. 15-16, 1998

10-98 C. W. Hirt, and M.R. Barkhudarov, Lost Foam Casting Simulation with Defect Prediction, Flow Science Inc, presented at Modeling of Casting, Welding and Advanced Solidification Processes VIII Conference, June 7-12, 1998, Catamaran Hotel, San Diego, California

9-98 M. R. Barkhudarov and C. W. Hirt, Tracking Defects, Flow Science Inc, presented at the 1st International Aluminum Casting Technology Symposium, 12-14 October 1998, Rosemont, IL

5-98 J. Righi, Computer Simulation Helps Eliminate Porosity, Die Casting Management Magazine, pp. 36-38, January 1998

3-98 P. Kapranos, M. R. Barkhudarov, D. H. Kirkwood, Modeling of Structural Breakdown during Rapid Compression of Semi-Solid Alloy Slugs, Dept. Engineering Materials, The University of Sheffield, Sheffield S1 3JD, U.K. and Flow Science Inc, USA, Presented at the 5th International Conference Semi-Solid Processing of Alloys and Composites, Colorado School of Mines, Golden, CO, 23-25 June 1998

1-98 U. Jerichow, T. Altan, and P. R. Sahm, Semi Solid Metal Forming of Aluminum Alloys-The Effect of Process Variables Upon Material Flow, Cavity Fill and Mechanical Properties, The Ohio State University, Columbus, OH, published in Die Casting Engineer, p. 26, Jan/Feb 1998

8-97 Michael Barkhudarov, High Pressure Die Casting Simulation Using FLOW-3D, Die Casting Engineer, 1997

15-97 M. R. Barkhudarov, Advanced Simulation of the Flow and Heat Transfer Process in Simultaneous Engineering, Flow Science report, presented at the Casting 1997 – International ADI and Simulation Conference, Helsinki, Finland, May 28-30, 1997

14-97 M. Ranganathan and R. Shivpuri, Reducing Scrap and Increasing Die Life in Low Pressure Die Casting through Flow Simulation and Accelerated Testing, Dept. Welding and Systems Engineering, Ohio State University, Columbus, OH, presented at 19th International Die Casting Congress & Exposition, November 3-6, 1997

13-97 J. Koke, Modellierung und Simulation der Fließeigenschaften teilerstarrter Metallegierungen, Livt Information, Institut für Verfahrenstechnik, RWTH Aachen, October 1997

10-97 J. P. Greene and J. O. Wilkes, Numerical Analysis of Injection Molding of Glass Fiber Reinforced Thermoplastics – Part 2 Fiber Orientation, Body-in-White Center, General Motors Corp. and Dept. Chemical Engineering, University of Michigan, Polymer Engineering and Science, Vol. 37, No. 6, June 1997

9-97 J. P. Greene and J. O. Wilkes, Numerical Analysis of Injection Molding of Glass Fiber Reinforced Thermoplastics. Part 1 – Injection Pressures and Flow, Manufacturing Center, General Motors Corp. and Dept. Chemical Engineering, University of Michigan, Polymer Engineering and Science, Vol. 37, No. 3, March 1997

8-97 H. Grazzini and D. Nesa, Thermophysical Properties, Casting Simulation and Experiments for a Stainless Steel, AT Systemes (Renault) report, presented at the Solidification Processing ’97 Conference, July 7-10, 1997, Sheffield, U.K.

7-97 R. Van Tol, L. Katgerman and H. E. A. Van den Akker, Horizontal Mould Filling of a Thin Wall Aluminum Casting, Laboratory of Materials report, Delft University, presented at the Solidification Processing ’97 Conference, July 7-10, 1997, Sheffield, U.K.

6-97 M. R. Barkhudarov, Is Fluid Flow Important for Predicting Solidification, Flow Science report, presented at the Solidification Processing ’97 Conference, July 7-10, 1997, Sheffield, U.K.

22-96 Grun, Gerd-Ulrich & Schneider, Wolfgang, 3-D Modeling of the Start-up Phase of DC Casting of Sheet Ingots, Proc TMS Annual Meeting, 1996, pp. 971-981

9-96 M. R. Barkhudarov and C. W. Hirt, Thixotropic Flow Effects under Conditions of Strong Shear, Flow Science report FSI96-00-2, to be presented at the “Materials Week ’96” TMS Conference, Cincinnati, OH, 7-10 October 1996

4-96 C. W. Hirt, A Computational Model for the Lost Foam Process, Flow Science final report, February 1996 (FSI-96-57-R2)

3-96 M. R. Barkhudarov, C. L. Bronisz, C. W. Hirt, Three-Dimensional Thixotropic Flow Model, Flow Science report, FSI-96-00-1, published in the proceedings of (pp. 110- 114) and presented at the 4th International Conference on Semi-Solid Processing of Alloys and Composites, The University of Sheffield, 19-21 June 1996

1-96 M. R. Barkhudarov, J. Beech, K. Chang, and S. B. Chin, Numerical Simulation of Metal/Mould Interfacial Heat Transfer in Casting, Dept. Mech. & Process Engineering, Dept. Engineering Materials, University of Sheffield and Flow Science Inc, 9th Int. Symposium on Transport Phenomena in Thermal-Fluid Engineering, June 25-28, 1996, Singapore

11-95 Barkhudarov, M. R., Hirt, C.W., Casting Simulation Mold Filling and Solidification-Benchmark Calculations Using FLOW-3D, Modeling of Casting, Welding, and Advanced Solidification Processes VII, pp 935-946

10-95 Grun, Gerd-Ulrich, & Schneider, Wolfgang, Optimal Design of a Distribution Pan for Level Pour Casting, Proc TMS Annual Meeting, 1995, pp. 1061-1070

9-95 E. Masuda, I. Itoh, K. Haraguchi, Application of Mold Filling Simulation to Die Casting Processes, Honda Engineering Co., Ltd., Tochigi, Japan, presented at the Modelling of Casting, Welding and Advanced Solidification Processes VII, The Minerals, Metals & Materials Society, 1995

6-95 K. Venkatesan, Experimental and Numerical Investigation of the Effect of Process Parameters on the Erosive Wear of Die Casting Dies, presented for Ph.D. degree at Ohio State University, 1995

5-95 J. Righi, A. F. LaCamera, S. A. Jones, W. G. Truckner, T. N. Rouns, Integration of Experience and Simulation Based Understanding in the Die Design Process, Alcoa Technical Center, Alcoa Center, PA 15069, presented by the North American Die Casting Association, 1995

2-95 K. Venkatesan and R. Shivpuri, Numerical Simulation and Comparison with Water Modeling Studies of the Inertia Dominated Cavity Filling in Die Casting, NUMIFORM, 1995

1-95 K. Venkatesan and R. Shivpuri, Numerical Investigation of the Effect of Gate Velocity and Gate Size on the Quality of Die Casting Parts, NAMRC, 1995.

15-94 D. Liang, Y. Bayraktar, S. A. Moir, M. Barkhudarov, and H. Jones, Primary Silicon Segregation During Isothermal Holding of Hypereutectic AI-18.3%Si Alloy in the Freezing Range, Dept. of Engr. Materials, U. of Sheffield, Metals and Materials, February 1994

13-94 Deniece Korzekwa and Paul Dunn, A Combined Experimental and Modeling Approach to Uranium Casting, Materials Division, Los Alamos National Laboratory, presented at the Symposium on Liquid Metal Processing and Casting, El Dorado Hotel, Santa Fe, New Mexico, 1994

12-94 R. van Tol, H. E. A. van den Akker and L. Katgerman, CFD Study of the Mould Filling of a Horizontal Thin Wall Aluminum Casting, Delft University of Technology, Delft, The Netherlands, HTD-Vol. 284/AMD-Vol. 182, Transport Phenomena in Solidification, ASME 1994

11-94 M. R. Barkhudarov and K. A. Williams, Simulation of ‘Surface Turbulence’ Fluid Phenomena During the Mold Filling Phase of Gravity Castings, Flow Science Technical Note #41, November 1994 (FSI-94-TN41)

10-94 M. R. Barkhudarov and S. B. Chin, Stability of a Numerical Algorithm for Gas Bubble Modelling, University of Sheffield, Sheffield, U.K., International Journal for Numerical Methods in Fluids, Vol. 19, 415-437 (1994)

16-93 K. Venkatesan and R. Shivpuri, Numerical Simulation of Die Cavity Filling in Die Castings and an Evaluation of Process Parameters on Die Wear, Dept. of Industrial Systems Engineering, Presented by: N.A. Die Casting Association, Cleveland, Ohio, October 18-21, 1993

15-93 K. Venkatesen and R. Shivpuri, Numerical Modeling of Filling and Solidification for Improved Quality of Die Casting: A Literature Survey (Chapters II and III), Engineering Research Center for Net Shape Manufacturing, Report C-93-07, August 1993, Ohio State University

1-93 P-E Persson, Computer Simulation of the Solidification of a Hub Carrier for the Volvo 800 Series, AB Volvo Technological Development, Metals Laboratory, Technical Report No. LM 500014E, Jan. 1993

13-92 D. R. Korzekwa, M. A. K. Lewis, Experimentation and Simulation of Gravity Fed Lead Castings, in proceedings of a TMS Symposium on Concurrent Engineering Approach to Materials Processing, S. N. Dwivedi, A. J. Paul and F. R. Dax, eds., TMS-AIME Warrendale, p. 155 (1992)

12-92 M. A. K. Lewis, Near-Net-Shaiconpe Casting Simulation and Experimentation, MST 1992 Review, Los Alamos National Laboratory

2-92 M. R. Barkhudarov, H. You, J. Beech, S. B. Chin, D. H. Kirkwood, Validation and Development of FLOW-3D for Casting, School of Materials, University of Sheffield, Sheffield, UK, presented at the TMS/AIME Annual Meeting, San Diego, CA, March 3, 1992

1-92 D. R. Korzekwa and L. A. Jacobson, Los Alamos National Laboratory and C.W. Hirt, Flow Science Inc, Modeling Planar Flow Casting with FLOW-3D, presented at the TMS/AIME Annual Meeting, San Diego, CA, March 3, 1992

12-91 R. Shivpuri, M. Kuthirakulathu, and M. Mittal, Nonisothermal 3-D Finite Difference Simulation of Cavity Filling during the Die Casting Process, Dept. Industrial and Systems Engineering, Ohio State University, presented at the 1991 Winter Annual ASME Meeting, Atlanta, GA, Dec. 1-6, 1991

3-91 C. W. Hirt, FLOW-3D Study of the Importance of Fluid Momentum in Mold Filling, presented at the 18th Annual Automotive Materials Symposium, Michigan State University, Lansing, MI, May 1-2, 1991 (FSI-91-00-2)

11-90 N. Saluja, O.J. Ilegbusi, and J. Szekely, On the Calculation of the Electromagnetic Force Field in the Circular Stirring of Metallic Melts, accepted in J. Appl. Physics, 1990

10-90 N. Saluja, O. J. Ilegbusi, and J. Szekely, On the Calculation of the Electromagnetic Force Field in the Circular Stirring of Metallic Molds in Continuous Castings, presented at the 6th Iron and Steel Congress of the Iron and Steel Institute of Japan, Nagoya, Japan, October 1990

9-90 N. Saluja, O. J. Ilegbusi, and J. Szekely, Fluid Flow in Phenomena in the Electromagnetic Stirring of Continuous Casting Systems, Part I. The Behavior of a Cylindrically Shaped, Laboratory Scale Installation, accepted for publication in Steel Research, 1990

8-89 C. W. Hirt, Gravity-Fed Casting, Flow Science Technical Note #20, July 1989 (FSI-89-TN20)

6-89 E. W. M. Hansen and F. Syvertsen, Numerical Simulation of Flow Behaviour in Moldfilling for Casting Analysis, SINTEF-Foundation for Scientific and Industrial Research at the Norwegian Institute of Technology, Trondheim, Norway, Report No. STS20 A89001, June 1989

1-88 C. W. Hirt and R. P. Harper, Modeling Tests for Casting Processes, Flow Science report, Jan. 1988 (FSI-88-38-01)

2-87 C. W. Hirt, Addition of a Solidification/Melting Model to FLOW-3D, Flow Science report, April 1987 (FSI-87-33-1)

수자원 및 환경 모델 / Water & Environmental Models

물 및 환경 모델

3D 자유 표면 흐름을 모델링 할 때 FLOW-3D의 고유한 강점은 복잡한 수리 환경분야에 쉽게 적용할 수 있는 최적화된 플랫폼이 제공된다는 점 입니다.  FLOW-3D 소프트웨어는 수십년 동안 복잡한 흐름 역학,  흐름/구조 상호 작용 및 환경 예측을 위해 업계 전문가들이 사용해 왔습니다. FLOW-3D의 적용에는 수처리 시설물 , 하천 계획 및 복원 , 댐 안전, 수력 및 방수 작업 , 설계 및 최적화, 저수지 유지 관리 및 계획, 해안 및 하구 공학 분야가 포함됩니다.

독특한 모델링 도구

하이브리드 3D/천수(shallow water) 해석기능은 계산상 매우 효율적이고 정확합니다. 천수(shallow water) 모델 솔루션은 대규모 도메인 (수 킬로미터 이상)에서의 유동 모델링을 허용하고 hydraulic jumps 및 침전물 이송을 정확하게 포착합니다. 브리지 교각 및 방수로와 같이 수직 흐름 효과가 중요한 지역의 3D 솔루션과 매끄럽게 연결됩니다. 또한, 등각 메쉬 (conformal meshing)는 효율적인 메쉬 생성을 능률화하고 사용자가 기하학적인 세부 사항을 쉽게 해결할 수 있게 합니다.

강력한 물리 모델

FLOW-3D는 퇴적물 정련 및 수송, 밀도 층화 및 혼합, 기포 및 캐비테이션, 증발 및 상 변화, 화학적 예측 및 수송, 다공성 매체를 포함하는 강력한 물리 모델을 추가로 포함합니다. 정확한 3 차원 유동 모델링 및 물리학 패키지를 통해 FLOW-3D 는 매우 복잡한 환경에서도 정확하고 효과적인 시뮬레이션을 결과를 제공합니다. 제공된 사례는 미세한 뉴트리안 광산 꼬리끌림의 영향을받는 세밀한 3D 유압 영역을 매핑하고 파고를 예측하는 것입니다. FLOW-3D 의 다 기능성은 사용자가 하나의 응용 프로그램에서 다음 응용 프로그램으로 부드럽게 탐색 할 수있게하며, 가장 복잡한 문제에 대한 탁월한 정확성과 사용 편의성을 제공합니다.

Coating Bibliography

아래는 코팅 참고 문헌의 기술 문서 모음입니다. 
이 모든 논문은 FLOW-3D  결과를 포함하고 있습니다. FLOW-3D를 사용하여 코팅 공정을 성공적으로 시뮬레이션  하는 방법에 대해 자세히 알아보십시오.

Coating Bibliography

2024년 11월 20일 Update

98-24 Fabiano I. Indicatti, Bo Cheng, Michael Rädler, Elisabeth Stammen, Klaus Dilger, Experimental and numerical investigation of the squeegee process during stencil printing of thick adhesive sealings, The Journal of Adhesion, 2024. doi.org/10.1080/00218464.2024.2356105

130-22   Md Didarul Islam, Himendra Perera, Benjamin Black, Matthew Phillips, Muh-Jang Chen, Greyson Hodges, Allyce Jackman, Yuxuan Liu, Chang-Jin Kim, Mohammed Zikry, Saad Khan, Yong Zhu, Mark Pankow, Jong Eun Ryu, Template-free scalable fabrication of linearly periodic microstructures by controlling ribbing defects phenomenon in forward roll coating for multifunctional applications, Advanced Materials Interfaces, 9.27; 2201237, 2022. doi.org/10.1002/admi.202201237

03-21   Delong Jia, Peng Yi, Yancong Liu, Jiawei Sun, Shengbo Yue, Qi Zhao, Effect of laser­ textured groove wall interface on molybdenum coating diffusion and metallurgical bonding, Surface and Coatings Technology, 405; 126561, 2021. doi.org/10.1016/j.surfcoat.2020.126561

50-19     Peng Yi, Delong Jia, Xianghua Zhan, Pengun Xu, and Javad Mostaghimi, Coating solidification mechanism during plasma-sprayed filling the laser textured grooves, International Journal of Heat and Mass Transfer, Vol. 142, 2019. doi:10.1016/j.ijheatmasstransfer.2019.118451

01-19   Jelena Dinic and Vivek Sharma, Computational analysis of self-similar capillary-driven thinning and pinch-off dynamics during dripping using the volume-of-fluid method, Physics of Fluids, Vol. 31, 2019. doi: 10.1063/1.5061715

85-18   Zia Jang, Oliver Litfin and Antonio Delgado, A semi-analytical approach for prediction of volume flow rate in nip-fed reverse roll coating process, Proceedings in Applied Mathematics and Mechanics, Vol. 18, no. 1, Special Issue: 89th Annual Meeting of the International Association of Applied Mathematics and Mechanics, 2018. doi: 10.1002/pamm.201800317

80-14   Hiroaki Koyama, Kazuhiro Fukada, Yoshitaka Murakami, Satoshi Inoue, and Tatsuya Shimoda, Investigation of Roll-to-Sheet Imprinting for the Fabrication of Thin-film Transistor Electrodes, IEICE TRAN, ELECTRON, VOL.E97-C, NO.11, November 2014

46-14   Isabell Vogeler, Andreas Olbers, Bettina Willinger and Antonio Delgado, Numerical investigation of the onset of air entrainment in forward roll coating, 17th International Coating Science and Technology Symposium September 7-10, 2014 San Diego, CA, USA

17-12  Chi-Feng Lin, Bo-Kai Wang, Carlos Tiu and Ta-Jo Liu, On the Pinning of Downstream Meniscus for Slot Die Coating, Advances in Polymer Technology, Vol. 00, No. 0, 1-9 (2012) © 2012 Wiley Periodicals, Inc. Available online at Wiley.

01-11  Reid Chesterfield, Andrew Johnson, Charlie Lang, Matthew Stainer, and Jonathan Ziebarth, Solution-Coating Technology for AMOLED Displays, Information Display Magazine, 1/11 0362-0972/01/2011-024 © SID 2011.

61-09 Yi-Rong Chang, Chi-Feng Lin and Ta-Jo Liu, Start-up of slot die coating, Polymer Engineering and Science, Vol. 49, pp. 1158-1167, 2009. doi:10.1002/pen.21360

26-06  James M. Brethour, 3-D transient simulation of viscoelastic coating flows, 13th International Coating Science and Technology Symposium, September 2006, Denver, Colorado

19-06  Ivosevic, M., Cairncross, R. A., and Knight, R., 3D Predictions of Thermally Sprayed Polymer Splats Modeling Particle Acceleration, Heating and Deformation on Impact with a Flat Substrate, Int. J. of Heat and Mass Transfer, 49, pp. 3285 – 3297, 2006

9-06  M. Ivosevic, R. A. Cairncross, R. Knight, T. E. Twardowski, V. Gupta, Drexel University, Philadelphia, PA; J. A. Baldoni, Duke University, Durham, NC, Effect of Substrate Roughness on Splatting Behavior of HVOF Sprayed Polymer Particles Modeling and Experiments, International Thermal Spray Conference, Seattle, WA, May 2006.

26-05  Ivosevic, M., Cairncross, R. A., Knight, R., Impact Modeling of Thermally Sprayed Polymer Particles, Proc. International Thermal Spray Conference [ITSC-2005], Eds., DVS/IIW/ASM-TSS, Basel, Switzerland, May 2005.

11-05  Brethour, J., Simulation of Viscoelastic Coating Flows with a Volume-of-fluid Technique, in Proceedings of the 6th European Coating Symposium, Bradford, UK, 2005

1-05 C.W. Hirt, Electro-Hydrodynamics of Semi-Conductive Fluids: With Application to Electro-Spraying, Flow Science Technical Note #70, FSI-05-TN70

38-04 K.H. Ho and Y.Y. Zhao, Modelling thermal development of liquid metal flow on rotating disc in centrifugal atomisation, Materials Science and Engineering, A365, pp. 336-340, 2004. doi:10.1016/j.msea.2003.09.044

30-04  M. Ivosevic, R.A. Cairncross, and R. Knight, Impact Modeling of HVOF Sprayed Polymer Particles, Presented at the 12th International Coating Science and Technology Symposium, Rochester, New York, September 23-25, 2004

29-04  J.M. Brethour and C.W. Hirt, Stains Arising from Dried Liquid Drops, Presented at the 12th International Coating Science and Technology Symposium, Rochester, New York, September 23-25, 2004

20-03  James Brethour, Filling and Emptying of Gravure Cells–A CFD Analysis, Convertech Pacific October 2002, Vol. 10, No 4, p 34-37

4-03   M. Toivakka, Numerical Investigation of Droplet Impact Spreading in Spray Coating of Paper, In Proceedings of 2003 TAPPI 8th Advanced Coating Fundamentals Symposium, TAPPI Press, Atlanta, 2003

28-02  J.M. Brethour and H. Benkreira, Filling and Emptying of Gravure Cells—Experiment and CFD Comparison, 11th International Coating Science and Technology Symposium, September 23-25, 2002, Minneapolis, Minnesota

22-02  Hirt, C.W., and Brethour, J.M., Contact Line on Rough Surfaces with Application to Air Entrainment, Presented at the 11th International Coating Science and Technology Symposium, September 23-25, 2002, Minneapolis, Minnesota. Unpublished.

17-01  J. M. Brethour, C. W. Hirt, Moving Contact Lines on Rough Surfaces, 4th European Coating Symposium, 2001, Belgium

16-01  J. M. Brethour, Filling and Emptying of Gravure Cells–-A CFD Analysis, proceedings of the 4th European Coating Symposium 2001, October 1-4, 2001, Brussels, Belgium

26-00 Ronald H. Miller and Gary S. Strumolo, A Self-Consistent Transient Paint Simulation, Proceedings of IMEC2000: 2000 ASME International Mechanical Engineering Congress and Exposition, November 2000, Orlando, Florida

6-99  C. W. Hirt, Direct Computation of Dynamic Contact Angles and Contact Lines, ECC99 Coating Conference, Erlangen, Germany (FSI-99-00-2), Sept. 1999

7-98 J. E. Richardson and Y. Becker, Three-Dimensional Simulation of Slot Coating Edge Effects, Flow Science Inc, and Polaroid Corporation, presented at the 9th International Coating Science and Technology Symposium, Newark, DE, May 18-20, 1998

6-98  C. W. Hirt and E. Choinski, Simulation of the Wet-Start Process in Slot Coating, Flow Science Inc, and Polaroid Corporation, presented at the 9th International Coating Science and Technology Symposium, Newark, DE, May 18-20, 1998

3-97  C. W. Hirt and J. E. Richardson of Flow Science Inc, and K.S. Chen, Sandia National Laboratory, Simulation of Transient and Three-Dimensional Coating Flows Using a Volume-of-Fluid Technique, presented at the 50th Annual Conference of the Society for Imaging and Science Technology, Boston, MA 18-23 May 1997

2-96 C. W. Hirt, K. S. Chen, Simulation of Slide-Coating Flows Using a Fixed Grid and a Volume-of-Fluid Front-Tracking Technique, presented a the 8th International Coating Process Science & Technology Symposium, February 25-29, 1996, New Orleans, LA

Metal Casting Bibliography

다음은 금속 주조 참고 문헌의 기술 문서 모음입니다. 
이 모든 논문은 FLOW-3D  CAST  결과를 포함하고 있습니다. FLOW-3D  CAST 를 사용하여 금속 주조 산업의 어플리케이션을 성공적으로 시뮬레이션  하는 방법에 대해 자세히 알아보십시오.

2024년 11월 20일 Update

93-24 Benedict Baumann, Andreas Kessler, Claudia Dommaschk, Gotthard Wolf , Influence of filter structure and casting system on filtration efficiency in aluminum mold casting, Multifunctional Ceramic Filter Systems for Metal Melt Filtration, Eds. C.G. Aneziris, H. Biermann, Springer Series in Materials Science, 337; 2024. doi.org/10.1007/978-3-031-40930-1_28

93-24 Benedict Baumann, Andreas Kessler, Claudia Dommaschk, Gotthard Wolf , Influence of filter structure and casting system on filtration efficiency in aluminum mold casting, Multifunctional Ceramic Filter Systems for Metal Melt Filtration, Eds. C.G. Aneziris, H. Biermann, Springer Series in Materials Science, 337; 2024. doi.org/10.1007/978-3-031-40930-1_28

87-24 Rahul Jayakumar, T.P.D. Rajan, Sivaraman Savithri, A GPU based accelerated solver for simulation of heat transfer during metal casting process, Modelling and Simulation in Materials Science and Engineering, 32.5; 055013, 2024. doi.org/10.1088/1361-651X/ad4406

46-24 Masyrukan, Irwan Mawarda, Sunardi Wiyono, Bibit Sugito, Ummi Kultsum, Dessy Ade Pratiwi, Desi Gustiani, Nur Annisa Istiqamah, The effect of differences in in-gate diameter size on the structure and mechanical properties of aluminum (Al) castings in pipe products with a red sand mold, AIP Conference Proceedings, 2838.1; 2024. doi.org/10.1063/5.0185773

43-24 German Alberto Barragán De Los Rios, Silvio Andrés Salazar Martínez, Emigdio Mendoza Fandiño, Patricia Fernández-Morales, Numerical simulation of aluminum foams by space holder infiltration, International Journal of Metalcasting, 2024. doi.org/10.1007/s40962-024-01287-8

40-24 Bin Zhang, Gary P. Grealy, Thermomechanical modeling on AirSlip® billet DC casting of high-strength crack-prone aluminum alloys, Light Metals 2024, Eds. S. Wagstaff, pp. 1015-1025, 2024. doi.org/10.1007/978-3-031-50308-5_128

35-24 Balaji Chandrakanth, Ved Prakash, Adwaita Maiti, Diya Mukherjee, Development of triply periodic minimal surface (TPMS) inspired structured cast iron foams through casting route, International Journal of Metalcasting, 2024. doi.org/10.1007/s40962-023-01247-8

19-24   Diya Mukherjee, Himadri Roy, Balaji Chandrakanth, Nilrudra Mandal, Sudip Kumar Samanta, Manidipto Mukherjee, Enhancing properties of Al-Zn-Mg-Cu alloy through microalloying and heat treatment, Materials Chemistry and Physics, 314; 128881, 2024. doi.org/10.1016/j.matchemphys.2024.128881

46-24 Masyrukan, Irwan Mawarda, Sunardi Wiyono, Bibit Sugito, Ummi Kultsum, Dessy Ade Pratiwi, Desi Gustiani, Nur Annisa Istiqamah, The effect of differences in in-gate diameter size on the structure and mechanical properties of aluminum (Al) castings in pipe products with a red sand mold, AIP Conference Proceedings, 2838.1; 2024. doi.org/10.1063/5.0185773

43-24 German Alberto Barragán De Los Rios, Silvio Andrés Salazar Martínez, Emigdio Mendoza Fandiño, Patricia Fernández-Morales, Numerical simulation of aluminum foams by space holder infiltration, International Journal of Metalcasting, 2024. doi.org/10.1007/s40962-024-01287-8

40-24 Bin Zhang, Gary P. Grealy, Thermomechanical modeling on AirSlip® billet DC casting of high-strength crack-prone aluminum alloys, Light Metals 2024, Eds. S. Wagstaff, pp. 1015-1025, 2024. doi.org/10.1007/978-3-031-50308-5_128

35-24 Balaji Chandrakanth, Ved Prakash, Adwaita Maiti, Diya Mukherjee, Development of triply periodic minimal surface (TPMS) inspired structured cast iron foams through casting route, International Journal of Metalcasting, 2024. doi.org/10.1007/s40962-023-01247-8

19-24   Diya Mukherjee, Himadri Roy, Balaji Chandrakanth, Nilrudra Mandal, Sudip Kumar Samanta, Manidipto Mukherjee, Enhancing properties of Al-Zn-Mg-Cu alloy through microalloying and heat treatment, Materials Chemistry and Physics, 314; 128881, 2024. doi.org/10.1016/j.matchemphys.2024.128881

181-23   Daichi Minamide, Ken’ichi Yano, Masahiro Sano, Takahiro Aoki, Overflow design system to decrease gas defects considering the direction of molten metal flow, 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), pp. 1-6, 2023. doi.org/10.1109/ICECCME57830.2023.10253413

102-23 Daichi Minamide, Ken’ichi Yano, Masahiro Sano, Takahiro Aoki, Automatic design of overflow system for preventing gas defects by considering the direction of molten metal flow, Computer-Aided Design, 163; 103586, 2023. doi.org/10.1016/j.cad.2023.103586

87-23 Prosenjit Das, Optimisation of melt pouring temperature and low superheat casting of Al-15Mg2Si-4.5Si composite, International Journal of Cast Metals Research, 36.1-3; 2023. doi.org/10.1080/13640461.2023.2211895

60-23   Yuanhao Gu, Feng Wang, Jian Jiao, Zhi Wang, Le Zhou, Pingli Mao, Zheng Liu, Study on semisolid rheo-diecasting process, microstructure and mechanical properties of Mg-6Al-1Ca-0.5Sb alloy with high solid fraction, International Journal of Metalcasting, 2023. doi.org/10.1007/s40962-023-01001-0

48-23   Patricia Fernández‑Morales, Lauramaría Echeverrí, Emigdio Mendoza Fandiño, Alejandro Alberto Zuleta Gil, Replication casting and additive manufacturing for fabrication of cellular aluminum with periodic topology: optimization by CFD simulation, The International Journal of Advanced Manufacturing Technology, 26; pp. 1789-1797, 2023. doi.org/10.1007/s00170-023-11124-7

45-23   Daniel Martinez, Philip King, Santosh Reddy Sama, Jay Sim, Hakan Toykoc, Guha Manogharan, Effect of freezing range on reducing casting defects through 3D sand-printed mold designs, The International Journal of Advanced Manufacturing Technology, 2023. doi.org/10.1007/s00170-023-11112-x

38-23   Emanuele Pagone, Christopher Jones, John Forde, William Shaw, Mark Jolly, Konstantinos Salonitis, Defect minimization in vacuum-assisted plaster mould investment casting through simulation of high-value aluminium alloy components, TMS 2023: Light Metals, pp. 1078-1086, 2023.

33-23   Philip King, Guha Manogharan, Novel experimental method for metal flow analysis using open molds for sand casting, International Journal of Metalcasting, 2023. doi.org/10.1007/s40962-023-00966-2

32-23   Sujeet Kumar Gautam, Himadri Roy, Aditya Kumar Lohar, Sudip Kumar Samanta, Studies on mold filling behavior of Al–10.5Si–1.7Cu Al alloy during rheo pressure die casting system, International Journal of Metalcasting, 2023. doi.org/10.1007/s40962-023-00958-2

31-23   Anand Kumbhare, Prasenjit Biswas, Anil Bisen, Chandan Choudary, Investigation of effect of the rheological parameters on the flow behavior of ADC12 Al alloy in rheo-pressure die casting, International Journal of Metalcasting, 2023. doi.org/10.1007/s40962-023-00962-6

24-23   Natalia Raźny, Anna Dmitruk, Maria Serdechnova, Carsten Blawert, Joanna Ludwiczak, Krzysztof Naplocha, The performance of thermally conductive tree-like cast aluminum structures in PCM-based storage units, International Communications in Heat and Mass Transfer, 142; 106606, 2023. doi.org/10.1016/j.icheatmasstransfer.2022.106606

172-22 J. Yokesh Kumar, S. Gopi, K.S. Amirthagadeswaran, Redesigning and numerical simulation of gating system to reduce cold shut defect in submersible pump part castings, Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2022. doi.org/10.1177/0954408922114218

125-22   Maximilian Erber, Tobias Rosnitschek, Christoph Hartmann, Bettina Alber-Laukant, Stephan Tremmel, Wolfram Volk, Geometry-based assurance of directional solidification for complex topology-optimized castings using the medial axis transform, Computer-Aided Design, 152; 103394, 2022. doi.org/10.1016/j.cad.2022.103394

74-22    Vasilios Fourlakidis, Ilia Belov, Attila Diószeg, Experimental model of the pearlite interlamellar spacing in lamellar graphite iron, Tecnologia em Metalurgia, Materiais e Mineração, 19; e2634, 2022. doi.org/10.4322/2176-1523.20222634

71-22   M. G. Mahmoud, Amr Abdelghany, Serag Salem, Numerical simulation of door lock plates castings produced by high pressure die casting process, International Journal of Metalcasting, 2022. doi.org/10.1007/s40962-022-00797-7

70-22   Andreas Schilling, Daniel Schmidt, Jakob Glück, Niklas Schwenke, Husam Sharabi, Martin Fehlbier, About the impact on gravity cast salt cores in high pressure die casting and rheocasting, Simulation Modelling Practice and Theory, 119; 102585, 2022. doi.org/10.1016/j.simpat.2022.102585

52-22   Manthan Dhisale, Jitesh Vasavada, Asim Tewari, An approach to optimize cooling channel parameters of low pressure die casting process for reducing shrinkage porosity in aluminium alloy wheels, Materials Today: Proceedings, in print, 2022. doi.org/10.1016/j.matpr.2022.03.478

44-22   Zihan Lang, Feng Wang, Wei Wang, Zhi Wang, Le Zhou, Pingli Mao, Zheng Liu, Numerical simulation and experimental study on semi-solid forming process of 319s aluminum alloy test bar, International Journal of Metalcasting, 2022. doi.org/10.1007/s40962-022-00788-8

32-22   Elisa Fracchia, Federico Simone Gobber, Claudio Mus, Raul Pirovino, Mario Russo, The local squeeze technology for challenging aluminium HPDC automotive components, Light Metals, pp. 772-778, 2022. doi.org/10.1007/978-3-030-92529-1_102

141-21   O. Ayer, O. Kaya, Mould design optimisation by FEM, Journal of Physics: Conference Series, 2130; 012021, 2021. doi.org/10.1088/1742-6596/2130/1/012021

117-21   I. Rajkumar, N. Rajini, T. Ram Prabhu, Sikiru O. Ismail, Suchart Siengchin, Faruq Mohammad, Hamad A. Al-Lohedan , Applicability of angular orientations of gating designs to quality of sand casting components using two-cavity mould set-up, Transactions of the Indian Institute of Metals, 2021. doi.org/10.1007/s12666-021-02434-z

106-21   M. Ahmed, E. Riedel, M. Kovalko, A. Volochko, R. Bähr, A. Nofal, Ultrafine ductile and austempered ductile irons by solidification in ultrasonic field, International Journal of Metalcasting, 2021. doi.org/10.1007/s40962-021-00683-8

97-21   J. Glueck, A. Schilling, N. Schwenke, A. Fros, M.Fehlbier, Efficiency and agility of a liquid CO2 cooling system for molten metal systems, Case Studies in Thermal Engineering, 28; 101485, 2021. doi.org/10.1016/j.csite.2021.101485

82-21   Giulia Scampone, Raul Pirovano, Stefano Mascetti, Giulio Timelli, Experimental and numerical investigations of oxide-related defects in Al alloy gravity die castings, The International Journal of Advanced Manufacturing Technology, 117; pp. 1765-1780, 2021. doi.org/10.1007/s00170-021-07680-5

74-21   Shuyang Ren, Feng Wang, Jingying Sun, Zheng Liu, Pingli Mao, Gating system design based on numerical simulation and production experiment verification of aluminum alloy bracket fabricated by semi-solid rheo-die casting process, International Journal of Metalcasting, 2021. doi.org/10.1007/s40962-021-00648-x

69-21   Ozen Gursoy, Murat Colak, Kazim Tur, Derya Dispinar, Characterization of properties of Vanadium, Boron and Strontium addition on HPDC of A360 alloy, Materials Chemistry and Physics, 271; 124931, 2021. doi.org/10.1016/j.matchemphys.2021.124931

54-21   K. Munpakdee, P. Ninpetch, S. Otarawanna, R. Canyook, P. Kowitwarangkul, Effect of feed sprue size on porosity defects in Platinum 950 centrifugal investment casting via numerical modelling, IOP Conference Series: Materials Science and Engineering, 11th TSME-International Conference on Mechanical Engineering, Ubon Ratchathani, Thailand, December 1-4, 2020, 1137; 012021, 2021. doi.org/10.1088/1757-899X/1137/1/012021/

44-21   Yunxiang Zhang, Haidong Zhao, Fei Liu, Microstructure characteristics and mechanical properties improvement of gravity cast Al-7Si-0.4Mg alloys with Zr additions, Materials Characterization, 176; 111117, 2021. doi.org/10.1016/j.matchar.2021.111117

05-21   Heqian Song, Lunyong Zhang, Fuyang Cao, Xu Gu, Jianfei Sun, Oxide bifilm defects in aluminum alloy castings, Materials Letters, 285; 129089, 2021. doi.org/10.1016/j.matlet.2020.129089

127-20   Eric Riedel, Niklas Bergedieck, Stefan Scharf, CFD simulation based investigation of cavitation cynamics during high intensity ultrasonic treatment of A356, Metals, 10.11; 1529, 2020. doi.org/10.3390/met10111529

86-20       Malte Leonhard, Matthias Todte, Jörg Schäfer, Realistic simulation of the combustion of exothermic feeders, Modern Casting, August 2020; pp. 35-40, 2020. (See also 58-19)

52-20       Mingfan Qi, Yonglin Kang, Jingyuan Li, Zhumabieke Wulabieke, Yuzhao Xu, Yangde Li, Aisen Liu, Junchen Chen, Microstructures refinement and mechanical properties enhancement of aluminum and magnesium alloys by combining distributary-confluence channel process for semisolid slurry preparation with high pressure die-casting, Journal of Materials Processing Technology, 285; 116800, 2020. doi.org/10.1016/j.jmatprotec.2020.116800

46-20       Yasushi Iwata, Shuxin Dong, Yoshio Sugiyama, Jun Yaokawa, Melt permeability changes during solidification of aluminum alloys and application to feeding simulation for die castings, Materials Transactions, 61.7; pp. 1381-1386, 2020. doi.org/10.2320/matertrans.F-M2020822

45-20       Daniel Bernal, Xabier Chamorro, Iñaki Hurtado, Iñaki Madariaga, Effect of boron content and cooling rate on the microstructure and boride formation of β-solidifying γ-TiAl TNM alloy, Metals, 10.5; 698, 2020. doi.org/10.3390/met10050698

33-20     Eric Riedel, Martin Liepe Stefan Scharf, Simulation of ultrasonic induced cavitation and acoustic streaming in liquid and solidifying aluminum, Metals, 10.4; 476, 2020. doi.org/10.3390/met10040476

20-20   Wu Yue, Li Zhuo and Lu Rong, Simulation and visual tester verification of solid propellant slurry vacuum plate casting, Propellants, Explosives, Pyrotechnics, 2020. doi.org/10.1002/prep.201900411

17-20   C.A. Jones, M.R. Jolly, A.E.W. Jarfors and M. Irwin, An experimental characterization of thermophysical properties of a porous ceramic shell used in the investment casting process, Supplimental Proceedings, pp. 1095-1105, TMS 2020 149th Annual Meeting and Exhibition, San Diego, CA, February 23-27, 2020. doi.org/10.1007/978-3-030-36296-6_102

12-20   Franz Josef Feikus, Paul Bernsteiner, Ricardo Fernández Gutiérrez and Michal Luszczak , Further development of electric motor housings, MTZ Worldwide, 81, pp. 38-43, 2020. doi.org/10.1007/s38313-019-0176-z

09-20   Mingfan Qi, Yonglin Kang, Yuzhao Xu, Zhumabieke Wulabieke and Jingyuan Li, A novel rheological high pressure die-casting process for preparing large thin-walled Al–Si–Fe–Mg–Sr alloy with high heat conductivity, high plasticity and medium strength, Materials Science and Engineering: A, 776, art. no. 139040, 2020. doi.org/10.1016/j.msea.2020.139040

07-20   Stefan Heugenhauser, Erhard Kaschnitz and Peter Schumacher, Development of an aluminum compound casting process – Experiments and numerical simulations, Journal of Materials Processing Technology, 279, art. no. 116578, 2020. doi.org/10.1016/j.jmatprotec.2019.116578

05-20   Michail Papanikolaou, Emanuele Pagone, Mark Jolly and Konstantinos Salonitis, Numerical simulation and evaluation of Campbell running and gating systems, Metals, 10.1, art. no. 68, 2020. doi.org/10.3390/met10010068

102-19   Ferencz Peti and Gabriela Strnad, The effect of squeeze pin dimension and operational parameters on material homogeneity of aluminium high pressure die cast parts, Acta Marisiensis. Seria Technologica, 16.2, 2019. doi.org/0.2478/amset-2019-0010

94-19   E. Riedel, I. Horn, N. Stein, H. Stein, R. Bahr, and S. Scharf, Ultrasonic treatment: a clean technology that supports sustainability incasting processes, Procedia, 26th CIRP Life Cycle Engineering (LCE) Conference, Indianapolis, Indiana, USA, May 7-9, 2019.

93-19   Adrian V. Catalina, Liping Xue, Charles A. Monroe, Robin D. Foley, and John A. Griffin, Modeling and Simulation of Microstructure and Mechanical Properties of AlSi- and AlCu-based Alloys, Transactions, 123rd Metalcasting Congress, Atlanta, GA, USA, April 27-30, 2019.

84-19   Arun Prabhakar, Michail Papanikolaou, Konstantinos Salonitis, and Mark Jolly, Sand casting of sheet lead: numerical simulation of metal flow and solidification, The International Journal of Advanced Manufacturing Technology, pp. 1-13, 2019. doi:10.1007/s00170-019-04522-3

72-19   Santosh Reddy Sama, Eric Macdonald, Robert Voigt, and Guha Manogharan, Measurement of metal velocity in sand casting during mold filling, Metals, 9:1079, 2019. doi:10.3390/met9101079

71-19   Sebastian Findeisen, Robin Van Der Auwera, Michael Heuser, and Franz-Josef Wöstmann, Gießtechnische Fertigung von E-Motorengehäusen mit interner Kühling (Casting production of electric motor housings with internal cooling), Geisserei, 106, pp. 72-78, 2019 (in German).

58-19     Von Malte Leonhard, Matthias Todte, and Jörg Schäffer, Realistic simulation of the combustion of exothermic feeders, Casting, No. 2, pp. 28-32, 2019. In English and German.

52-19     S. Lakkum and P. Kowitwarangkul, Numerical investigations on the effect of gas flow rate in the gas stirred ladle with dual plugs, International Conference on Materials Research and Innovation (ICMARI), Bangkok, Thailand, December 17-21, 2018. IOP Conference Series: Materials Science and Engineering, Vol. 526, 2019. doi: 10.1088/1757-899X/526/1/012028

47-19     Bing Zhou, Shuai Lu, Kaile Xu, Chun Xu, and Zhanyong Wang, Microstructure and simulation of semisolid aluminum alloy castings in the process of stirring integrated transfer-heat (SIT) with water cooling, International Journal of Metalcasting, Online edition, pp. 1-13, 2019. doi: 10.1007/s40962-019-00357-6

31-19     Zihao Yuan, Zhipeng Guo, and S.M. Xiong, Skin layer of A380 aluminium alloy die castings and its blistering during solution treatment, Journal of Materials Science & Technology, Vol. 35, No. 9, pp. 1906-1916, 2019. doi: 10.1016/j.jmst.2019.05.011

25-19     Stefano Mascetti, Raul Pirovano, and Giulio Timelli, Interazione metallo liquido/stampo: Il fenomeno della metallizzazione, La Metallurgia Italiana, No. 4, pp. 44-50, 2019. In Italian.

20-19     Fu-Yuan Hsu, Campbellology for runner system design, Shape Casting: The Minerals, Metals & Materials Series, pp. 187-199, 2019. doi: 10.1007/978-3-030-06034-3_19

19-19     Chengcheng Lyu, Michail Papanikolaou, and Mark Jolly, Numerical process modelling and simulation of Campbell running systems designs, Shape Casting: The Minerals, Metals & Materials Series, pp. 53-64, 2019. doi: 10.1007/978-3-030-06034-3_5

18-19     Adrian V. Catalina, Liping Xue, and Charles Monroe, A solidification model with application to AlSi-based alloys, Shape Casting: The Minerals, Metals & Materials Series, pp. 201-213, 2019. doi: 10.1007/978-3-030-06034-3_20

17-19     Fu-Yuan Hsu and Yu-Hung Chen, The validation of feeder modeling for ductile iron castings, Shape Casting: The Minerals, Metals & Materials Series, pp. 227-238, 2019. doi: 10.1007/978-3-030-06034-3_22

04-19   Santosh Reddy Sama, Tony Badamo, Paul Lynch and Guha Manogharan, Novel sprue designs in metal casting via 3D sand-printing, Additive Manufacturing, Vol. 25, pp. 563-578, 2019. doi: 10.1016/j.addma.2018.12.009

02-19   Jingying Sun, Qichi Le, Li Fu, Jing Bai, Johannes Tretter, Klaus Herbold and Hongwei Huo, Gas entrainment behavior of aluminum alloy engine crankcases during the low-pressure-die-casting-process, Journal of Materials Processing Technology, Vol. 266, pp. 274-282, 2019. doi: 10.1016/j.jmatprotec.2018.11.016

82-18   Xu Zhao, Ping Wang, Tao Li, Bo-yu Zhang, Peng Wang, Guan-zhou Wang and Shi-qi Lu, Gating system optimization of high pressure die casting thin-wall AlSi10MnMg longitudinal loadbearing beam based on numerical simulation, China Foundry, Vol. 15, no. 6, pp. 436-442, 2018. doi: 10.1007/s41230-018-8052-z

80-18   Michail Papanikolaou, Emanuele Pagone, Konstantinos Salonitis, Mark Jolly and Charalampos Makatsoris, A computational framework towards energy efficient casting processes, Sustainable Design and Manufacturing 2018: Proceedings of the 5th International Conference on Sustainable Design and Manufacturing (KES-SDM-18), Gold Coast, Australia, June 24-26 2018, SIST 130, pp. 263-276, 2019. doi: 10.1007/978-3-030-04290-5_27

64-18   Vasilios Fourlakidis, Ilia Belov and Attila Diószegi, Strength prediction for pearlitic lamellar graphite iron: Model validation, Metals, Vol. 8, No. 9, 2018. doi: 10.3390/met8090684

51-18   Xue-feng Zhu, Bao-yi Yu, Li Zheng, Bo-ning Yu, Qiang Li, Shu-ning Lü and Hao Zhang, Influence of pouring methods on filling process, microstructure and mechanical properties of AZ91 Mg alloy pipe by horizontal centrifugal casting, China Foundry, vol. 15, no. 3, pp.196-202, 2018. doi: 10.1007/s41230-018-7256-6

47-18   Santosh Reddy Sama, Jiayi Wang and Guha Manogharan, Non-conventional mold design for metal casting using 3D sand-printing, Journal of Manufacturing Processes, vol. 34-B, pp. 765-775, 2018. doi: 10.1016/j.jmapro.2018.03.049

42-18   M. Koru and O. Serçe, The Effects of Thermal and Dynamical Parameters and Vacuum Application on Porosity in High-Pressure Die Casting of A383 Al-Alloy, International Journal of Metalcasting, pp. 1-17, 2018. /doi: 10.1007/s40962-018-0214-7

41-18   Abhilash Viswanath, S. Savithri, U.T.S. Pillai, Similitude analysis on flow characteristics of water, A356 and AM50 alloys during LPC process, Journal of Materials Processing Technology, vol. 257, pp. 270-277, 2018. doi: 10.1016/j.jmatprotec.2018.02.031

29-18   Seyboldt, Christoph and Liewald, Mathias, Investigation on thixojoining to produce hybrid components with intermetallic phase, AIP Conference Proceedings, vol. 1960, no. 1, 2018. doi: 10.1063/1.5034992

28-18   Laura Schomer, Mathias Liewald and Kim Rouven Riedmüller, Simulation of the infiltration process of a ceramic open-pore body with a metal alloy in semi-solid state to design the manufacturing of interpenetrating phase composites, AIP Conference Proceedings, vol. 1960, no. 1, 2018. doi: 10.1063/1.5034991

41-17   Y. N. Wu et al., Numerical Simulation on Filling Optimization of Copper Rotor for High Efficient Electric Motors in Die Casting Process, Materials Science Forum, Vol. 898, pp. 1163-1170, 2017.

12-17   A.M.  Zarubin and O.A. Zarubina, Controlling the flow rate of melt in gravity die casting of aluminum alloys, Liteynoe Proizvodstvo (Casting Manufacturing), pp 16-20, 6, 2017. In Russian.

10-17   A.Y. Korotchenko, Y.V. Golenkov, M.V. Tverskoy and D.E. Khilkov, Simulation of the Flow of Metal Mixtures in the Mold, Liteynoe Proizvodstvo (Casting Manufacturing), pp 18-22, 5, 2017. In Russian.

08-17   Morteza Morakabian Esfahani, Esmaeil Hajjari, Ali Farzadi and Seyed Reza Alavi Zaree, Prediction of the contact time through modeling of heat transfer and fluid flow in compound casting process of Al/Mg light metals, Journal of Materials Research, © Materials Research Society 2017

04-17   Huihui Liu, Xiongwei He and Peng Guo, Numerical simulation on semi-solid die-casting of magnesium matrix composite based on orthogonal experiment, AIP Conference Proceedings 1829, 020037 (2017); doi: 10.1063/1.4979769.

100-16  Robert Watson, New numerical techniques to quantify and predict the effect of entrainment defects, applied to high pressure die casting, PhD Thesis: University of Birmingham, 2016.

88-16   M.C. Carter, T. Kauffung, L. Weyenberg and C. Peters, Low Pressure Die Casting Simulation Discovery through Short Shot, Cast Expo & Metal Casting Congress, April 16-19, 2016, Minneapolis, MN, Copyright 2016 American Foundry Society.

61-16   M. Koru and O. Serçe, Experimental and numerical determination of casting mold interfacial heat transfer coefficient in the high pressure die casting of a 360 aluminum alloy, ACTA PHYSICA POLONICA A, Vol. 129 (2016)

59-16   R. Pirovano and S. Mascetti, Tracking of collapsed bubbles during a filling simulation, La Metallurgia Italiana – n. 6 2016

43-16   Kevin Lee, Understanding shell cracking during de-wax process in investment casting, Ph.D Thesis: University of Birmingham, School of Engineering, Department of Chemical Engineering, 2016.

35-16   Konstantinos Salonitis, Mark Jolly, Binxu Zeng, and Hamid Mehrabi, Improvements in energy consumption and environmental impact by novel single shot melting process for casting, Journal of Cleaner Production, doi:10.1016/j.jclepro.2016.06.165, Open Access funded by Engineering and Physical Sciences Research Council, June 29, 2016

20-16   Fu-Yuan Hsu, Bifilm Defect Formation in Hydraulic Jump of Liquid Aluminum, Metallurgical and Materials Transactions B, 2016, Band: 47, Heft 3, 1634-1648.

15-16   Mingfan Qia, Yonglin Kanga, Bing Zhoua, Wanneng Liaoa, Guoming Zhua, Yangde Lib,and Weirong Li, A forced convection stirring process for Rheo-HPDC aluminum and magnesium alloys, Journal of Materials Processing Technology 234 (2016) 353–367

112-15   José Miguel Gonçalves Ledo Belo da Costa, Optimization of filling systems for low pressure by FLOW-3D, Dissertação de mestrado integrado em Engenharia Mecânica, http://hdl.handle.net/1822/40132, 2015

89-15   B.W. Zhu, L.X. Li, X. Liu, L.Q. Zhang and R. Xu, Effect of Viscosity Measurement Method to Simulate High Pressure Die Casting of Thin-Wall AlSi10MnMg Alloy Castings, Journal of Materials Engineering and Performance, Published online, November 2015, DOI: 10.1007/s11665-015-1783-8, © ASM International.

88-15   Peng Zhang, Zhenming Li, Baoliang Liu, Wenjiang Ding and Liming Peng, Improved tensile properties of a new aluminum alloy for high pressure die casting, Materials Science & Engineering A651(2016)376–390, Available online, November 2015.

83-15   Zu-Qi Hu, Xin-Jian Zhang and Shu-Sen Wu, Microstructure, Mechanical Properties and Die-Filling Behavior of High-Performance Die-Cast Al–Mg–Si–Mn Alloy, Acta Metall. Sin. (Engl. Lett.), DOI 10.1007/s40195-015-0332-7, © The Chinese Society for Metals and Springer-Verlag Berlin Heidelberg 2015.

82-15   J. Müller, L. Xue, M.C. Carter, C. Thoma, M. Fehlbier and M. Todte, A Die Spray Cooling Model for Thermal Die Cycling Simulations, 2015 Die Casting Congress & Exposition, Indianapolis, IN, October 2015

81-15   M. T. Murray, L.F. Hansen, L. Chilcott, E. Li and A.M. Murray, Case Studies in the Use of Simulation- Improved Yield and Reduced Time to Market, 2015 Die Casting Congress & Exposition, Indianapolis, IN, October 2015

80-15   R. Bhola, S. Chandra and D. Souders, Predicting Castability of Thin-Walled Parts for the HPDC Process Using Simulations, 2015 Die Casting Congress & Exposition, Indianapolis, IN, October 2015

76-15   Prosenjit Das, Sudip K. Samanta, Shashank Tiwari and Pradip Dutta, Die Filling Behaviour of Semi Solid A356 Al Alloy Slurry During Rheo Pressure Die Casting, Transactions of the Indian Institute of Metals, pp 1-6, October 2015

74-15   Murat KORU and Orhan SERÇE, Yüksek Basınçlı Döküm Prosesinde Enjeksiyon Parametrelerine Bağlı Olarak Döküm Simülasyon, Cumhuriyet University Faculty of Science, Science Journal (CSJ), Vol. 36, No: 5 (2015) ISSN: 1300-1949, May 2015

69-15   A. Viswanath, S. Sivaraman, U. T. S. Pillai, Computer Simulation of Low Pressure Casting Process Using FLOW-3D, Materials Science Forum, Vols. 830-831, pp. 45-48, September 2015

68-15   J. Aneesh Kumar, K. Krishnakumar and S. Savithri, Computer Simulation of Centrifugal Casting Process Using FLOW-3D, Materials Science Forum, Vols. 830-831, pp. 53-56, September 2015

59-15   F. Hosseini Yekta and S. A. Sadough Vanini, Simulation of the flow of semi-solid steel alloy using an enhanced model, Metals and Materials International, August 2015.

44-15   Ulrich E. Klotz, Tiziana Heiss and Dario Tiberto, Platinum investment casting material properties, casting simulation and optimum process parameters, Jewelry Technology Forum 2015

41-15   M. Barkhudarov and R. Pirovano, Minimizing Air Entrainment in High Pressure Die Casting Shot Sleeves, GIFA 2015, Düsseldorf, Germany

40-15   M. Todte, A. Fent, and H. Lang, Simulation in support of the development of innovative processes in the casting industry, GIFA 2015, Düsseldorf, Germany

19-15   Bruce Morey, Virtual casting improves powertrain design, Automotive Engineering, SAE International, March 2015.

15-15   K.S. Oh, J.D. Lee, S.J. Kim and J.Y. Choi, Development of a large ingot continuous caster, Metall. Res. Technol. 112, 203 (2015) © EDP Sciences, 2015, DOI: 10.1051/metal/2015006, www.metallurgical-research.org

14-15   Tiziana Heiss, Ulrich E. Klotz and Dario Tiberto, Platinum Investment Casting, Part I: Simulation and Experimental Study of the Casting Process, Johnson Matthey Technol. Rev., 2015, 59, (2), 95, doi:10.1595/205651315×687399

138-14 Christopher Thoma, Wolfram Volk, Ruben Heid, Klaus Dilger, Gregor Banner and Harald Eibisch, Simulation-based prediction of the fracture elongation as a failure criterion for thin-walled high-pressure die casting components, International Journal of Metalcasting, Vol. 8, No. 4, pp. 47-54, 2014. doi:10.1007/BF03355594

107-14  Mehran Seyed Ahmadi, Dissolution of Si in Molten Al with Gas Injection, ProQuest Dissertations And Theses; Thesis (Ph.D.), University of Toronto (Canada), 2014; Publication Number: AAT 3637106; ISBN: 9781321195231; Source: Dissertation Abstracts International, Volume: 76-02(E), Section: B.; 191 p.

99-14   R. Bhola and S. Chandra, Predicting Castability for Thin-Walled HPDC Parts, Foundry Management Technology, December 2014

92-14   Warren Bishenden and Changhua Huang, Venting design and process optimization of die casting process for structural components; Part II: Venting design and process optimization, Die Casting Engineer, November 2014

90-14   Ken’ichi Kanazawa, Ken’ichi Yano, Jun’ichi Ogura, and Yasunori Nemoto, Optimum Runner Design for Die-Casting using CFD Simulations and Verification with Water-Model Experiments, Proceedings of the ASME 2014 International Mechanical Engineering Congress and Exposition, IMECE2014, November 14-20, 2014, Montreal, Quebec, Canada, IMECE2014-37419

89-14   P. Kapranos, C. Carney, A. Pola, and M. Jolly, Advanced Casting Methodologies: Investment Casting, Centrifugal Casting, Squeeze Casting, Metal Spinning, and Batch Casting, In Comprehensive Materials Processing; McGeough, J., Ed.; 2014, Elsevier Ltd., 2014; Vol. 5, pp 39–67.

77-14   Andrei Y. Korotchenko, Development of Scientific and Technological Approaches to Casting Net-Shaped Castings in Sand Molds Free of Shrinkage Defects and Hot Tears, Post-doctoral thesis: Russian State Technological University, 2014. In Russian.

69-14   L. Xue, M.C. Carter, A.V. Catalina, Z. Lin, C. Li, and C. Qiu, Predicting, Preventing Core Gas Defects in Steel Castings, Modern Casting, September 2014

68-14   L. Xue, M.C. Carter, A.V. Catalina, Z. Lin, C. Li, and C. Qiu, Numerical Simulation of Core Gas Defects in Steel Castings, Copyright 2014 American Foundry Society, 118th Metalcasting Congress, April 8 – 11, 2014, Schaumburg, IL

51-14   Jesus M. Blanco, Primitivo Carranza, Rafael Pintos, Pedro Arriaga, and Lakhdar Remaki, Identification of Defects Originated during the Filling of Cast Pieces through Particles Modelling, 11th World Congress on Computational Mechanics (WCCM XI), 5th European Conference on Computational Mechanics (ECCM V), 6th European Conference on Computational Fluid Dynamics (ECFD VI), E. Oñate, J. Oliver and A. Huerta (Eds)

47-14   B. Vijaya Ramnatha, C.Elanchezhiana, Vishal Chandrasekhar, A. Arun Kumarb, S. Mohamed Asif, G. Riyaz Mohamed, D. Vinodh Raj , C .Suresh Kumar, Analysis and Optimization of Gating System for Commutator End Bracket, Procedia Materials Science 6 ( 2014 ) 1312 – 1328, 3rd International Conference on Materials Processing and Characterisation (ICMPC 2014)

42-14  Bing Zhou, Yong-lin Kang, Guo-ming Zhu, Jun-zhen Gao, Ming-fan Qi, and Huan-huan Zhang, Forced convection rheoforming process for preparation of 7075 aluminum alloy semisolid slurry and its numerical simulation, Trans. Nonferrous Met. Soc. China 24(2014) 1109−1116

37-14    A. Karwinski, W. Lesniewski, P. Wieliczko, and M. Malysza, Casting of Titanium Alloys in Centrifugal Induction Furnaces, Archives of Metallurgy and Materials, Volume 59, Issue 1, DOI: 10.2478/amm-2014-0068, 2014.

26-14    Bing Zhou, Yonglin Kang, Mingfan Qi, Huanhuan Zhang and Guoming ZhuR-HPDC Process with Forced Convection Mixing Device for Automotive Part of A380 Aluminum Alloy, Materials 2014, 7, 3084-3105; doi:10.3390/ma7043084

20-14  Johannes Hartmann, Tobias Fiegl, Carolin Körner, Aluminum integral foams with tailored density profile by adapted blowing agents, Applied Physics A, 10.1007/s00339-014-8377-4, March 2014.

19-14    A.Y. Korotchenko, N.A. Nikiforova, E.D. Demjanov, N.C. Larichev, The Influence of the Filling Conditions on the Service Properties of the Part Side Frame, Russian Foundryman, 1 (January), pp 40-43, 2014. In Russian.

11-14 B. Fuchs and C. Körner, Mesh resolution consideration for the viability prediction of lost salt cores in the high pressure die casting process, Progress in Computational Fluid Dynamics, Vol. 14, No. 1, 2014, Copyright © 2014 Inderscience Enterprises Ltd.

08-14 FY Hsu, SW Wang, and HJ Lin, The External and Internal Shrinkages in Aluminum Gravity Castings, Shape Casting: 5th International Symposium 2014. Available online at Google Books

103-13  B. Fuchs, H. Eibisch and C. Körner, Core Viability Simulation for Salt Core Technology in High-Pressure Die Casting, International Journal of Metalcasting, July 2013, Volume 7, Issue 3, pp 39–45

94-13    Randall S. Fielding, J. Crapps, C. Unal, and J.R.Kennedy, Metallic Fuel Casting Development and Parameter Optimization Simulations, International Conference on Fast reators and Related Fuel Cycles (FR13), 4-7 March 2013, Paris France

90-13  A. Karwińskia, M. Małyszaa, A. Tchórza, A. Gila, B. Lipowska, Integration of Computer Tomography and Simulation Analysis in Evaluation of Quality of Ceramic-Carbon Bonded Foam Filter, Archives of Foundry Engineering, DOI: 10.2478/afe-2013-0084, Published quarterly as the organ of the Foundry Commission of the Polish Academy of Sciences, ISSN, (2299-2944), Volume 13, Issue 4/2013

88-13  Litie and Metallurgia (Casting and Metallurgy), 3 (72), 2013, N.V.Sletova, I.N.Volnov, S.P.Zadrutsky, V.A.Chaikin, Modeling of the Process of Removing Non-metallic Inclusions in Aluminum Alloys Using the FLOW-3D program, pp 138-140. In Russian.

85-13    Michał Szucki,Tomasz Goraj, Janusz Lelito, Józef S. Suchy, Numerical Analysis of Solid Particles Flow in Liquid Metal, XXXVII International Scientific Conference Foundryman’ Day 2013, Krakow, 28-29 November 2013

84-13  Körner, C., Schwankl, M., Himmler, D., Aluminum-Aluminum compound castings by electroless deposited zinc layers, Journal of Materials Processing Technology (2014), http://dx.doi.org/10.1016/j.jmatprotec.2013.12.01483-13.

77-13  Antonio Armillotta & Raffaello Baraggi & Simone Fasoli, SLM tooling for die casting with conformal cooling channels, The International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-013-5523-7, December 2013.

64-13   Johannes Hartmann, Christina Blümel, Stefan Ernst, Tobias Fiegl, Karl-Ernst Wirth, Carolin Körner, Aluminum integral foam castings with microcellular cores by nano-functionalization, J Mater Sci, DOI: 10.1007/s10853-013-7668-z, September 2013.

46-13  Nicholas P. Orenstein, 3D Flow and Temperature Analysis of Filling a Plutonium Mold, LA-UR-13-25537, Approved for public release; distribution is unlimited. Los Alamos Annual Student Symposium 2013, 2013-07-24 (Rev.1)

42-13   Yang Yue, William D. Griffiths, and Nick R. Green, Modelling of the Effects of Entrainment Defects on Mechanical Properties in a Cast Al-Si-Mg Alloy, Materials Science Forum, 765, 225, 2013.

39-13  J. Crapps, D.S. DeCroix, J.D Galloway, D.A. Korzekwa, R. Aikin, R. Fielding, R. Kennedy, C. Unal, Separate effects identification via casting process modeling for experimental measurement of U-Pu-Zr alloys, Journal of Nuclear Materials, 15 July 2013.

35-13   A. Pari, Real Life Problem Solving through Simulations in the Die Casting Industry – Case Studies, © Die Casting Engineer, July 2013.

34-13  Martin Lagler, Use of Simulation to Predict the Viability of Salt Cores in the HPDC Process – Shot Curve as a Decisive Criterion, © Die Casting Engineer, July 2013.

24-13    I.N.Volnov, Optimizatsia Liteynoi Tekhnologii, (Casting Technology Optimization), Liteyshik Rossii (Russian Foundryman), 3, 2013, 27-29. In Russian

23-13  M.R. Barkhudarov, I.N. Volnov, Minimizatsia Zakhvata Vozdukha v Kamere Pressovania pri Litie pod Davleniem, (Minimization of Air Entrainment in the Shot Sleeve During High Pressure Die Casting), Liteyshik Rossii (Russian Foundryman), 3, 2013, 30-34. In Russian

09-13  M.C. Carter and L. Xue, Simulating the Parameters that Affect Core Gas Defects in Metal Castings, Copyright 2012 American Foundry Society, Presented at the 2013 CastExpo, St. Louis, Missouri, April 2013

08-13  C. Reilly, N.R. Green, M.R. Jolly, J.-C. Gebelin, The Modelling Of Oxide Film Entrainment In Casting Systems Using Computational Modelling, Applied Mathematical Modelling, http://dx.doi.org/10.1016/j.apm.2013.03.061, April 2013.

03-13  Alexandre Reikher and Krishna M. Pillai, A fast simulation of transient metal flow and solidification in a narrow channel. Part II. Model validation and parametric study, Int. J. Heat Mass Transfer (2013), http://dx.doi.org/10.1016/j.ijheatmasstransfer.2012.12.061.

02-13  Alexandre Reikher and Krishna M. Pillai, A fast simulation of transient metal flow and solidification in a narrow channel. Part I: Model development using lubrication approximation, Int. J. Heat Mass Transfer (2013), http://dx.doi.org/10.1016/j.ijheatmasstransfer.2012.12.060.

116-12  Jufu Jianga, Ying Wang, Gang Chena, Jun Liua, Yuanfa Li and Shoujing Luo, “Comparison of mechanical properties and microstructure of AZ91D alloy motorcycle wheels formed by die casting and double control forming, Materials & Design, Volume 40, September 2012, Pages 541-549.

107-12  F.K. Arslan, A.H. Hatman, S.Ö. Ertürk, E. Güner, B. Güner, An Evaluation for Fundamentals of Die Casting Materials Selection and Design, IMMC’16 International Metallurgy & Materials Congress, Istanbul, Turkey, 2012.

103-12 WU Shu-sen, ZHONG Gu, AN Ping, WAN Li, H. NAKAE, Microstructural characteristics of Al−20Si−2Cu−0.4Mg−1Ni alloy formed by rheo-squeeze casting after ultrasonic vibration treatment, Transactions of Nonferrous Metals Society of China, 22 (2012) 2863-2870, November 2012. Full paper available online.

109-12 Alexandre Reikher, Numerical Analysis of Die-Casting Process in Thin Cavities Using Lubrication Approximation, Ph.D. Thesis: The University of Wisconsin Milwaukee, Engineering Department (2012) Theses and Dissertations. Paper 65.

97-12 Hong Zhou and Li Heng Luo, Filling Pattern of Step Gating System in Lost Foam Casting Process and its Application, Advanced Materials Research, Volumes 602-604, Progress in Materials and Processes, 1916-1921, December 2012.

93-12  Liangchi Zhang, Chunliang Zhang, Jeng-Haur Horng and Zichen Chen, Functions of Step Gating System in the Lost Foam Casting Process, Advanced Materials Research, 591-593, 940, DOI: 10.4028/www.scientific.net/AMR.591-593.940, November 2012.

91-12  Hong Yan, Jian Bin Zhu, Ping Shan, Numerical Simulation on Rheo-Diecasting of Magnesium Matrix Composites, 10.4028/www.scientific.net/SSP.192-193.287, Solid State Phenomena, 192-193, 287.

89-12  Alexandre Reikher and Krishna M. Pillai, A Fast Numerical Simulation for Modeling Simultaneous Metal Flow and Solidification in Thin Cavities Using the Lubrication Approximation, Numerical Heat Transfer, Part A: Applications: An International Journal of Computation and Methodology, 63:2, 75-100, November 2012.

82-12  Jufu Jiang, Gang Chen, Ying Wang, Zhiming Du, Weiwei Shan, and Yuanfa Li, Microstructure and mechanical properties of thin-wall and high-rib parts of AM60B Mg alloy formed by double control forming and die casting under the optimal conditions, Journal of Alloys and Compounds, http://dx.doi.org/10.1016/j.jallcom.2012.10.086, October 2012.

78-12   A. Pari, Real Life Problem Solving through Simulations in the Die Casting Industry – Case Studies, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012, Indianapolis, IN.

77-12  Y. Wang, K. Kabiri-Bamoradian and R.A. Miller, Rheological behavior models of metal matrix alloys in semi-solid casting process, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012, Indianapolis, IN.

76-12  A. Reikher and H. Gerber, Analysis of Solidification Parameters During the Die Cast Process, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012, Indianapolis, IN.

75-12 R.A. Miller, Y. Wang and K. Kabiri-Bamoradian, Estimating Cavity Fill Time, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012Indianapolis, IN.

65-12  X.H. Yang, T.J. Lu, T. Kim, Influence of non-conducting pore inclusions on phase change behavior of porous media with constant heat flux boundaryInternational Journal of Thermal Sciences, Available online 10 October 2012. Available online at SciVerse.

55-12  Hejun Li, Pengyun Wang, Lehua Qi, Hansong Zuo, Songyi Zhong, Xianghui Hou, 3D numerical simulation of successive deposition of uniform molten Al droplets on a moving substrate and experimental validation, Computational Materials Science, Volume 65, December 2012, Pages 291–301.

52-12 Hongbing Ji, Yixin Chen and Shengzhou Chen, Numerical Simulation of Inner-Outer Couple Cooling Slab Continuous Casting in the Filling Process, Advanced Materials Research (Volumes 557-559), Advanced Materials and Processes II, pp. 2257-2260, July 2012.

47-12    Petri Väyrynen, Lauri Holappa, and Seppo Louhenkilpi, Simulation of Melting of Alloying Materials in Steel Ladle, SCANMET IV – 4th International Conference on Process Development in Iron and Steelmaking, Lulea, Sweden, June 10-13, 2012.

46-12  Bin Zhang and Dave Salee, Metal Flow and Heat Transfer in Billet DC Casting Using Wagstaff® Optifill™ Metal Distribution Systems, 5th International Metal Quality Workshop, United Arab Emirates Dubai, March 18-22, 2012.

45-12 D.R. Gunasegaram, M. Givord, R.G. O’Donnell and B.R. Finnin, Improvements engineered in UTS and elongation of aluminum alloy high pressure die castings through the alteration of runner geometry and plunger velocity, Materials Science & Engineering.

44-12    Antoni Drys and Stefano Mascetti, Aluminum Casting Simulations, Desktop Engineering, September 2012

42-12   Huizhen Duan, Jiangnan Shen and Yanping Li, Comparative analysis of HPDC process of an auto part with ProCAST and FLOW-3D, Applied Mechanics and Materials Vols. 184-185 (2012) pp 90-94, Online available since 2012/Jun/14 at www.scientific.net, © (2012) Trans Tech Publications, Switzerland, doi:10.4028/www.scientific.net/AMM.184-185.90.

41-12    Deniece R. Korzekwa, Cameron M. Knapp, David A. Korzekwa, and John W. Gibbs, Co-Design – Fabrication of Unalloyed Plutonium, LA-UR-12-23441, MDI Summer Research Group Workshop Advanced Manufacturing, 2012-07-25/2012-07-26 (Los Alamos, New Mexico, United States)

29-12  Dario Tiberto and Ulrich E. Klotz, Computer simulation applied to jewellery casting: challenges, results and future possibilities, IOP Conf. Ser.: Mater. Sci. Eng.33 012008. Full paper available at IOP.

28-12  Y Yue and N R Green, Modelling of different entrainment mechanisms and their influences on the mechanical reliability of Al-Si castings, 2012 IOP Conf. Ser.: Mater. Sci. Eng. 33,012072.Full paper available at IOP.

27-12  E Kaschnitz, Numerical simulation of centrifugal casting of pipes, 2012 IOP Conf. Ser.: Mater. Sci. Eng. 33 012031, Issue 1. Full paper available at IOP.

15-12  C. Reilly, N.R Green, M.R. Jolly, The Present State Of Modeling Entrainment Defects In The Shape Casting Process, Applied Mathematical Modelling, Available online 27 April 2012, ISSN 0307-904X, 10.1016/j.apm.2012.04.032.

12-12   Andrei Starobin, Tony Hirt, Hubert Lang, and Matthias Todte, Core drying simulation and validation, International Foundry Research, GIESSEREIFORSCHUNG 64 (2012) No. 1, ISSN 0046-5933, pp 2-5

10-12  H. Vladimir Martínez and Marco F. Valencia (2012). Semisolid Processing of Al/β-SiC Composites by Mechanical Stirring Casting and High Pressure Die Casting, Recent Researches in Metallurgical Engineering – From Extraction to Forming, Dr Mohammad Nusheh (Ed.), ISBN: 978-953-51-0356-1, InTech

07-12     Amir H. G. Isfahani and James M. Brethour, Simulating Thermal Stresses and Cooling Deformations, Die Casting Engineer, March 2012

06-12   Shuisheng Xie, Youfeng He and Xujun Mi, Study on Semi-solid Magnesium Alloys Slurry Preparation and Continuous Roll-casting Process, Magnesium Alloys – Design, Processing and Properties, ISBN: 978-953-307-520-4, InTech.

04-12 J. Spangenberg, N. Roussel, J.H. Hattel, H. Stang, J. Skocek, M.R. Geiker, Flow induced particle migration in fresh concrete: Theoretical frame, numerical simulations and experimental results on model fluids, Cement and Concrete Research, http://dx.doi.org/10.1016/j.cemconres.2012.01.007, February 2012.

01-12   Lee, B., Baek, U., and Han, J., Optimization of Gating System Design for Die Casting of Thin Magnesium Alloy-Based Multi-Cavity LCD Housings, Journal of Materials Engineering and Performance, Springer New York, Issn: 1059-9495, 10.1007/s11665-011-0111-1, Volume 1 / 1992 – Volume 21 / 2012. Available online at Springer Link.

104-11  Fu-Yuan Hsu and Huey Jiuan Lin, Foam Filters Used in Gravity Casting, Metall and Materi Trans B (2011) 42: 1110. doi:10.1007/s11663-011-9548-8.

99-11    Eduardo Trejo, Centrifugal Casting of an Aluminium Alloy, thesis: Doctor of Philosophy, Metallurgy and Materials School of Engineering University of Birmingham, October 2011. Full paper available upon request.

93-11  Olga Kononova, Andrejs Krasnikovs ,Videvuds Lapsa,Jurijs Kalinka and Angelina Galushchak, Internal Structure Formation in High Strength Fiber Concrete during Casting, World Academy of Science, Engineering and Technology 59 2011

76-11  J. Hartmann, A. Trepper, and C. Körner, Aluminum Integral Foams with Near-Microcellular Structure, Advanced Engineering Materials 2011, Volume 13 (2011) No. 11, © Wiley-VCH

71-11  Fu-Yuan Hsu and Yao-Ming Yang Confluence Weld in an Aluminum Gravity Casting, Journal of Materials Processing Technology, Available online 23 November 2011, ISSN 0924-0136, 10.1016/j.jmatprotec.2011.11.006.

65-11     V.A. Chaikin, A.V. Chaikin, I.N.Volnov, A Study of the Process of Late Modification Using Simulation, in Zagotovitelnye Proizvodstva v Mashinostroenii, 10, 2011, 8-12. In Russian.

54-11  Ngadia Taha Niane and Jean-Pierre Michalet, Validation of Foundry Process for Aluminum Parts with FLOW-3D Software, Proceedings of the 2011 International Symposium on Liquid Metal Processing and Casting, 2011.

51-11    A. Reikher and H. Gerber, Calculation of the Die Cast parameters of the Thin Wall Aluminum Cast Part, 2011 Die Casting Congress & Tabletop, Columbus, OH, September 19-21, 2011

50-11   Y. Wang, K. Kabiri-Bamoradian, and R.A. Miller, Runner design optimization based on CFD simulation for a die with multiple cavities, 2011 Die Casting Congress & Tabletop, Columbus, OH, September 19-21, 2011

48-11 A. Karwiński, W. Leśniewski, S. Pysz, P. Wieliczko, The technology of precision casting of titanium alloys by centrifugal process, Archives of Foundry Engineering, ISSN: 1897-3310), Volume 11, Issue 3/2011, 73-80, 2011.

46-11  Daniel Einsiedler, Entwicklung einer Simulationsmethodik zur Simulation von Strömungs- und Trocknungsvorgängen bei Kernfertigungsprozessen mittels CFD (Development of a simulation methodology for simulating flow and drying operations in core production processes using CFD), MSc thesis at Technical University of Aalen in Germany (Hochschule Aalen), 2011.

44-11  Bin Zhang and Craig Shaber, Aluminum Ingot Thermal Stress Development Modeling of the Wagstaff® EpsilonTM Rolling Ingot DC Casting System during the Start-up Phase, Materials Science Forum Vol. 693 (2011) pp 196-207, © 2011 Trans Tech Publications, July, 2011.

43-11 Vu Nguyen, Patrick Rohan, John Grandfield, Alex Levin, Kevin Naidoo, Kurt Oswald, Guillaume Girard, Ben Harker, and Joe Rea, Implementation of CASTfill low-dross pouring system for ingot casting, Materials Science Forum Vol. 693 (2011) pp 227-234, © 2011 Trans Tech Publications, July, 2011.

40-11  A. Starobin, D. Goettsch, M. Walker, D. Burch, Gas Pressure in Aluminum Block Water Jacket Cores, © 2011 American Foundry Society, International Journal of Metalcasting/Summer 2011

37-11 Ferencz Peti, Lucian Grama, Analyze of the Possible Causes of Porosity Type Defects in Aluminum High Pressure Diecast Parts, Scientific Bulletin of the Petru Maior University of Targu Mures, Vol. 8 (XXV) no. 1, 2011, ISSN 1841-9267

31-11  Johannes Hartmann, André Trepper, Carolin Körner, Aluminum Integral Foams with Near-Microcellular Structure, Advanced Engineering Materials, 13: n/a. doi: 10.1002/adem.201100035, June 2011.

27-11  A. Pari, Optimization of HPDC Process using Flow Simulation Case Studies, Die Casting Engineer, July 2011

26-11    A. Reikher, H. Gerber, Calculation of the Die Cast Parameters of the Thin Wall Aluminum Die Casting Part, Die Casting Engineer, July 2011

21-11 Thang Nguyen, Vu Nguyen, Morris Murray, Gary Savage, John Carrig, Modelling Die Filling in Ultra-Thin Aluminium Castings, Materials Science Forum (Volume 690), Light Metals Technology V, pp 107-111, 10.4028/www.scientific.net/MSF.690.107, June 2011.

19-11 Jon Spangenberg, Cem Celal Tutum, Jesper Henri Hattel, Nicolas Roussel, Metter Rica Geiker, Optimization of Casting Process Parameters for Homogeneous Aggregate Distribution in Self-Compacting Concrete: A Feasibility Study, © IEEE Congress on Evolutionary Computation, 2011, New Orleans, USA

16-11  A. Starobin, C.W. Hirt, H. Lang, and M. Todte, Core Drying Simulation and Validations, AFS Proceedings 2011, © American Foundry Society, Presented at the 115th Metalcasting Congress, Schaumburg, Illinois, April 2011.

15-11  J. J. Hernández-Ortega, R. Zamora, J. López, and F. Faura, Numerical Analysis of Air Pressure Effects on the Flow Pattern during the Filling of a Vertical Die Cavity, AIP Conf. Proc., Volume 1353, pp. 1238-1243, The 14th International Esaform Conference on Material Forming: Esaform 2011; doi:10.1063/1.3589686, May 2011. Available online.

10-11 Abbas A. Khalaf and Sumanth Shankar, Favorable Environment for Nondentric Morphology in Controlled Diffusion Solidification, DOI: 10.1007/s11661-011-0641-z, © The Minerals, Metals & Materials Society and ASM International 2011, Metallurgical and Materials Transactions A, March 11, 2011.

08-11 Hai Peng Li, Chun Yong Liang, Li Hui Wang, Hong Shui Wang, Numerical Simulation of Casting Process for Gray Iron Butterfly Valve, Advanced Materials Research, 189-193, 260, February 2011.

04-11  C.W. Hirt, Predicting Core Shooting, Drying and Defect Development, Foundry Management & Technology, January 2011.

76-10  Zhizhong Sun, Henry Hu, Alfred Yu, Numerical Simulation and Experimental Study of Squeeze Casting Magnesium Alloy AM50, Magnesium Technology 2010, 2010 TMS Annual Meeting & ExhibitionFebruary 14-18, 2010, Seattle, WA.

68-10  A. Reikher, H. Gerber, K.M. Pillai, T.-C. Jen, Natural Convection—An Overlooked Phenomenon of the Solidification Process, Die Casting Engineer, January 2010

54-10    Andrea Bernardoni, Andrea Borsi, Stefano Mascetti, Alessandro Incognito and Matteo Corrado, Fonderia Leonardo aveva ragione! L’enorme cavallo dedicato a Francesco Sforza era materialmente realizzabile, A&C – Analisis e Calcolo, Giugno 2010. In  Italian.

48-10  J. J. Hernández-Ortega, R. Zamora, J. Palacios, J. López and F. Faura, An Experimental and Numerical Study of Flow Patterns and Air Entrapment Phenomena During the Filling of a Vertical Die Cavity, J. Manuf. Sci. Eng., October 2010, Volume 132, Issue 5, 05101, doi:10.1115/1.4002535.

47-10  A.V. Chaikin, I.N. Volnov, and V.A. Chaikin, Development of Dispersible Mixed Inoculant Compositions Using the FLOW-3D Program, Liteinoe Proizvodstvo, October, 2010, in Russian.

42-10  H. Lakshmi, M.C. Vinay Kumar, Raghunath, P. Kumar, V. Ramanarayanan, K.S.S. Murthy, P. Dutta, Induction reheating of A356.2 aluminum alloy and thixocasting as automobile component, Transactions of Nonferrous Metals Society of China 20(20101) s961-s967.

41-10  Pamela J. Waterman, Understanding Core-Gas Defects, Desktop Engineering, October 2010. Available online at Desktop Engineering. Also published in the Foundry Trade Journal, November 2010.

39-10  Liu Zheng, Jia Yingying, Mao Pingli, Li Yang, Wang Feng, Wang Hong, Zhou Le, Visualization of Die Casting Magnesium Alloy Steering Bracket, Special Casting & Nonferrous Alloys, ISSN: 1001-2249, CN: 42-1148/TG, 2010-04. In Chinese.

37-10  Morris Murray, Lars Feldager Hansen, and Carl Reinhardt, I Have Defects – Now What, Die Casting Engineer, September 2010

36-10  Stefano Mascetti, Using Flow Analysis Software to Optimize Piston Velocity for an HPDC Process, Die Casting Engineer, September 2010. Also available in Italian: Ottimizzare la velocita del pistone in pressofusione.  A & C, Analisi e Calcolo, Anno XII, n. 42, Gennaio 2011, ISSN 1128-3874.

32-10  Guan Hai Yan, Sheng Dun Zhao, Zheng Hui Sha, Parameters Optimization of Semisolid Diecasting Process for Air-Conditioner’s Triple Valve in HPb59-1 Alloy, Advanced Materials Research (Volumes 129 – 131), Vol. Material and Manufacturing Technology, pp. 936-941, DOI: 10.4028/www.scientific.net/AMR.129-131.936, August 2010.

29-10 Zheng Peng, Xu Jun, Zhang Zhifeng, Bai Yuelong, and Shi Likai, Numerical Simulation of Filling of Rheo-diecasting A357 Aluminum Alloy, Special Casting & Nonferrous Alloys, DOI: CNKI:SUN:TZZZ.0.2010-01-024, 2010.

27-10 For an Aerospace Diecasting, Littler Uses Simulation to Reveal Defects, and Win a New Order, Foundry Management & Technology, July 2010

23-10 Michael R. Barkhudarov, Minimizing Air Entrainment, The Canadian Die Caster, June 2010

15-10 David H. Kirkwood, Michel Suery, Plato Kapranos, Helen V. Atkinson, and Kenneth P. Young, Semi-solid Processing of Alloys, 2010, XII, 172 p. 103 illus., 19 in color., Hardcover ISBN: 978-3-642-00705-7.

09-10  Shannon Wetzel, Fullfilling Da Vinci’s Dream, Modern Casting, April 2010.

08-10 B.I. Semenov, K.M. Kushtarov, Semi-solid Manufacturing of Castings, New Industrial Technologies, Publication of Moscow State Technical University n.a. N.E. Bauman, 2009 (in Russian)

07-10 Carl Reilly, Development Of Quantitative Casting Quality Assessment Criteria Using Process Modelling, thesis: The University of Birmingham, March 2010 (Available upon request)

06-10 A. Pari, Optimization of HPDC Process using Flow Simulation – Case Studies, CastExpo ’10, NADCA, Orlando, Florida, March 2010

05-10 M.C. Carter, S. Palit, and M. Littler, Characterizing Flow Losses Occurring in Air Vents and Ejector Pins in High Pressure Die Castings, CastExpo ’10, NADCA, Orlando, Florida, March 2010

04-10 Pamela Waterman, Simulating Porosity Factors, Foundry Management Technology, March 2010, Article available at Foundry Management Technology

03-10 C. Reilly, M.R. Jolly, N.R. Green, JC Gebelin, Assessment of Casting Filling by Modeling Surface Entrainment Events Using CFD, 2010 TMS Annual Meeting & Exhibition (Jim Evans Honorary Symposium), Seattle, Washington, USA, February 14-18, 2010

02-10 P. Väyrynen, S. Wang, J. Laine and S.Louhenkilpi, Control of Fluid Flow, Heat Transfer and Inclusions in Continuous Casting – CFD and Neural Network Studies, 2010 TMS Annual Meeting & Exhibition (Jim Evans Honorary Symposium), Seattle, Washington, USA, February 14-18, 2010

60-09   Somlak Wannarumon, and Marco Actis Grande, Comparisons of Computer Fluid Dynamic Software Programs applied to Jewelry Investment Casting Process, World Academy of Science, Engineering and Technology 55 2009.

59-09   Marco Actis Grande and Somlak Wannarumon, Numerical Simulation of Investment Casting of Gold Jewelry: Experiments and Validations, World Academy of Science, Engineering and Technology, Vol:3 2009-07-24

56-09  Jozef Kasala, Ondrej Híreš, Rudolf Pernis, Start-up Phase Modeling of Semi Continuous Casting Process of Brass Billets, Metal 2009, 19.-21.5.2009

51-09  In-Ting Hong, Huan-Chien Tung, Chun-Hao Chiu and Hung-Shang Huang, Effect of Casting Parameters on Microstructure and Casting Quality of Si-Al Alloy for Vacuum Sputtering, China Steel Technical Report, No. 22, pp. 33-40, 2009.

42-09  P. Väyrynen, S. Wang, S. Louhenkilpi and L. Holappa, Modeling and Removal of Inclusions in Continuous Casting, Materials Science & Technology 2009 Conference & Exhibition, Pittsburgh, Pennsylvania, USA, October 25-29, 2009

41-09 O.Smirnov, P.Väyrynen, A.Kravchenko and S.Louhenkilpi, Modern Methods of Modeling Fluid Flow and Inclusions Motion in Tundish Bath – General View, Proceedings of Steelsim 2009 – 3rd International Conference on Simulation and Modelling of Metallurgical Processes in Steelmaking, Leoben, Austria, September 8-10, 2009

21-09 A. Pari, Case Studies – Optimization of HPDC Process Using Flow Simulation, Die Casting Engineer, July 2009

20-09 M. Sirvio, M. Wos, Casting directly from a computer model by using advanced simulation software, FLOW-3D Cast, Archives of Foundry Engineering Volume 9, Issue 1/2009, 79-82

19-09 Andrei Starobin, C.W. Hirt, D. Goettsch, A Model for Binder Gas Generation and Transport in Sand Cores and Molds, Modeling of Casting, Welding, and Solidification Processes XII, TMS (The Minerals, Metals & Minerals Society), June 2009

11-09 Michael Barkhudarov, Minimizing Air Entrainment in a Shot Sleeve during Slow-Shot Stage, Die Casting Engineer (The North American Die Casting Association ISSN 0012-253X), May 2009

10-09 A. Reikher, H. Gerber, Application of One-Dimensional Numerical Simulation to Optimize Process Parameters of a Thin-Wall Casting in High Pressure Die Casting, Die Casting Engineer (The North American Die Casting Association ISSN 0012-253X), May 2009

7-09 Andrei Starobin, Simulation of Core Gas Evolution and Flow, presented at the North American Die Casting Association – 113th Metalcasting Congress, April 7-10, 2009, Las Vegas, Nevada, USA

6-09 A.Pari, Optimization of HPDC PROCESS: Case Studies, North American Die Casting Association – 113th Metalcasting Congress, April 7-10, 2009, Las Vegas, Nevada, USA

2-09 C. Reilly, N.R. Green and M.R. Jolly, Oxide Entrainment Structures in Horizontal Running Systems, TMS 2009, San Francisco, California, February 2009

30-08 I.N.Volnov, Computer Modeling of Casting of Pipe Fittings, © 2008, Pipe Fittings, 5 (38), 2008. Russian version

28-08 A.V.Chaikin, I.N.Volnov, V.A.Chaikin, Y.A.Ukhanov, N.R.Petrov, Analysis of the Efficiency of Alloy Modifiers Using Statistics and Modeling, © 2008, Liteyshik Rossii (Russian Foundryman), October, 2008

27-08 P. Scarber, Jr., H. Littleton, Simulating Macro-Porosity in Aluminum Lost Foam Castings, American Foundry Society, © 2008, AFS Lost Foam Conference, Asheville, North Carolina, October, 2008

25-08 FMT Staff, Forecasting Core Gas Pressures with Computer Simulation, Foundry Management and Technology, October 28, 2008 © 2008 Penton Media, Inc. Online article

24-08 Core and Mold Gas Evolution, Foundry Management and Technology, January 24, 2008 (excerpted from the FM&T May 2007 issue) © 2008 Penton Media, Inc.

22-08 Mark Littler, Simulation Eliminates Die Casting Scrap, Modern Casting/September 2008

21-08 X. Chen, D. Penumadu, Permeability Measurement and Numerical Modeling for Refractory Porous Materials, AFS Transactions © 2008 American Foundry Society, CastExpo ’08, Atlanta, Georgia, May 2008

20-08 Rolf Krack, Using Solidification Simulations for Optimising Die Cooling Systems, FTJ July/August 2008

19-08 Mark Littler, Simulation Software Eliminates Die Casting Scrap, ECS Casting Innovations, July/August 2008

13-08 T. Yoshimura, K. Yano, T. Fukui, S. Yamamoto, S. Nishido, M. Watanabe and Y. Nemoto, Optimum Design of Die Casting Plunger Tip Considering Air Entrainment, Proceedings of 10th Asian Foundry Congress (AFC10), Nagoya, Japan, May 2008

08-08 Stephen Instone, Andreas Buchholz and Gerd-Ulrich Gruen, Inclusion Transport Phenomena in Casting Furnaces, Light Metals 2008, TMS (The Minerals, Metals & Materials Society), 2008

07-08 P. Scarber, Jr., H. Littleton, Simulating Macro-Porosity in Aluminum Lost Foam Casting, AFS Transactions 2008 © American Foundry Society, CastExpo ’08, Atlanta, Georgia, May 2008

06-08 A. Reikher, H. Gerber and A. Starobin, Multi-Stage Plunger Deceleration System, CastExpo ’08, NADCA, Atlanta, Georgia, May 2008

05-08 Amol Palekar, Andrei Starobin, Alexander Reikher, Die-casting end-of-fill and drop forge viscometer flow transients examined with a coupled-motion numerical model, 68th World Foundry Congress, Chennai, India, February 2008

03-08 Petri J. Väyrynen, Sami K. Vapalahti and Seppo J. Louhenkilpi, On Validation of Mathematical Fluid Flow Models for Simulation of Tundish Water Models and Industrial Examples, AISTech 2008, May 2008

53-07   A. Kermanpur, Sh. Mahmoudi and A. Hajipour, Three-dimensional Numerical Simulation of Metal Flow and Solidification in the Multi-cavity Casting Moulds of Automotive Components, International Journal of Iron & Steel Society of Iran, Article 2, Volume 4, Issue 1, Summer and Autumn 2007, pages 8-15.

36-07 Duque Mesa A. F., Herrera J., Cruz L.J., Fernández G.P. y Martínez H.V., Caracterización Defectológica de Piezas Fundida por Lost Foam Casting Mediante Simulación Numérica, 8° Congreso Iberoamericano de Ingenieria Mecanica, Cusco, Peru, 23 al 25 de Octubre de 2007 (in Spanish)

27-07 A.Y. Korotchenko, A.M. Zarubin, I.A.Korotchenko, Modeling of High Pressure Die Casting Filling, Russian Foundryman, December 2007, pp 15-19. (in Russian)

26-07 I.N. Volnov, Modeling of Casting Processes with Variable Geometry, Russian Foundryman, November 2007, pp 27-30. (in Russian)

16-07 P. Väyrynen, S. Vapalahti, S. Louhenkilpi, L. Chatburn, M. Clark, T. Wagner, Tundish Flow Model Tuning and Validation – Steady State and Transient Casting Situations, STEELSIM 2007, Graz/Seggau, Austria, September 12-14 2007

11-07 Marco Actis Grande, Computer Simulation of the Investment Casting Process – Widening of the Filling Step, Santa Fe Symposium on Jewelry Manufacturing Technology, May 2007

09-07 Alexandre Reikher and Michael Barkhudarov, Casting: An Analytical Approach, Springer, 1st edition, August 2007, Hardcover ISBN: 978-1-84628-849-4. U.S. Order Form; Europe Order Form.

07-07 I.N. Volnov, Casting Modeling Systems – Current State, Problems and Perspectives, (in Russian), Liteyshik Rossii (Russian Foundryman), June 2007

05-07 A.N. Turchin, D.G. Eskin, and L. Katgerman, Solidification under Forced-Flow Conditions in a Shallow Cavity, DOI: 10.1007/s1161-007-9183-9, © The Minerals, Metals & Materials Society and ASM International 2007

04-07 A.N. Turchin, M. Zuijderwijk, J. Pool, D.G. Eskin, and L. Katgerman, Feathery grain growth during solidification under forced flow conditions, © Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. DOI: 10.1016/j.actamat.2007.02.030, April 2007

03-07 S. Kuyucak, Sponsored Research – Clean Steel Casting Production—Evaluation of Laboratory Castings, Transactions of the American Foundry Society, Volume 115, 111th Metalcasting Congress, May 2007

02-07 Fu-Yuan Hsu, Mark R. Jolly and John Campbell, The Design of L-Shaped Runners for Gravity Casting, Shape Casting: 2nd International Symposium, Edited by Paul N. Crepeau, Murat Tiryakioðlu and John Campbell, TMS (The Minerals, Metals & Materials Society), Orlando, FL, Feb 2007

30-06 X.J. Liu, S.H. Bhavnani, R.A. Overfelt, Simulation of EPS foam decomposition in the lost foam casting process, Journal of Materials Processing Technology 182 (2007) 333–342, © 2006 Elsevier B.V. All rights reserved.

25-06 Michael Barkhudarov and Gengsheng Wei, Modeling Casting on the Move, Modern Casting, August 2006; Modeling of Casting Processes with Variable Geometry, Russian Foundryman, December 2007, pp 10-15. (in Russian)

24-06 P. Scarber, Jr. and C.E. Bates, Simulation of Core Gas Production During Mold Fill, © 2006 American Foundry Society

7-06 M.Y.Smirnov, Y.V.Golenkov, Manufacturing of Cast Iron Bath Tubs Castings using Vacuum-Process in Russia, Russia’s Foundryman, July 2006. In Russian.

6-06 M. Barkhudarov, and G. Wei, Modeling of the Coupled Motion of Rigid Bodies in Liquid Metal, Modeling of Casting, Welding and Advanced Solidification Processes – XI, May 28 – June 2, 2006, Opio, France, eds. Ch.-A. Gandin and M. Bellet, pp 71-78, 2006.

2-06 J.-C. Gebelin, M.R. Jolly and F.-Y. Hsu, ‘Designing-in’ Controlled Filling Using Numerical Simulation for Gravity Sand Casting of Aluminium Alloys, Int. J. Cast Met. Res., 2006, Vol.19 No.1

1-06 Michael Barkhudarov, Using Simulation to Control Microporosity Reduces Die Iterations, Die Casting Engineer, January 2006, pp. 52-54

30-05 H. Xue, K. Kabiri-Bamoradian, R.A. Miller, Modeling Dynamic Cavity Pressure and Impact Spike in Die Casting, Cast Expo ’05, April 16-19, 2005

22-05 Blas Melissari & Stavros A. Argyropoulous, Measurement of Magnitude and Direction of Velocity in High-Temperature Liquid Metals; Part I, Mathematical Modeling, Metallurgical and Materials Transactions B, Volume 36B, October 2005, pp. 691-700

21-05 M.R. Jolly, State of the Art Review of Use of Modeling Software for Casting, TMS Annual Meeting, Shape Casting: The John Campbell Symposium, Eds, M. Tiryakioglu & P.N Crepeau, TMS, Warrendale, PA, ISBN 0-87339-583-2, Feb 2005, pp 337-346

20-05 J-C Gebelin, M.R. Jolly & F-Y Hsu, ‘Designing-in’ Controlled Filling Using Numerical Simulation for Gravity Sand Casting of Aluminium Alloys, TMS Annual Meeting, Shape Casting: The John Campbell Symposium, Eds, M. Tiryakioglu & P.N Crepeau, TMS, Warrendale, PA, ISBN 0-87339-583-2, Feb 2005, pp 355-364

19-05 F-Y Hsu, M.R. Jolly & J Campbell, Vortex Gate Design for Gravity Castings, TMS Annual Meeting, Shape Casting: The John Campbell Symposium, Eds, M. Tiryakioglu & P.N Crepeau, TMS, Warrendale, PA, ISBN 0-87339-583-2, Feb 2005, pp 73-82

18-05 M.R. Jolly, Modelling the Investment Casting Process: Problems and Successes, Japanese Foundry Society, JFS, Tokyo, Sept. 2005

13-05 Xiaogang Yang, Xiaobing Huang, Xiaojun Dai, John Campbell and Joe Tatler, Numerical Modelling of the Entrainment of Oxide Film Defects in Filling of Aluminium Alloy Castings, International Journal of Cast Metals Research, 17 (6), 2004, 321-331

10-05 Carlos Evaristo Esparza, Martha P. Guerro-Mata, Roger Z. Ríos-Mercado, Optimal Design of Gating Systems by Gradient Search Methods, Computational Materials Science, October 2005

6-05 Birgit Hummler-Schaufler, Fritz Hirning, Jurgen Schaufler, A World First for Hatz Diesel and Schaufler Tooling, Die Casting Engineer, May 2005, pp. 18-21

4-05 Rolf Krack, The W35 Topic—A World First, Die Casting World, March 2005, pp. 16-17

3-05 Joerg Frei, Casting Simulations Speed Up Development, Die Casting World, March 2005, p. 14

2-05 David Goettsch and Michael Barkhudarov, Analysis and Optimization of the Transient Stage of Stopper-Rod Pour, Shape Casting: The John Campbell Symposium, The Minerals, Metals & Materials Society, 2005

36-04  Ik Min Park, Il Dong Choi, Yong Ho Park, Development of Light-Weight Al Scroll Compressor for Car Air Conditioner, Materials Science Forum, Designing, Processing and Properties of Advanced Engineering Materials, 449-452, 149, March 2004.

32-04 D.H. Kirkwood and P.J Ward, Numerical Modelling of Semi-Solid Flow under Processing Conditions, steel research int. 75 (2004), No. 8/9

30-04 Haijing Mao, A Numerical Study of Externally Solidified Products in the Cold Chamber Die Casting Process, thesis: The Ohio State University, 2004 (Available upon request)

28-04 Z. Cao, Z. Yang, and X.L. Chen, Three-Dimensional Simulation of Transient GMA Weld Pool with Free Surface, Supplement to the Welding Journal, June 2004.

23-04 State of the Art Use of Computational Modelling in the Foundry Industry, 3rd International Conference Computational Modelling of Materials III, Sicily, Italy, June 2004, Advances in Science and Technology,  Eds P. Vincenzini & A Lami, Techna Group Srl, Italy, ISBN: 88-86538-46-4, Part B, pp 479-490

22-04 Jerry Fireman, Computer Simulation Helps Reduce Scrap, Die Casting Engineer, May 2004, pp. 46-49

21-04 Joerg Frei, Simulation—A Safe and Quick Way to Good Components, Aluminium World, Volume 3, Issue 2, pp. 42-43

20-04 J.-C. Gebelin, M.R. Jolly, A. M. Cendrowicz, J. Cirre and S. Blackburn, Simulation of Die Filling for the Wax Injection Process – Part II Numerical Simulation, Metallurgical and Materials Transactions, Volume 35B, August 2004

14-04 Sayavur I. Bakhtiyarov, Charles H. Sherwin, and Ruel A. Overfelt, Hot Distortion Studies In Phenolic Urethane Cold Box System, American Foundry Society, 108th Casting Congress, June 12-15, 2004, Rosemont, IL, USA

13-04 Sayavur I. Bakhtiyarov and Ruel A. Overfelt, First V-Process Casting of Magnesium, American Foundry Society, 108th Casting Congress, June 12-15, 2004, Rosemont, IL, USA

5-04 C. Schlumpberger & B. Hummler-Schaufler, Produktentwicklung auf hohem Niveau (Product Development on a High Level), Druckguss Praxis, January 2004, pp 39-42 (in German).

3-04 Charles Bates, Dealing with Defects, Foundry Management and Technology, February 2004, pp 23-25

1-04 Laihua Wang, Thang Nguyen, Gary Savage and Cameron Davidson, Thermal and Flow Modeling of Ladling and Injection in High Pressure Die Casting Process, International Journal of Cast Metals Research, vol. 16 No 4 2003, pp 409-417

2-03 J-C Gebelin, AM Cendrowicz, MR Jolly, Modeling of the Wax Injection Process for the Investment Casting Process – Prediction of Defects, presented at the Third International Conference on Computational Fluid Dynamics in the Minerals and Process Industries, December 10-12, 2003, Melbourne, Australia, pp. 415-420

29-03 C. W. Hirt, Modeling Shrinkage Induced Micro-porosity, Flow Science Technical Note (FSI-03-TN66)

28-03 Thixoforming at the University of Sheffield, Diecasting World, September 2003, pp 11-12

26-03 William Walkington, Gas Porosity-A Guide to Correcting the Problems, NADCA Publication: 516

22-03 G F Yao, C W Hirt, and M Barkhudarov, Development of a Numerical Approach for Simulation of Sand Blowing and Core Formation, in Modeling of Casting, Welding, and Advanced Solidification Process-X”, Ed. By Stefanescu et al pp. 633-639, 2003

21-03 E F Brush Jr, S P Midson, W G Walkington, D T Peters, J G Cowie, Porosity Control in Copper Rotor Die Castings, NADCA Indianapolis Convention Center, Indianapolis, IN September 15-18, 2003, T03-046

12-03 J-C Gebelin & M.R. Jolly, Modeling Filters in Light Alloy Casting Processes,  Trans AFS, 2002, 110, pp. 109-120

11-03 M.R. Jolly, Casting Simulation – How Well Do Reality and Virtual Casting Match – A State of the Art Review, Intl. J. Cast Metals Research, 2002, 14, pp. 303-313

10-03 Gebelin., J-C and Jolly, M.R., Modeling of the Investment Casting Process, Journal of  Materials Processing Tech., Vol. 135/2-3, pp. 291 – 300

9-03 Cox, M, Harding, R.A. and Campbell, J., Optimised Running System Design for Bottom Filled Aluminium Alloy 2L99 Investment Castings, J. Mat. Sci. Tech., May 2003, Vol. 19, pp. 613-625

8-03 Von Alexander Schrey and Regina Reek, Numerische Simulation der Kernherstellung, (Numerical Simulation of Core Blowing), Giesserei, June 2003, pp. 64-68 (in German)

7-03 J. Zuidema Jr., L Katgerman, Cyclone separation of particles in aluminum DC Casting, Proceedings from the Tenth International Conference on Modeling of Casting, Welding and Advanced Solidification Processes, Destin, FL, May 2003, pp. 607-614

6-03 Jean-Christophe Gebelin and Mark Jolly, Numerical Modeling of Metal Flow Through Filters, Proceedings from the Tenth International Conference on Modeling of Casting, Welding and Advanced Solidification Processes, Destin, FL, May 2003, pp. 431-438

5-03 N.W. Lai, W.D. Griffiths and J. Campbell, Modelling of the Potential for Oxide Film Entrainment in Light Metal Alloy Castings, Proceedings from the Tenth International Conference on Modeling of Casting, Welding and Advanced Solidification Processes, Destin, FL, May 2003, pp. 415-422

21-02 Boris Lukezic, Case History: Process Modeling Solves Die Design Problems, Modern Casting, February 2003, P 59

20-02 C.W. Hirt and M.R. Barkhudarov, Predicting Defects in Lost Foam Castings, Modern Casting, December 2002, pp 31-33

19-02 Mark Jolly, Mike Cox, Ric Harding, Bill Griffiths and John Campbell, Quiescent Filling Applied to Investment Castings, Modern Casting, December 2002 pp. 36-38

18-02 Simulation Helps Overcome Challenges of Thin Wall Magnesium Diecasting, Foundry Management and Technology, October 2002, pp 13-15

17-02 G Messmer, Simulation of a Thixoforging Process of Aluminum Alloys with FLOW-3D, Institute for Metal Forming Technology, University of Stuttgart

16-02 Barkhudarov, Michael, Computer Simulation of Lost Foam Process, Casting Simulation Background and Examples from Europe and the USA, World Foundrymen Organization, 2002, pp 319-324

15-02 Barkhudarov, Michael, Computer Simulation of Inclusion Tracking, Casting Simulation Background and Examples from Europe and the USA, World Foundrymen Organization, 2002, pp 341-346

14-02 Barkhudarov, Michael, Advanced Simulation of the Flow and Heat Transfer of an Alternator Housing, Casting Simulation Background and Examples from Europe and the USA, World Foundrymen Organization, 2002, pp 219-228

8-02 Sayavur I. Bakhtiyarov, and Ruel A. Overfelt, Experimental and Numerical Study of Bonded Sand-Air Two-Phase Flow in PUA Process, Auburn University, 2002 American Foundry Society, AFS Transactions 02-091, Kansas City, MO

7-02 A Habibollah Zadeh, and J Campbell, Metal Flow Through a Filter System, University of Birmingham, 2002 American Foundry Society, AFS Transactions 02-020, Kansas City, MO

6-02 Phil Ward, and Helen Atkinson, Final Report for EPSRC Project: Modeling of Thixotropic Flow of Metal Alloys into a Die, GR/M17334/01, March 2002, University of Sheffield

5-02 S. I. Bakhtiyarov and R. A. Overfelt, Numerical and Experimental Study of Aluminum Casting in Vacuum-sealed Step Molding, Auburn University, 2002 American Foundry Society, AFS Transactions 02-050, Kansas City, MO

4-02 J. C. Gebelin and M. R. Jolly, Modelling Filters in Light Alloy Casting Processes, University of Birmingham, 2002 American Foundry Society AFS Transactions 02-079, Kansas City, MO

3-02 Mark Jolly, Mike Cox, Jean-Christophe Gebelin, Sam Jones, and Alex Cendrowicz, Fundamentals of Investment Casting (FOCAST), Modelling the Investment Casting Process, Some preliminary results from the UK Research Programme, IRC in Materials, University of Birmingham, UK, AFS2001

49-01   Hua Bai and Brian G. Thomas, Bubble formation during horizontal gas injection into downward-flowing liquid, Metallurgical and Materials Transactions B, Vol. 32, No. 6, pp. 1143-1159, 2001. doi.org/10.1007/s11663-001-0102-y

45-01 Jan Zuidema; Laurens Katgerman; Ivo J. Opstelten;Jan M. Rabenberg, Secondary Cooling in DC Casting: Modelling and Experimental Results, TMS 2001, New Orleans, Louisianna, February 11-15, 2001

43-01 James Andrew Yurko, Fluid Flow Behavior of Semi-Solid Aluminum at High Shear Rates,Ph.D. thesis; Massachusetts Institute of Technology, June 2001. Abstract only; full thesis available at http://dspace.mit.edu/handle/1721.1/8451 (for a fee).

33-01 Juang, S.H., CAE Application on Design of Die Casting Dies, 2001 Conference on CAE Technology and Application, Hsin-Chu, Taiwan, November 2001, (article in Chinese with English-language abstract)

32-01 Juang, S.H. and C. M. Wang, Effect of Feeding Geometry on Flow Characteristics of Magnesium Die Casting by Numerical Analysis, The Preceedings of 6th FADMA Conference, Taipei, Taiwan, July 2001, Chinese language with English abstract

26-01 C. W. Hirt., Predicting Defects in Lost Foam Castings, December 13, 2001

21-01 P. Scarber Jr., Using Liquid Free Surface Areas as a Predictor of Reoxidation Tendency in Metal Alloy Castings, presented at the Steel Founders’ Society of American, Technical and Operating Conference, October 2001

20-01 P. Scarber Jr., J. Griffin, and C. E. Bates, The Effect of Gating and Pouring Practice on Reoxidation of Steel Castings, presented at the Steel Founders’ Society of American, Technical and Operating Conference, October 2001

19-01 L. Wang, T. Nguyen, M. Murray, Simulation of Flow Pattern and Temperature Profile in the Shot Sleeve of a High Pressure Die Casting Process, CSIRO Manufacturing Science and Technology, Melbourne, Victoria, Australia, Presented by North American Die Casting Association, Oct 29-Nov 1, 2001, Cincinnati, To1-014

18-01 Rajiv Shivpuri, Venkatesh Sankararaman, Kaustubh Kulkarni, An Approach at Optimizing the Ingate Design for Reducing Filling and Shrinkage Defects, The Ohio State University, Columbus, OH, Presented by North American Die Casting Association, Oct 29-Nov 1, 2001, Cincinnati, TO1-052

5-01 Michael Barkhudarov, Simulation Helps Overcome Challenges of Thin Wall Magnesium Diecasting, Diecasting World, March 2001, pp. 5-6

2-01 J. Grindling, Customized CFD Codes to Simulate Casting of Thermosets in Full 3D, Electrical Manufacturing and Coil Winding 2000 Conference, October 31-November 2, 20

20-00 Richard Schuhmann, John Carrig, Thang Nguyen, Arne Dahle, Comparison of Water Analogue Modelling and Numerical Simulation Using Real-Time X-Ray Flow Data in Gravity Die Casting, Australian Die Casting Association Die Casting 2000 Conference, September 3-6, 2000, Melbourne, Victoria, Australia

15-00 M. Sirvio, Vainola, J. Vartianinen, M. Vuorinen, J. Orkas, and S. Devenyi, Fluid Flow Analysis for Designing Gating of Aluminum Castings, Proc. NADCA Conf., Rosemont, IL, Nov 6-8, 1999

14-00 X. Yang, M. Jolly, and J. Campbell, Reduction of Surface Turbulence during Filling of Sand Castings Using a Vortex-flow Runner, Conference for Modeling of Casting, Welding, and Advanced Solidification Processes IX, Aachen, Germany, August 2000

13-00 H. S. H. Lo and J. Campbell, The Modeling of Ceramic Foam Filters, Conference for Modeling of Casting, Welding, and Advanced Solidification Processes IX, Aachen, Germany, August 2000

12-00 M. R. Jolly, H. S. H. Lo, M. Turan and J. Campbell, Use of Simulation Tools in the Practical Development of a Method for Manufacture of Cast Iron Camshafts,” Conference for Modeling of Casting, Welding, and Advanced Solidification Processes IX, Aachen, Germany, August, 2000

14-99 J Koke, and M Modigell, Time-Dependent Rheological Properties of Semi-solid Metal Alloys, Institute of Chemical Engineering, Aachen University of Technology, Mechanics of Time-Dependent Materials 3: 15-30, 1999

12-99 Grun, Gerd-Ulrich, Schneider, Wolfgang, Ray, Steven, Marthinusen, Jan-Olaf, Recent Improvements in Ceramic Foam Filter Design by Coupled Heat and Fluid Flow Modeling, Proc TMS Annual Meeting, 1999, pp. 1041-1047

10-99 Bongcheol Park and Jerald R. Brevick, Computer Flow Modeling of Cavity Pre-fill Effects in High Pressure Die Casting, NADCA Proceedings, Cleveland T99-011, November, 1999

8-99 Brad Guthrie, Simulation Reduces Aluminum Die Casting Cost by Reducing Volume, Die Casting Engineer Magazine, September/October 1999, pp. 78-81

7-99 Fred L. Church, Virtual Reality Predicts Cast Metal Flow, Modern Metals, September, 1999, pp. 67F-J

19-98 Grun, Gerd-Ulrich, & Schneider, Wolfgang, Numerical Modeling of Fluid Flow Phenomena in the Launder-integrated Tool Within Casting Unit Development, Proc TMS Annual Meeting, 1998, pp. 1175-1182

18-98 X. Yang & J. Campbell, Liquid Metal Flow in a Pouring Basin, Int. J. Cast Metals Res, 1998, 10, pp. 239-253

15-98 R. Van Tol, Mould Filling of Horizontal Thin-Wall Castings, Delft University Press, The Netherlands, 1998

14-98 J. Daughtery and K. A. Williams, Thermal Modeling of Mold Material Candidates for Copper Pressure Die Casting of the Induction Motor Rotor Structure, Proc. Int’l Workshop on Permanent Mold Casting of Copper-Based Alloys, Ottawa, Ontario, Canada, Oct. 15-16, 1998

10-98 C. W. Hirt, and M.R. Barkhudarov, Lost Foam Casting Simulation with Defect Prediction, Flow Science Inc, presented at Modeling of Casting, Welding and Advanced Solidification Processes VIII Conference, June 7-12, 1998, Catamaran Hotel, San Diego, California

9-98 M. R. Barkhudarov and C. W. Hirt, Tracking Defects, Flow Science Inc, presented at the 1st International Aluminum Casting Technology Symposium, 12-14 October 1998, Rosemont, IL

5-98 J. Righi, Computer Simulation Helps Eliminate Porosity, Die Casting Management Magazine, pp. 36-38, January 1998

3-98 P. Kapranos, M. R. Barkhudarov, D. H. Kirkwood, Modeling of Structural Breakdown during Rapid Compression of Semi-Solid Alloy Slugs, Dept. Engineering Materials, The University of Sheffield, Sheffield S1 3JD, U.K. and Flow Science Inc, USA, Presented at the 5th International Conference Semi-Solid Processing of Alloys and Composites, Colorado School of Mines, Golden, CO, 23-25 June 1998

1-98 U. Jerichow, T. Altan, and P. R. Sahm, Semi Solid Metal Forming of Aluminum Alloys-The Effect of Process Variables Upon Material Flow, Cavity Fill and Mechanical Properties, The Ohio State University, Columbus, OH, published in Die Casting Engineer, p. 26, Jan/Feb 1998

8-97 Michael Barkhudarov, High Pressure Die Casting Simulation Using FLOW-3D, Die Casting Engineer, 1997

15-97 M. R. Barkhudarov, Advanced Simulation of the Flow and Heat Transfer Process in Simultaneous Engineering, Flow Science report, presented at the Casting 1997 – International ADI and Simulation Conference, Helsinki, Finland, May 28-30, 1997

14-97 M. Ranganathan and R. Shivpuri, Reducing Scrap and Increasing Die Life in Low Pressure Die Casting through Flow Simulation and Accelerated Testing, Dept. Welding and Systems Engineering, Ohio State University, Columbus, OH, presented at 19th International Die Casting Congress & Exposition, November 3-6, 1997

13-97 J. Koke, Modellierung und Simulation der Fließeigenschaften teilerstarrter Metallegierungen, Livt Information, Institut für Verfahrenstechnik, RWTH Aachen, October 1997

10-97 J. P. Greene and J. O. Wilkes, Numerical Analysis of Injection Molding of Glass Fiber Reinforced Thermoplastics – Part 2 Fiber Orientation, Body-in-White Center, General Motors Corp. and Dept. Chemical Engineering, University of Michigan, Polymer Engineering and Science, Vol. 37, No. 6, June 1997

9-97 J. P. Greene and J. O. Wilkes, Numerical Analysis of Injection Molding of Glass Fiber Reinforced Thermoplastics. Part 1 – Injection Pressures and Flow, Manufacturing Center, General Motors Corp. and Dept. Chemical Engineering, University of Michigan, Polymer Engineering and Science, Vol. 37, No. 3, March 1997

8-97 H. Grazzini and D. Nesa, Thermophysical Properties, Casting Simulation and Experiments for a Stainless Steel, AT Systemes (Renault) report, presented at the Solidification Processing ’97 Conference, July 7-10, 1997, Sheffield, U.K.

7-97 R. Van Tol, L. Katgerman and H. E. A. Van den Akker, Horizontal Mould Filling of a Thin Wall Aluminum Casting, Laboratory of Materials report, Delft University, presented at the Solidification Processing ’97 Conference, July 7-10, 1997, Sheffield, U.K.

6-97 M. R. Barkhudarov, Is Fluid Flow Important for Predicting Solidification, Flow Science report, presented at the Solidification Processing ’97 Conference, July 7-10, 1997, Sheffield, U.K.

22-96 Grun, Gerd-Ulrich & Schneider, Wolfgang, 3-D Modeling of the Start-up Phase of DC Casting of Sheet Ingots, Proc TMS Annual Meeting, 1996, pp. 971-981

9-96 M. R. Barkhudarov and C. W. Hirt, Thixotropic Flow Effects under Conditions of Strong Shear, Flow Science report FSI96-00-2, to be presented at the “Materials Week ’96” TMS Conference, Cincinnati, OH, 7-10 October 1996

4-96 C. W. Hirt, A Computational Model for the Lost Foam Process, Flow Science final report, February 1996 (FSI-96-57-R2)

3-96 M. R. Barkhudarov, C. L. Bronisz, C. W. Hirt, Three-Dimensional Thixotropic Flow Model, Flow Science report, FSI-96-00-1, published in the proceedings of (pp. 110- 114) and presented at the 4th International Conference on Semi-Solid Processing of Alloys and Composites, The University of Sheffield, 19-21 June 1996

1-96 M. R. Barkhudarov, J. Beech, K. Chang, and S. B. Chin, Numerical Simulation of Metal/Mould Interfacial Heat Transfer in Casting, Dept. Mech. & Process Engineering, Dept. Engineering Materials, University of Sheffield and Flow Science Inc, 9th Int. Symposium on Transport Phenomena in Thermal-Fluid Engineering, June 25-28, 1996, Singapore

11-95 Barkhudarov, M. R., Hirt, C.W., Casting Simulation Mold Filling and Solidification-Benchmark Calculations Using FLOW-3D, Modeling of Casting, Welding, and Advanced Solidification Processes VII, pp 935-946

10-95 Grun, Gerd-Ulrich, & Schneider, Wolfgang, Optimal Design of a Distribution Pan for Level Pour Casting, Proc TMS Annual Meeting, 1995, pp. 1061-1070

9-95 E. Masuda, I. Itoh, K. Haraguchi, Application of Mold Filling Simulation to Die Casting Processes, Honda Engineering Co., Ltd., Tochigi, Japan, presented at the Modelling of Casting, Welding and Advanced Solidification Processes VII, The Minerals, Metals & Materials Society, 1995

6-95 K. Venkatesan, Experimental and Numerical Investigation of the Effect of Process Parameters on the Erosive Wear of Die Casting Dies, presented for Ph.D. degree at Ohio State University, 1995

5-95 J. Righi, A. F. LaCamera, S. A. Jones, W. G. Truckner, T. N. Rouns, Integration of Experience and Simulation Based Understanding in the Die Design Process, Alcoa Technical Center, Alcoa Center, PA 15069, presented by the North American Die Casting Association, 1995

2-95 K. Venkatesan and R. Shivpuri, Numerical Simulation and Comparison with Water Modeling Studies of the Inertia Dominated Cavity Filling in Die Casting, NUMIFORM, 1995

1-95 K. Venkatesan and R. Shivpuri, Numerical Investigation of the Effect of Gate Velocity and Gate Size on the Quality of Die Casting Parts, NAMRC, 1995.

15-94 D. Liang, Y. Bayraktar, S. A. Moir, M. Barkhudarov, and H. Jones, Primary Silicon Segregation During Isothermal Holding of Hypereutectic AI-18.3%Si Alloy in the Freezing Range, Dept. of Engr. Materials, U. of Sheffield, Metals and Materials, February 1994

13-94 Deniece Korzekwa and Paul Dunn, A Combined Experimental and Modeling Approach to Uranium Casting, Materials Division, Los Alamos National Laboratory, presented at the Symposium on Liquid Metal Processing and Casting, El Dorado Hotel, Santa Fe, New Mexico, 1994

12-94 R. van Tol, H. E. A. van den Akker and L. Katgerman, CFD Study of the Mould Filling of a Horizontal Thin Wall Aluminum Casting, Delft University of Technology, Delft, The Netherlands, HTD-Vol. 284/AMD-Vol. 182, Transport Phenomena in Solidification, ASME 1994

11-94 M. R. Barkhudarov and K. A. Williams, Simulation of ‘Surface Turbulence’ Fluid Phenomena During the Mold Filling Phase of Gravity Castings, Flow Science Technical Note #41, November 1994 (FSI-94-TN41)

10-94 M. R. Barkhudarov and S. B. Chin, Stability of a Numerical Algorithm for Gas Bubble Modelling, University of Sheffield, Sheffield, U.K., International Journal for Numerical Methods in Fluids, Vol. 19, 415-437 (1994)

16-93 K. Venkatesan and R. Shivpuri, Numerical Simulation of Die Cavity Filling in Die Castings and an Evaluation of Process Parameters on Die Wear, Dept. of Industrial Systems Engineering, Presented by: N.A. Die Casting Association, Cleveland, Ohio, October 18-21, 1993

15-93 K. Venkatesen and R. Shivpuri, Numerical Modeling of Filling and Solidification for Improved Quality of Die Casting: A Literature Survey (Chapters II and III), Engineering Research Center for Net Shape Manufacturing, Report C-93-07, August 1993, Ohio State University

1-93 P-E Persson, Computer Simulation of the Solidification of a Hub Carrier for the Volvo 800 Series, AB Volvo Technological Development, Metals Laboratory, Technical Report No. LM 500014E, Jan. 1993

13-92 D. R. Korzekwa, M. A. K. Lewis, Experimentation and Simulation of Gravity Fed Lead Castings, in proceedings of a TMS Symposium on Concurrent Engineering Approach to Materials Processing, S. N. Dwivedi, A. J. Paul and F. R. Dax, eds., TMS-AIME Warrendale, p. 155 (1992)

12-92 M. A. K. Lewis, Near-Net-Shaiconpe Casting Simulation and Experimentation, MST 1992 Review, Los Alamos National Laboratory

2-92 M. R. Barkhudarov, H. You, J. Beech, S. B. Chin, D. H. Kirkwood, Validation and Development of FLOW-3D for Casting, School of Materials, University of Sheffield, Sheffield, UK, presented at the TMS/AIME Annual Meeting, San Diego, CA, March 3, 1992

1-92 D. R. Korzekwa and L. A. Jacobson, Los Alamos National Laboratory and C.W. Hirt, Flow Science Inc, Modeling Planar Flow Casting with FLOW-3D, presented at the TMS/AIME Annual Meeting, San Diego, CA, March 3, 1992

12-91 R. Shivpuri, M. Kuthirakulathu, and M. Mittal, Nonisothermal 3-D Finite Difference Simulation of Cavity Filling during the Die Casting Process, Dept. Industrial and Systems Engineering, Ohio State University, presented at the 1991 Winter Annual ASME Meeting, Atlanta, GA, Dec. 1-6, 1991

3-91 C. W. Hirt, FLOW-3D Study of the Importance of Fluid Momentum in Mold Filling, presented at the 18th Annual Automotive Materials Symposium, Michigan State University, Lansing, MI, May 1-2, 1991 (FSI-91-00-2)

11-90 N. Saluja, O.J. Ilegbusi, and J. Szekely, On the Calculation of the Electromagnetic Force Field in the Circular Stirring of Metallic Melts, accepted in J. Appl. Physics, 1990

10-90 N. Saluja, O. J. Ilegbusi, and J. Szekely, On the Calculation of the Electromagnetic Force Field in the Circular Stirring of Metallic Molds in Continuous Castings, presented at the 6th Iron and Steel Congress of the Iron and Steel Institute of Japan, Nagoya, Japan, October 1990

9-90 N. Saluja, O. J. Ilegbusi, and J. Szekely, Fluid Flow in Phenomena in the Electromagnetic Stirring of Continuous Casting Systems, Part I. The Behavior of a Cylindrically Shaped, Laboratory Scale Installation, accepted for publication in Steel Research, 1990

8-89 C. W. Hirt, Gravity-Fed Casting, Flow Science Technical Note #20, July 1989 (FSI-89-TN20)

6-89 E. W. M. Hansen and F. Syvertsen, Numerical Simulation of Flow Behaviour in Moldfilling for Casting Analysis, SINTEF-Foundation for Scientific and Industrial Research at the Norwegian Institute of Technology, Trondheim, Norway, Report No. STS20 A89001, June 1989

1-88 C. W. Hirt and R. P. Harper, Modeling Tests for Casting Processes, Flow Science report, Jan. 1988 (FSI-88-38-01)

2-87 C. W. Hirt, Addition of a Solidification/Melting Model to FLOW-3D, Flow Science report, April 1987 (FSI-87-33-1)

Water & Environmental Bibliography

다음은 수자원 및 환경 분야에 대한 참고 문 기술 문서 모음입니다.
이 모든 논문은 FLOW-3D  해석 결과를 사용하였습니다. FLOW-3D  를 사용하여 수처리 및 환경 산업을 위한 응용 프로그램을 성공적으로 시뮬레이션하는 방법에 대해 자세히 알아보십시오.

Water and Environmental Bibliography

2024년 11월 20일 Update

118-24 Lei Liao, Jia Li, Min Chen, Ruidong An, Effects of hydraulic cues in barrier environments on fish navigation downstream of dams, Journal of Environmental Management, 365; 121495, 2024. doi.org/10.1016/j.jenvman.2024.121495

115-24 H. Liu, Y.G. Cheng, Z.Y. Yang, J. Zhang, J.Y. Fan, W.X. Li, Effect of uneven inflow on hydrodynamic performance of bulb turbine, Journal of Physics: Conference Series, 2752; 012032, 2024. doi.org/10.1088/1742-6596/2752/1/012032

112-24 Jian Guo, Bowen Weng, Jiyi Wu, Investigation of the energy loss in cylindrical bridge piers scour depth prediction on sand-bed, Ocean Engineering, 309.1; 118513, 2024. doi.org/10.1016/j.oceaneng.2024.118513

110-24 Siyu Chen, Xiyen Liu, Junyao Tang, Ying Gao, Tianyou Zhang, Linhao Gu, Tao Ma, Can Chen, Study on the influence of design parameters of porous asphalt pavement on drainage performance, Journal of Hydrology, 638; 131514, 2024. doi.org/10.1016/j.jhydrol.2024.131514

108-24 Abubaker Sami Dheyab, Mustafa Günal, Experimental and numerical study for local scour around cylindrical bridge pier in non-cohesive sediment bed, 4th International Congress of Engineering and Natural Sciences (ICENSS), 2024.

106-24 P. Asabian, C.D. Rennie, N. Egsgard, Experimental and numerical investigation of the flow-structure of river surf waves, River Flow 2022, eds. Ana Maria Ferreira da Silva, Colin Rennie, Susan Gaskin, Jay Lacey, Bruce MacVicar, 2024.

105-24 M. Cihan Aydin, Ali Emre Ulu, Ercan Işık, Nizamettin Hamidi, An experimental and numerical investigation of hydraulic performance of in-channel triangular labyrinth weir for free overflow, ISH Journal of Hydraulic Engineering, pp. 1-10, 2024. doi.org/10.1080/09715010.2024.2363224

103-24 Yazhou Wang, Jinrong Da, Yuchen Luo, Sirui He, Zuocong Tian, Ziyi Xue, Zehao Li, Xianyu Zhao, Desheng Yin, Hui Peng, Xiang Liu, Xiaoning Liu , Minimization of heavy metal adsorption in struvite through effective separation and manipulation of flow field, Journal of Hazardous Materials, 474; 134820, 2024. doi.org/10.1016/j.jhazmat.2024.134820

101-24 Davut Yilmaz, Tugce Basar, Arzu Ozkaya, Assessing the pressure variation in the plunge pool of Yusufeli dam, Dams and Reservoirs, 2024. doi.org/10.1680/jdare.2024.1

99-24 Azim Turan, High resolution flash flood forecasting by combining a hydrometeorological modeling system with a computational fluid dynamics model, Thesis, Middle East Technical University, 2024.

97-24 Umut Aykan, Numerical investigation of vortex formation at single and multiple symmetric horizontal intakes, Thesis, Middle East Technical University, 2024.

91-24 Di Wang, Xiaoyong Cheng, Zhixuan Cao, Jinyun Deng, Three-dimensional flow structure in a confluence-bifurcation unit, Engineering Applications of Computational Fluid Mechanics, 18.1; 2024. doi.org/10.1080/19942060.2024.2349076

86-24 M.Z. Qamar, M.K. Verma, A.P. Meshram, Physical and numerical modelling for settling efficiency of desilting chamber, ISH Journal of Hydraulic Engineering, 30.3; 2024. doi.org/10.1080/09715010.2024.2345338

85-24 Ruichen Xu, Duane C. Chapman, Caroline M. Elliott, Bruce C. Call, Robert B. Jacobson, Binbin Wang, Ecological inferences on invasive carp survival using hydrodynamics and egg drift models, Scientific Reports, 14; 9556, 2024. doi.org/10.1038/s41598-024-60189-1

84-24 M. Cihan Aydin, Ali Emre Ulu, Ercan Işik, Experimental and numerical investigation of rectangular labyrinth weirs in an open channel, Water Management , 2024. doi.org/10.1680/jwama.22.00112

76-24 Chyan-Deng Jan, Litan Dey, Slump-flow channel test for evaluating the relations between spreading and rheological parameters of sediment mixtures, European Journal of Mechanics – B/Fluids, 106; pp. 137-147, 2024. doi.org/10.1016/j.euromechflu.2024.04.005

74-24 Abhishek K. Pandey, Pranab K. Mohapatra, 3D numerical simulations of the bed evolution at an open-channel junction in flood conditions, Journal of Irrigation and Drainage Engineering, 150.3; 2024. doi.org/10.1061/JIDEDH.IRENG-10321

70-24 Jianing Rao, Qi Wei, Lian Tang, Yuanming Wang, Ruifeng Liang, Kefeng Li, A design of a nature-like fishway to solve the fractured river connectivity caused by small hydropower based on hydrodynamics and fish behaviors, Environmental Science and Pollution Research, 31; pp. 27883-27896, 2024. doi.org/10.1007/s11356-024-33034-1

69-24 M. Cihan Aydin, Ali Emre Ulu, Ercan Işık, Determination of effective flow behaviors on discharge performance of trapezoidal labyrinth weirs using numerical and physical models, Modeling Earth Systems and Environment, 10; pp. 3763-3776, 2024. doi.org/10.1007/s40808-024-01996-3

62-24 Ramtin Sabeti, Mohammad Heidarzadeh, Estimating maximum initial wave amplitude of subaerial landslide tsunamis: A three-dimensional modelling approach, Ocean Modelling, 189; 102360, 2024. doi.org/10.1016/j.ocemod.2024.102360

60-24 Mahdi Ebrahimi, Mirali Mohammadi, Sayed Mohammad Hadi Meshkati, Farhad Imanshoar, Embankment dams overtopping breach: A numerical investigation of hydraulic results, Iranian Journal of Science and Technology: Transactions of Civil Engineering, 2024. doi.org/10.1007/s40996-024-01387-9

59-24 Behshad Mardasi, Rasoul Ilkhanipour Zeynali, Majid Heydari, Conducting experimental and numerical studies to analyze the impact of the base nose shape on flow hydraulics in PKW weir using FLOW-3D, Journal of Hydraulic Structures, 9.4; pp. 88-113, 2024. doi.org/10.22055/JHS.2024.45888.1284

58-24 Ramtin Sabeti, Mohammad Heidarzadeh, Alessandro Romano, Gabriel Barajas Ojeda, Javier L. Lara, Three-dimensional simulations of subaerial landslide-generated waves: Comparing OpenFOAM and FLOW-3D HYDRO models, Pure and Applied Geophysics, 181; pp. 1075-1093, 2024. doi.org/10.1007/s00024-024-03443-x

56-24 Ali Poorkarimi, Khaled Mafakheri, Shahrzad Maleki, Effect of inlet and baffle position on the removal efficiency of sedimentation tank using FLOW-3D software, Journal of Hydraulic Structures, 9.4; pp. 76-87, 2024. doi.org/10.22055/jhs.2024.44817.1265

55-24 P Sujith Nair, Aniruddha D. Ghare, Ankur Kapoor, An approach to hydraulic design of conical central baffle flumes, Flow Measurement and Instrumentation, 97; 102573, 2024. doi.org/10.1016/j.flowmeasinst.2024.102573

54-24 Isabelle Cheff, Julie Taylor, Andrew Mitchell, Kathleen Horita, Darren Shepherd, Steven Rintoul, Rob Millar, Evaluating uncertainty in debris flood modelling for the design of a steep built channel, EGU General Assembly, EGU24-20781, 2024. doi.org/10.5194/egusphere-egu24-20781

53-24 Antonija Harasti, Gordon Gilja, Josip Vuco, Jelena Boban, Manousos Valyrakis, Temporal development of the scour hole next to the riprap sloping structure, EGU General Assembly, EGU24-10349, 2024. doi.org/10.5194/egusphere-egu24-10349

52-24 Gordon Gilja, Antonija Harasti, Dea Delija, Iva Mejašić, Manousos Valyrakis, Change in flow field next to riprap sloping structure caused by variability of scoured bathymetry, EGU General Assembly, EGU24-10417, 2024. doi.org/10.5194/egusphere-egu24-10417

49-24 Mehdi Hamidi, Mehran Sadeqlu, Ali Mahdian Khalili, Investigating the design and arrangement of dual submerged vanes as mitigation countermeasure of bridge pier scour depth using a numerical approach, Ocean Engineering, 299; 117270, 2024. doi.org/10.1016/j.oceaneng.2024.117270

48-24 Yingying Wang, Mouchao Lv, Wen’e Wang, Ming Meng, Discharge formula and hydraulics of rectangular side weirs in the small channel and field inlet, Water, 16.5; 713, 2024. doi.org/10.3390/w16050713

45-24 José Saldanha Matos, Filipa Ferreira, Lisbon Master Plans and nature-based solutions, Urban Green Spaces – New Perspectives for Urban Resilience, Eds. Cristina M. Monteiro, Cristina Santos, Cristina Matos, Ana Briga Sá. doi.org/10.5772/intechopen.113870

44-24 Muhanad Al-Jubouri, Richard P. Ray, Enhancing pier local scour prediction in the presence of floating debris, Pollack Periodica, 2024. doi.org/10.1556/606.2023.00952

42-24 Huanquan Yang, Jiabao Ma, Xueying Liu, Numerical simulation research on energy dissipation characteristics of fish scale weir, ES3 Web of Conferences, 490; 03005, 2024. doi.org/10.1051/e3sconf/202449003005

39-24 Henry-John Wright, Investigation of novel deflector shapes for uncontrolled spillways, Thesis, Stellenbosch University, 2024.

37-24 Filipe Romão, Ana L. Quaresma, Joana Simão, Francisco J. Bravo-Córdoba, Teresa Viseu, José M. Santos, Francisco J. Sanz-Ronda, António N. Pi, Debating the rules: an experimental approach to assess cyprinid passage performance thresholds in vertical slot fishways, Water, 16.3; 439, 2024. doi.org/10.3390/w16030439

36-24 Berkay Erat, Efe Barbaros, Kerem Taştan, Experimental and numerical investigation on flow and scour upstream of pipe intake structures, Arabian Journal for Science and Engineering, 49; pp. 5973-5987, 2024. doi.org/10.1007/s13369-023-08539-5

31-24 Mahmoud T. Ghonim, Ashraf Jatwary, Magdy H. Mowafy, Martina Zelenakova, Hany F. Abd-Elhamid, H. Omara, Hazem M. Eldeeb, Estimating the peak outflow and maximum erosion rate during the breach of embankment dam, Water, 16.3; 399, 2024. doi.org/10.3390/w16030399

30-24 Deli Qiu, Jiangdong Xu, Hai Lin, Numerical analysis of the overtopping failure of the tailings dam model based on inception similarity optimization, Applied Sciences, 14.3; 990, 2024. doi.org/10.3390/app14030990

29-24 Tino Kostić, Yuanjie Ren, Stephan Theobald, 3D-CFD analysis of bedload transport in channel bifurcations, Journal of Hydroinformatics, 26.2; 480, 2024. doi.org/10.2166/hydro.2024.175

28-24 Chenhao Zhang, Xin Li, Renyu Zhou, Bernard A. Engel, Yubao Wang, Hydraulic characteristics and flow measurement performance of portable primary and subsidiary fish-shaped flumes in U-shaped channels, Flow Measurement and Instrumentation, 96; 102539, 2024. doi.org/10.1016/j.flowmeasinst.2024.102539

23-24   Arash Ahmadi, Amir H. Azimi, Effects of ramp slope and discharge on hydraulic performance of submerged hump weirs, Flow Measurement and Instrumentation, 96; 102520, 2024. doi.org/10.1016/j.flowmeasinst.2023.102520

20-24   Parisa Mirkhorli, Amir Ghaderi, Forough Alizadeh Sanami, Mirali Mohammadi, Alban Kuriqi, An investigation on hydraulic aspects of rectangular labyrinth pool and weir fishway using FLOW-3D, Arabian Journal for Science and Engineering, 2024. doi.org/10.1007/s13369-023-08537-7

17-24   Veysi Kartal, M. Emin Emiroglu, Numerical simulation of the flow passing through the side weir-gate, Flow Measurement and Instrumentation, 95; 102519, 2024. doi.org/10.1016/j.flowmeasinst.2023.102519

16-24   Junqi Chen, Wen Zhang, Chen Cao, Han Yin, Jia Wang, Wankun Li, Yanhao Zheng, The effect of the check dam on the sediment transport and control in debris flow events, Engineering Geology, 329; 107397, 2024. doi.org/10.1016/j.enggeo.2023.107397

15-24   Jingxin Mao, Yijun Wang, Hao Zhang, Xiaofei Jing, Study on the influence of urban water supply pipeline leakage on the scouring failure law of cohesive soil subgrade, Water, 16.1; 93, 2024. doi.org/10.3390/w16010093

13-24   Ramtin Sabeti, Mohammad Heidarzadeh, Alessandro Romano, Gabriel Barajas Ojeda, Javier L. Lara, Three-dimensional simulations of subaerial landslide-generated wave: comparing OpenFOAM and FLOW-3D HYDRO models, Pure and Applied Geophysics, 2024. doi.org/10.1007/s00024-024-03443-x

12-24   Damoon Mohammad Ali Nezhadian, Hossein Hamidifar, Effects of floating debris on flow characteristics around slotted bridge piers: a numerical simulation, Water, 16.1; 90, 2024. doi.org/10.3390/w16010090

10-24   Zhong Gao, Jinpeng Liu, Wen He, Bokai Lu, Manman Wang, Zikai Tang, Study of a tailings dam failure pattern and post-failure effects under flooding conditions, Water, 16.1; 68, 2024. doi.org/10.3390/w16010068

9-24   Yilin Yang, Jinzhao Li, Waner Zou, Benshuang Chen, Numerical investigation of flow and scour around complex bridge piers in wind-wave-current conditions, Journal of Marine Science and Engineering, 12.1; 23, 2024. doi.org/10.3390/jmse12010023

7-24   Penfeng Li, Haixiao Jing, Guodong Li, Generation and prediction of water waves induced by rigid piston-like landslide, Natural Hazards, 120; pp. 2683-2704, 2024. doi.org/10.1007/s11069-023-06300-7

6-24   Jie-yuan Zhang, Xing-Guo Yang, Gang Fan, Hai-bo Li, Jia-wen Zhou, Physical and numerical modeling of a landslide dam breach and flood routing process, Journal of Hydrology, 628; 130552, 2024. doi.org/10.1016/j.jhydrol.2023.130552

241-23 Kamyab Habibi, Farinaz Erfani Fard, Seyed Amin Asghari Pari, Investigation of the flow field around bridge piers on a non-eroding bed using FLOW-3D, 22nd Iranian Conference on Hydraulics, 2023.

240-23 Dong Hyun Kim, Su-Hyun Yang, Sung Sik Joo, Seung Oh Lee, Analysis of flow velocity in the channel according to the type of revetments blocks using 3D numerical model, Journal of Korean Society of Disaster and Security, 16.4; pp. 9-18, 2023.

238-23 Mohamed Elberry, Abdelazim Ali, Fahmy Abdelhaleem, Amir Ibrahim, Numerical investigations of stilling basin efficiency downstream radial gates – A case study of New Assuit Barrage, Egypt, Journal of Water and Land Development, 59 (X-XII); pp. 126-134, 2023. doi.org/10.24425/jwld.2023.147237

237-23 Oğuzhan Uluyurt, Numerical investigation of energy dissipation using macro roughness elements in a stilling basin, Thesis, Middle East Technical University, 2023.

236-23   Mohamed Galal Eltarabily, Mohamed Kamel Elshaarawy, Mohamed Elkiki, Tarek Selim, Computational fluid dynamics and artificial neural networks for modelling lined irrigation canals with low-density polyethylene and cement concrete liners, Irrigation and Drainage, 2023. doi.org/10.1002/ird.2911

234-23   Saman Baharvand, Babak Lashkar-Ara, Hydrodynamic and biological assessment of modified meander C-type fishway to pass rainbow trout (Oncorhynchus mykiss) fish species, Scientia Iranica, 2023.

232-23   Chung R. Song, Richard L. Wood, Basil Abualshar, Bashar Al-Nimri, Mark O’Brien, Mitra Nasimi, Erosion resistant rock shoulder, Nebraska Department of Transportation, Final Report SPR-P1(20), 2023.

230-23   Rongzhao Zhang, Wen Xiong, Xiaolong Ma, C.S. Cai, A forensic investigation of progressive bridge collapse under floods and asymmetric scour validated by incident video footages, Structure and Infrastructure Engineering, 2023. doi.org/10.1080/15732479.2023.2290701

229-23   Vivek Sharma Jai, Hydraulic simulation and numerical investigation of the flow in the stepped spillway with the help of FLOW-3D software, International Journal of Innovative Science and Research Technology, 8; 2023. doi.org/10.5281/zenodo.8076943

228-23   Hao Chen, Yang Tang, Jinyuan Li, Faxin Zhu, Xianbin Teng, The influence of impinging distance variable on the effect of submerged jet scour, Journal of Physics: Conference Series, 2660; 012004, 2023. doi.org/10.1088/1742-6596/2660/1/012004

225-23   Kyle Thomson, Towards safer bridges: Overcoming 2D model limitations and reducing flood risks through computational fluid dynamics, IPWEA Annual Conference Gold Coast, 2023.

223-23   Chong-xun Wang, Jia-wen Zhou, Chang-bing Zhang, Yu-xiang Hu, Hao Chen, Hai-bo Li, Failure mechanism analysis and mass movement assessment of a post‑earthquake high slope, Arabian Journal of Geosciences, 16; 683, 2023. doi.org/10.1007/s12517-023-11737-y

222-23   Alaa Ghzayel, Anthony Beaudoin, Sébastien Jarny, Three-dimensional numerical study of a local scour downstream of a submerged sluice gate using two hydro-morphodynamic models, SedFoam and FLOW-3D, Comptes Rendus. Mécanique, 351.G2; pp. 525-550, 2023. doi.org/10.5802/crmeca.223

221-23   Othon José Rocha, Luiz Renato Martini Filho, Caio Gripp Benevente, Letícia Imbuzeiro, Modelagem CFD-3D aplicada ao setor de mineração (3D CFD modeling applied to the mining sector), 34th Seminario Nacional de Grandes Barragens, 2023.

220-23   Gaetano Crispino, David Dorthe, Corrado Gisonni, Michael Pfister, Optimal hydraulic design of supercritical bend manholes, Proceedings of the 40th IAHR World Congress, Eds. Helmut Habersack, Michael Tritthart, Lisa Waldenberger, 2023. doi.org/10.3850/978-90-833476-1-5_iahr40wc-p0090-cd

218-23   Arun Goel, Aditya Thakare, M.K. Verma, M.Z. Qamar, Evaluation of design approaches of desilting basins for hydroelectric projects in Himalayan region, ISH Journal of Hydraulic Engineering, 30.1; pp. 122-131, 2023. doi.org/10.1080/09715010.2023.2283593

215-23   Ahmed Ashour, Emam Salah, Numerical study of energy dissipation in baffled stepped spillway using FLOW-3D, International Journal of Research in Engineering, Science and Management, 6.11; 2023.

214-23   Farshid Mosaddeghi, Mete Koken, Ismail Aydin, Finite volume analysis of dam breaking subjected to earthquake accelerations, Journal of Hydraulic Research, 61.6; pp. 845-865, 2023. doi.org/10.1080/00221686.2023.2259858

213-23   Habib Ahmari, Ashish Bhurtyal, Srinivas Prabakar, Qazi Ashique Mowla, Saman Baharvand, Hassan Alsaud, Laboratory testing of engineered media for biofiltration swales, University of Texas Arlington, Project No. TRN6835 Final Report, 2023.

209-23   Cong Trieu Tran, Cong Ty Trinh, Prediction of the vortex evolution and influence analysis of rough bed in a hydraulic jump with the Omega-Liutex method, Tehnički Vjesnik, 30.6; 2023. doi.org/10.17559/TV-20230206000327

203-23   Muhammad Waqas Zaffar, Ishtiaq Hassan, Zulfiqar Ali, Kaleem Sarwar, Muhammad Hassan, Muhammad Taimoor Mustafa, Faizan Ahmed Waris, Numerical investigation of hydraulic jumps with USBR and wedge-shaped baffle block basins for lower tailwater, AQUA – Water Infrastructure, Ecosystems and Society, 72.11; 2081, 2023. doi.org/10.2166/aqua.2023.261

201-23   E.F.R. Bollaert, Digital cloud-based platform to predict rock scour at high-head dams, Role of Dams and Reservoirs in a Successful Energy Transition, Eds. Robert Boes, Patrice Droz, Raphael Leroy, 2023. doi.org/10.1201/9781003440420

200-23   Iacopo Vona, Oysters’ integration on submerged breakwaters as nature-based solution for coastal protection within estuarine environments, Thesis, University of Maryland, 2023.

198-23   Hao Chen, Xianbin Teng, Zhibin Zhang, Faxin Zhu, Jie Wang, Zhaohao Zhang, Numerical analysis of the influence of the impinging distance on the scouring efficiency of submerged jets, Fluid Dynamics & Materials Processing, 20.2; pp. 429-445, 2023. doi.org/10.32604/fdmp.2023.030585

193-23   Chen Peng, Liuweikai Gu, Qiming Zhong, Numerical simulation of dam failure process based on FLOW-3D, Advances in Frontier Research on Engineering Structures, pp. 545-550, 2023. doi.org/10.3233/ATDE230245

189-23   Rebecca G. Englert, Age J. Vellinga, Matthieu J.B. Cartigny, Michael A. Clare, Joris T. Eggenhuisen, Stephen M. Hubbard, Controls on upstream-migrating bed forms in sandy submarine channels, Geology, 51.12; PP. 1137-1142, 2023. doi.org/10.1130/G51385.1

187-23   J.W. Kim, S.B. Woo, A numerical approach to the treatment of submerged water exchange processes through the sluice gates of a tidal power plant, Renewable Energy, 219.1; 119408, 2023. doi.org/10.1016/j.renene.2023.119408

186-23   Chan Jin Jeong, Hyung Jun Park, Hyung Suk Kim, Seung Oh Lee, Study on fish-friendly flow characteristic in stepped fishway, Proceedings of the Korean Water Resources Association Conference, 2023. (In Korean)

185-23   Jaehwan Yoo, Sedong Jang, Byunghyun Kim, Analysis of coastal city flooding in 2D and 3D considering extreme conditions and climate change, Proceedings of the Korean Water Resources Association Conference, 2023. (In Korean)

180-23   Prathyush Nallamothu, Jonathan Gregory, Jordan Leh, Daniel P. Zielinski, Jesse L. Eickholt, Semi-automated inquiry of fish launch angle and speed for hazard analysis, Fishes, 8.10; 476, 2023. doi.org/10.3390/fishes8100476

179-23   Reza Norouzi, Parisa Ebadzadeh, Veli Sume, Rasoul Daneshfaraz, Upstream vortices of a sluice gate: an experimental and numerical study, AQUA – Water Infrastructure, Ecosystems and Society, 72.10; 1906, 2023. doi.org/10.2166/aqua.2023.269

178-23   Bai Hao Li, How Tion Puay, Muhammad Azfar Bin Hamidi, Influence of spur dike’s angle on sand bar formation in a rectangular channel, IOP Conference Series: Earth and Environmental Science, 1238; 012027, 2023. doi.org/10.1088/1755-1315/1238/1/012027

177-23   Hao Zhe Khor, How Tion Puay, Influence of gate lip angle on downpull forces for vertical lift gates, IOP Conference Series: Earth and Environmental Science, 1238; 012019, 2023. doi.org/10.1088/1755-1315/1238/1/012019

175-23   Juan Francisco Macián-Pérez, Rafael García-Bartual, P. Amparo López-Jiménez, Francisco José Vallés-Morán, Numerical modeling of hydraulic jumps at negative steps to improve energy dissipation in stilling basins, Applied Water Science, 13.203; 2023. doi.org/10.1007/s13201-023-01985-4

174-23   Ahintha Kandamby, Dusty Myers, Narrows bypass chute CFD analysis, Dam Safety, 2023.

173-23   H. Jalili, R.C. Mahon, M.F. Martinez, J.W. Nicklow, Sediment sluicing from the reservoirs with high efficiency, SEDHYD, 2023.

170-23   Ramith Fernando, Gangfu Zhang, Beyond 2D: Unravelling bridge hydraulics with CFD modelling, 24th Queensland Water Symposium, 2023.

169-23   K. Licht, G. Lončar, H. Posavčić, I. Halkijević, Short-time numerical simulation of ultrasonically assisted electrochemical removal of strontium from water, 18th International Conference on Environmental Science and Technology (CEST), 2023.

166-23   Ebrahim Hamid Hussein Al-Qadami, Mohd Adib Mohammad Razi, Wawan Septiawan Damanik, Zahiraniza Mustaffa, Eduardo Martinez-Gomariz, Fang Yenn Teo, Anwar Ameen Hezam Saeed, Understanding the stability of passenger vehicles exposed to water flows through 3D CFD modelling, Sustainability, 15.17; 13262, 2023. doi.org/10.3390/su151713262

165-23   Ebrahim Hamid Hussein Al-Qadami, Mohd Adib Mohammad Razi, Wawan Septiawan Damanik, Zahiraniza Mustaffa, Eduardo Martinez-Gomariz, Fang Yenn Teo, Anwar Ameen Hezam Saeed, 3-dimensional numerical study on the critical orientation of the flooded passenger vehicles, Engineering Letters, 31.3; 2023.

159-23 Ruosi Zha, Weiwen Zhao, Decheng Wan, Numerical study of wave-ice floe interactions and overwash by a meshfree particle method, Ocean Engineering, 286.2; 115681, 2023. doi.org/10.1016/j.oceaneng.2023.115681

157-23 Hamidreza Abbaszadeh, Kiyoumars Roushangar, Zahra Salahpour, Theoretical and numerical investigation of the sluice and radial gates discharge coefficient in the conditions of sill application, Iranian Journal of Irrigation and Drainage, 2023.

155-23 Ting Zhang, Qunwei Dai, Dejun An, R. Agustin Mors, Qiongfang Li, Ricardo A. Astini, Jingwen He, Jie Cui, Ruiyang Jiang, Faqin Dong, Zheng Dang, Effective mechanisms in the formation of pool-rimstone dams in continental carbonate systems: The case study of Huanglong, China, Sedimentary Geology, 455; 106486, 2023. doi.org/10.1016/j.sedgeo.2023.106486

153-23 Jyh-Haw Tang, Aisyah Puspasari, Numerical simulation of scouring around four cylindrical piles with different inclination angles arrangements, Proceedings of the 4th International Conference on Advanced Engineering and Technology (ICATECH), 1; pp. 139-145, 2023. doi.org/10.5220/0012115500003680

152-23 Yasser El-Saie, Osama Saleh, Marihan El-Sayed, Abdelazim Ali, Eslam El-Tohamy, Yasser Mohamed Sadek, Dissipation of water energy by using a special stilling basin via three-dimensional numerical model, The Open Civil Engineering Journal, 17; 2023.

150-23 Shelby J. Koldewyn, Using computational fluid dynamics for predicting hydraulic performance of arced labyrinth weirs, Thesis, Utah State University, 2023.

146-23 Lav Kumar Gupta, Manish Pandey, P. Anand Raj, Numerical modeling of scour and erosion processes around spur dike, CLEAN Soil Air Water, 2023. doi.org/10.1002/clen.202300135

145-23 Nariman Mehranfar, Morteza Kolahdoozan, Shervin Faghihirad, Development of multiphase solver for the modeling of turbidity currents (the case study of Dez Dam), International Journal of Multiphase Flow, 168; 104586, 2023. doi.org/10.1016/j.ijmultiphaseflow.2023.104586

143-23 Fei Ma, Lei You, Jin Liu, Estimation in jet deflection angle of deflector on the chutes, ISH Journal of Hydraulic Engineering, 2023. doi.org/10.1080/09715010.2023.2241416

142-23 Ali Emre Ulu, M. Cihan Aydin, Fevzi Önen, Energy dissipation potentials of grouped spur dikes in an open channel, Water Resources Management, 37; pp. 4491-4506, 2023. doi.org/10.1007/s11269-023-03571-4

141-23 Haofei Feng, Shengtao Du, David Z. Zhu, Numerical study of effects of flushing gate height and sediment bed properties on cleaning efficiency in a simplified self-cleaning device, Water Science & Technology, 88.3; pp. 542-555, 2023. doi.org/10.2166/wst.2023.245

140-23 Brian Fox, 3D CFD modeling with FLOW-3D HYDRO, Proceedings, SEDHYD, 2023.

139-23 Masoumeh (Negar) Ghahramani, Improved empirical and numerical predictive modelling of potential tailings dam breaches and their downstream impacts, Thesis, The University of British Columbia, 2023.

138-23 Rui-Tao Yin, Bing Zhu, Shuai-Wei Yuan, Jun-Nan Li, Zhen-Yu Yang, Zhi-Ying Yang, Dynamic analyses of long-span cable-stayed and suspension cooperative system bridge under combined actions of wind and regular wave loads, Applied Ocean Research, 138; 103683, 2023. doi.org/10.1016/j.apor.2023.103683

137-23 Xuefeng Chen, Shikang Liu, Yuanming Wang, Yuetong Hao, Kefeng Li, Hongtao Wang, Ruifeng Liang, Restoration of a fish-attracting flow field downstream of a dam based on the swimming ability of endemic fishes: A case study in the upper Yangtze River basin, Journal of Environmental Management, 345; 118694, 2023. doi.org/10.1016/j.jenvman.2023.118694

135-23 Nelson Cely Calixto, Melquisedec Cortés Zambrano, Alberto Galvis Castaño, Gustavo Carrillo Soto, Analysis of a three-dimensional numerical modeling approach for predicting scour processes in longitudinal walls of granular bedding rivers, EUREKA: Physics and Engineering, 4; 2023. doi.org/10.21303/2461-4262.2023.002682

134-23 Tarek Selim, Abdelrahman Kamal Hamed, Mohamed Elkiki, Mohamed Galal Eltarabily, Numerical investigation of flow characteristics and energy dissipation over piano key and trapezoidal labyrinth weirs under free-flow conditions, Modeling Earth Systems and Environment, 2023. doi.org/10.1007/s40808-023-01844-w

132-23 Gang Lei, Hongbao Huang, Xiongan Fan, Junan Su, Qingxiang Wang, Xiaoliang Wang, Kai Peng, Jianmin Zhang, Influence of the transition section shape on the cavitation characteristics of the bottom outlet, Water Supply, 23.8; pp. 3061-3077, 2023. doi.org/10.2166/ws.2023.181

129-23 Rasoul Daneshfaraz, Reza Norouzi, John Patrick Abraham, Parisa Ebadzadeh, Behnaz Akhondi, Maryam Abar, Determination of flow characteristics over sharp-crested triangular plan form weirs using numerical simulation, Water Science, 37.1; 2023. doi.org/10.1080/23570008.2023.2236384

124-23 Imad Habeeb Obead, Ahmed Rahim Sahib, Mathematical models for simulating the hydraulic behavior of flow deflectors: laboratory and CFD-based study, Innovative Infrastructure Solutions, 8; 213, 2023. doi.org/10.1007/s41062-023-01170-1

120-23 Kwang-Su Kim, Jong-Song Jo, Improving the power output estimation for a tidal power plant: a case study, Energy, 2023. doi.org/10.1680/jener.23.00007

119-23 Hanif Pourshahbaz, Tadros Ghobrial, Ahmad Shakibaeinia, Evaluating a CFD model for three-dimensional simulation of ice structure interaction, CGU HS Committee on River Ice Processes and the Environment (CRIPE), 22nd Workshop on the Hydraulics of Ice-Covered Rivers, 2023.

118-23 Sruthi T. Kalathil, Venu Chandra, Experimental and numerical investigation on the hydraulic design criteria for a step-pool nature-like fishway, Progress in Physical Geography: Earth and Environment, 2023. doi.org/10.1177/03091333231187619

117-23 Lav Kumar Gupta, Manish Pandey, P. Anand Raj, Numerical simulation of local scour around the pier with and without airfoil collar (AFC) using FLOW-3D, Environmental Fluid Mechanics, 2023. doi.org/10.1007/s10652-023-09932-2

116-23 Paolo Peruzzo, Matteo Cappozzo, Nicola Durighetto, Gianluca Botter, Local processes with a global impact: unraveling the dynamics of gas evasion in a step-and-pool configuration, Biogeosciences, 20; pp. 3261-3271, 2023. doi.org/10.5194/bg-20-3261-2023

114-23 Muhammad Waqas Zaffar, Ishtiaq Hassan, Numerical investigation of hydraulic jump for different stilling basins using FLOW-3D, AQUA – Water Infrastructure, Ecosystems and Society, 72.7; pp. 1320-1343, 2023. doi.org/10.2166/aqua.2023.290

112-23 J. Chandrashekhar Iyer, E.J. James, Indispensability of model studies in the design of settling basins of hydropower projects in river basins with high sediment yield, Fluid Mechanics and Hydraulics, pp. 367-381, 2023. doi.org/10.1007/978-981-19-9151-6_30

110-23 Ehsan Afaridegan, Nosratollah Amanian, Abbas Parsaie, Amin Gharehbaghi, Hydraulic investigation of modified semi-cylindrical weirs, Flow Measurement and Instrumentation, 93; 102405, 2023. doi.org/10.1016/j.flowmeasinst.2023.102405

103-23 Jin Yang, Weqiang Su, Binhua Li, Calculation of natural alluvial separation of sandy tailings slurry based on FLOW-3D, Mechanics in Engineering, 45.3; pp. 559-564, 2023.

101-23 Tutku Ezgi Yönter, Modeling of river flow and flow dynamics near junctions, Thesis, Middle East Technical University, 2023.

99-23 Mohammad Sadeghpour, Mohammad Vaghefi, Seyed Hamed Meraji, Artificial roughness dimensions and their influence on bed topography variations downstream of a culvert: An experimental study, Water Resources Management, 37; pp. 4143-4157, 2023. doi.org/10.1007/s11269-023-03543-8

98-23 M. Aksel, Numerical analysis of the flow structure around inclined solid cylinder and its effect on bed shear stress distribution, Journal of Applied Fluid Mechanics, 16.8; pp. 1627-1639, 2023. doi.org/10.47176/jafm.16.08.1697

96-23 Waqed H. Hassan, Nidaa Ali Shabat, Numerical investigation of the optimum angle for open channel junction, Civil Engineering Journal, 9.5; 2023. doi.org/10.28991/CEJ-2023-09-05-07

94-23 Emad Khanahmadi, Amir Ahmad Dehghani, Seyed Nasrollah Alenabi, Navid Dehghani, Edward Barry, Hydraulic of curved type-B piano key weirs characteristics under free flow conditions, Modeling Earth Systems and Environment, 2023. doi.org/10.1007/s40808-023-01790-7

93-23 Laura-Louise Alicke, Improved priming of a siphon spillway with the use of a flexible membrane researched through numerical modeling, Thesis, Idaho State University, 2023.

91-23 Wahidullah Hakim Safi, Pranab K. Mohapatra, Flow past: An artificial channel confluence with mobile bed, World Environmental and Water Resources Congress, 2023. doi.org/10.1061/9780784484852.023

86-23 Ghasem Aghashirmohammadi, Mohammad Heidarnejad, Mohammad Hossein Purmohammadi, Alireza Masjedi, Experimental and numerical study the effect of flow splitters on trapezoidal and triangular labyrinth weirs, Water Science, 37.1; 2023. doi.org/10.1080/23570008.2023.2210391

84-23 Nikolaos Xafoulis, Evangelia Farsirotou, Spyridon Kotsopoulos, Three-dimensional computational flow dynamics analysis of free-surface flow in a converging channel, Energy Systems, 2023. doi.org/10.1007/s12667-023-00575-2

83-23 Navid Zarrabi, Mohammad Navid Moghim, Mohammad Reza Eftakhar, A semi-analytical study of fiber reinforced concrete abrasion-erosion through water-borne sand-jet flow in hydraulic structures, Tribology International, 185; 108568, 2023. doi.org/10.1016/j.triboint.2023.108568

82-23 Somayyeh Saffar, Abbas Safaei, Farnoush Aghaee Daneshvar, Mohsen Solimani Babarsad, FLOW-3D numerical modeling of converged side weir, Iranian Journal of Science and Technology: Transactions of Civil Engineering, 2023. doi.org/10.1007/s40996-023-01077-y

79-23 Wangshu Wei, Optimization of the mixing in a produced water storage tank using CFD, World Environmental and Water Resources Congress, Eds. Sajjad Ahmad, Regan Murray, 2023. doi.org/10.1061/9780784484852

77-23   Paolo Peruzzo, Matteo Cappozzo, Nicola Durighetto, Gianluca Botter, Local processes with global impact: unraveling the dynamics of gas evasion in a step-and-pool configuration, Biogeosciences, 2023. doi.org/10.5194/bg-2023-68

74-23   Kaywan Othman Ahmed, Nazim Nariman, Dara Muhammad Hawez, Ozgur Kisi, Ata Amini, Predicting and optimizing the influenced parameters for culvert outlet scouring utilizing coupled FLOW 3D-surrogate modeling, Iranian Journal of Science and Technology: Transactions of Civil Engineering, 47; pp. 1763-1776, 2023. doi.org/10.1007/s40996-023-01096-9

73-23   Ashkan Pilbala, Mahmood Shafai Bejestan, Seyed Mohsen Sajjadi, Luigi Fraccarollo, Investigation of the different models of elliptical-Lopac gate performance under submerged flow conditions, Water Resources Management, 2023. doi.org/10.1007/s11269-023-03512-1

69-23   Chonoor Abdi Chooplou, Masoud Ghodsian, Davoud Abediakbar, Aram Ghafouri, An experimental and numerical study on the flow field and scour downstream of rectangular piano key weirs with crest indentations, Innovative Infrastructure Solutions, 8; 140, 2023. doi.org/10.1007/s41062-023-01108-7

68-23   Mahmood Shafai Bajestan, Mostafa Adineh, Hesam Ghodousi, Numerical modeling of sediment washing (flushing) in dams (Case study of Sefidrood dam), Journal of Irrigation Sciences and Engineering, 2023.

65-23   Charles R. Ortloff, CFD investigations of water supply and distribution systems of ancient old and new world archaeological sites to recover ancient water engineering technologies, Water, 15.7; 1363, 2023. doi.org/10.3390/w15071363

63-23   Rasoul Daneshfaraz, Reza Norouzi, Parisa Ebadzadeh, Alban Kuriqi, Effect of geometric shapes of chimney weir on discharge coefficient, Journal of Applied Water Engineering and Research, 2023. doi.org/10.1080/23249676.2023.2192977

59-23   Hongbo Mi, Chuan Wang, Xuanwen Jia, Bo Hu, Hongliang Wang, Hui Wang, Yong Zhu, Hydraulic characteristics of continuous submerged jet impinging on a wall by using numerical simulation and PIV experiment, Sustainability, 15.6; 5159, 2023. doi.org/10.3390/su15065159

58-23   O.P. Maurya, K.K. Nandi, S. Modalavalasa, S. Dutta, Flow hydrodynamics influences due to flood plain sand mining in a meandering channel, Sustainable Environment (NERC 2022), Eds. D. Deka, S.K. Majumder, M.K., Purkait, 2023. doi.org/10.1007/978-981-19-8464-8_16

57-23   Harshvardhan Harshvardhan, Deo Raj Kaushal, CFD modelling of local scour and flow field around isolated and in-line bridge piers using FLOW-3D, EGU General Assembly, EGU23-3820, 2023. doi.org/10.5194/egusphere-egu23-3820

54-23   Reza Nematzadeh, Gholam-Abbas Barani, Ehsan Fadaei-Kermani, Numerical investigation of bed-load changes on sediment flushing cavity, Journal of Hydraulic Structures, 4; 2023. doi.org/10.22055/jhs.2023.42542.1237

53-23   Rasoul Daneshfaraz, Reza Norouzi, Parisa Ebadzadeh, Alban Kuriqi, Influence of sill integration in labyrinth sluice gate hydraulic performance, Innovative Infrastructure Solutions, 8.118; 2023. doi.org/10.1007/s41062-023-01083-z

52-23   Shu Jiang, Yutong Hua, Mengxing He, Ying-Tien Lin, Biyun Sheng, Effect of a circular cylinder on hydrodynamic characteristics over a strongly curved channel, Sustainability, 15.6; 4890, 2023. doi.org/10.3390/su15064890

51-23   Ehsan Aminvash, Kiyoumars Roushangar, Numerical investigation of the effect of the frontal slope of simple and blocky stepped spillway with sem-circular crest on its hydraulic parameters, Iranian Journal of Irrigation and Drainage, 17.1; pp. 102-116, 2023.

50-23   Shizhuang Chen, Anchi Shi, Weiya Xu, Long Yan, Huanling Wang, Lei Tian, Wei-Chau Xie, Numerical investigation of landslide-induced waves: a case study of Wangjiashan landslide in Baihetan Reservoir, China, Bulletin of Engineering Geology and the Environment, 82.110; 2023. doi.org/10.1007/s10064-023-03148-w

49-23   Jiří Procházka, Modelling flow distribution in inlet galleries, VTEI, 1; 2023. doi.org/10.46555/VTEI.2022.11.002

47-23   M. Cihan Aydin, Ali Emre Ulu, Numerical investigation of labyrinth‑shaft spillway, Applied Water Science, 13.89; 2023. doi.org/10.1007/s13201-023-01896-4

46-23   Guangwei Lu, Jinxin Liu, Zhixian Cao, Youwei Li, Xueting Lei, Ying Li, A computational study of 3D flow structure in two consecutive bends subject to the influence of tributary inflow in the middle Yangtze River, Engineering Applications of Computational Fluid Mechanics, 17.1; 2183901, 2023. doi.org/10.1080/19942060.2023.2183901

44-23   Xun Huang, Zhijian Zhang, Guoping Xiang, Sensitivity analysis of a built environment exposed to the synthetic monophasic viscous debris flow impacts with 3-D numerical simulations, Natural Hazards and Earth Systems Sciences, 23; pp. 871-889, 2023. doi.org/10.5194/nhess-23-871-2023

43-23   Yisheng Zhang, Jiangfei Wang, Qi Zhou, Haisong Li, Wei Tang, Investigation of the reduction of sediment deposition and river flow resistance around dimpled surface piers, Environmental Science and Pollution Research, 2023. doi.org/10.1007/s11356-023-26034-0

41-23   Nejib Hassen Abdullahi, Zulfequar Ahmad, Experimental and CFD studies on the flow field and bed morphology in the vicinity of a sediment mining pit, EGU General Assembly, 2023. doi.org/10.5194/egusphere-egu23-446

40-23   Seonghyeon Ju, Jongchan Yi, Junho Lee, Jiyoon Kim, Chaehwi Lim, Jihoon Lee, Kyungtae Kim, Yeojoon Yoon, High-efficiency microplastic sampling device improved using CFD analysis, Sustainability, 15.5; 3907, 2023. doi.org/10.3390/su15053907

37-23   Muhammad Waqas Zaffar, Ishtiaq Hassan, Hydraulic investigation of stilling basins of the barrage before and after remodelling using FLOW-3D, Water Supply, 23.2; pp. 796-820, 2023. doi.org/10.2166/ws.2023.032

35-23   Mehmet Cihan, Ali Emre Ulu, Developing and testing a novel pressure-controlled hydraulic profile for siphon-shaft spillways, Flow Measurement and Instrumentation, 90; 102332, 2023. doi.org/10.1016/j.flowmeasinst.2023.102332

28-23   Yuhan Li, Deshen Chen, Yan Zhang, Hongliang Qian, Jiangyang Pan, Yinghan Huang, Boo Cheong Khoo, Thermal structure and hydrodynamic analysis for a new type of flexible temperature-control curtain, Journal of Hydrology, 618; 129170, 2023. doi.org/10.1016/j.jhydrol.2023.129170

22-23   Rong Lu, Wei Jiang, Jingjing Xiao, Dongdong Yuan, Yupeng Li, Yukai Hou, Congcong Liu, Evaluation of moisture migration characteristics of permeable asphalt pavement: Field research, Journal of Environmental Management, 330; 117176, 2023. doi.org/10.1016/j.jenvman.2022.117176

18-23   Thu Hien-T. Le, Van Chien Nguyen, Cong Phuc Dang, Thanh Thin-T. Nguyen, Bach Quynh-T. Pham, Ngoc Thoa Le, Numerical assessment on hydraulic safety of existing conveyance structures, Modeling Earth Systems and Environment, 2023. doi.org/10.1007/s40808-022-01685-z

17-23   Meysam Nouri, Parveen Sihag, Ozgur Kisi, Mohammad Hemmati, Shamsuddin Shahid, Rana Muhammad Adnan, Prediction of the discharge coefficient in compound broad-crested weir gate by supervised data mining techniques, Sustainability, 15.1; 433, 2023. doi.org/10.3390/su15010433

16-23   Mohammad Bananmah, Mohammad Reza Nikoo, Mehrdad Ghorbani Mooselu, Amir H. Gandomi, Optimum design of the chute-flip bucket system using evolutionary algorithms considering conflicts between decision-makers, Expert Systems with Applications, 216; 119480, 2023. doi.org/10.1016/j.eswa.2022.119480

13-23   Xiaoyu Yi, Wenkai Feng, Botao Li, Baoguo Yin, Xiujun Dong, Chunlei Xin, Mingtang Wu, Deformation characteristics, mechanisms, and potential impulse wave assessment of the Wulipo landslide in the Baihetan reservoir region, China, Landslides, 20; pp. 615-628, 2023. doi.org/10.1007/s10346-022-02010-6

11-23 Şebnem Elçi, Oğuz Hazar, Nisa Bahadıroğlu, Derya Karakaya, Aslı Bor, Destratification of thermally stratified water columns by air diffusers, Journal of Hydro-environment Research, 46; pp. 44-59, 2023. doi.org/10.1016/j.jher.2022.12.001

7-23 Shikang Liu, Yuxiang Jian, Pengcheng Li, Ruifeng Liang, Xuefeng Chen, Yunong Qin, Yuanming Wang, Kefeng Li, Optimization schemes to significantly improve the upstream migration of fish: A case study in the lower Yangtze River basin, Ecological Engineering, 186; 106838, 2023. doi.org/10.1016/j.ecoleng.2022.106838

6-23 Maryam Shahabi, Javad Ahadiyan, Mehdi Ghomeshi, Marjan Narimousa, Christos Katopodis, Numerical study of the effect of a V-shaped weir on turbulence characteristics and velocity in V-weir fishways, River Research and Applications, 2023. doi.org/10.1002/rra.4064

5-23 Muhammad Nur Aiman Bin Roslan, Hee Min Teh, Faris Ali Hamood Al-Towayti, Numerical simulations of wave diffraction around a low-crested semicircular breakwater, Proceedings of the 5th International Conference on Water Resources (ICWR), Lecture Notes in Civil Engineering, 293.1; pp. 421-433, 2023. doi.org/10.1007/978-981-19-5947-9_34

4-23 V.K. Krishnasamy, M.H. Jamal, M.R. Haniffah, Modelling of wave runup and overtopping over Accropode II breakwater, Proceedings of the 5th International Conference on Water Resources (ICWR), Lecture Notes in Civil Engineering, 293.1; pp. 435-444, 2023. doi.org/10.1007/978-981-19-5947-9_35

3-23 Anas S. Ghamam, Mohammed A. Abohatem, Mohd Ridza Bin Mohd Haniffah, Ilya K. Othman, The relationship between flow and pressure head of partially submerged orifice through CFD modelling using Flow-3D, Proceedings of the 5th International Conference on Water Resources (ICWR), Lecture Notes in Civil Engineering, 293.1; pp. 235-250, 2023. doi.org/10.1007/978-981-19-5947-9_20

2-23 M.Y. Zainab, A.L.S. Zebedee, A.W. Ahmad Khairi, I. Zulhilmi, A. Shahabuddin, Modelling of an embankment failure using Flow-3D, Proceedings of the 5th International Conference on Water Resources (ICWR), Lecture Notes in Civil Engineering, 293.1; pp. 273-282, 2023. doi.org/10.1007/978-981-19-5947-9_23

1-23 Gaetano Crispino, David Dorthe, Corrado Gisonni, Michael Pfister, Hydraulic capacity of bend manholes for supercritical flow, Journal of Irrigation and Drainage Engineering, 149.2; 2022. doi.org/10.1061/JIDEDH.IRENG-10014

178-22 Greg Collecutt, Urs Baeumer, Shuang Gao, Bill Syme, Bridge deck afflux modelling — benchmarking of CFD and SWE codes to real-world data, Hydrology & Water Resources Symposium, 2022.

177-22 Kyle Thomson, Mitchell Redenbach, Understanding cone fishway flow regimes with CFD, Hydrology & Water Resources Symposium, 2022.

176-22 Kyle Thomson, Practical application of CFD for fish passage design, Hydrology & Water Resources Symposium, 2022.

173-22 Melquisedec Cortés Zambrano, Helmer Edgardo Monroy González, Wilson Enrique Amaya Tequia, Three-dimensional numerical evaluation of hydraulic efficiency and discharge coefficient in grate inlets, Environmental Research, Engineering and Management, 78.4; 2022. doi.org/10.5755/j01.erem.78.4.31243

168-22 Mohammad Javadi Rad, Pedram Eshaghieh Firoozbadi, Fatemeh Rostami, Numerical investigation of the effect dimensions of rectangular sedimentation tanks on its hydraulic efficiency using Flow-3D Software, Acta Technica Jaurinensis, 15.4; 2022. doi.org/10.14513/actatechjaur.00672

165-22 Saman Mostafazadeh-Fard, Zohrab Samani, Dissipating culvert end design for erosion control using CFD platform FLOW-3D numerical simulation modeling, Journal of Pipeline Systems Engineering and Practice, 14.1; 2022. doi.org/10.1061/JPSEA2.PSENG-1373

164-22 Mohammad Ahmadi, Alban Kuriqi, Hossein Mohammad Nezhad, Amir Ghaderi, Mirali Mohammadi, Innovative configuration of vertical slot fishway to enhance fish swimming conditions, Journal of Hydrodynamics, 34; pp. 917-933, 2022. doi.org/10.1007/s42241-022-0071-y

160-22 Serife Yurdagul Kumcu, Kamil Ispir, Experimental and numerical modeling of various energy dissipator designs in chute channels, Applied Water Science, 12; 266, 2022. doi.org/10.1007/s13201-022-01792-3

154-22 Usama Majeed, Najam us Saqib, Muhammad Akbar, Numerical analysis of energy dissipator options using computational fluid dynamics modeling — a case study of Mirani Dam, Arabian Journal of Geosciences, 15; 1614, 2022. doi.org/10.1007/s12517-022-10888-8

151-22 Meibao Chen, Xiaofei Jing, Xiaohua Liu, Xuewei Huang, Wen Nie, Multiscale investigations of overtopping erosion in reinforced tailings dam induced by mud-water mixture overflow, Geofluids, 7209176, 2022. doi.org/10.1155/2022/7209176

150-22   Daniel Damov, Francis Lepage, Michel Tremblay, Arian Cueto Bergner, Marc Villaneuve, Frank Scarcelli, Gord McPhail, Calabogie GS redevelopment—Capacity upgrade and hydraulic design, CDA Annual Conference, Proceedings, 2022.

147-22   Hien T.T. Le, Chien Van Nguyen, Duc-Hau Le, Numerical study of sediment scour at meander flume outlet of boxed culvert diversion work, PLoS One, 17.9; e0275347, 2022. doi.org/10.1371/journal.pone.0275347

140-22   Jackson Tellez-Alvarez, Manuel Gómez, Beniamino Russo, Numerical simulation of the hydraulic behavior of stepped stairs in a metro station, Advances in Hydroinformatics, Eds. P. Gourbesville, G. Caignaert, pp. 1001-1009, 2022. doi.org/10.1007/978-981-19-1600-7_62

139-22   Juan Yu, Keyao Liu, Anbin Li, Mingfei Yang, Xiaodong Gao, Xining Zhao, Yaohui Cai, The effect of plug height and inflow rate on water flow characteristics in furrow irrigation, Agronomy, 12; 2225, 2022. doi.org/10.3390/agronomy12092225

138-22   Nejib Hassen Abdullahi, Zulfequar Ahmad, Flow and morphological characteristics in mining pits of a river through numerical and experimental modeling, Modeling Earth Systems and Environment, 2022. doi.org/10.1007/s40808-022-01530-3

137-22   Romain N.H.M. Van Mol, Christian Mörtl, Azin Amini, Sofia Siachou, Anton Schleiss, Giovanni De Cesare, Plunge pool scour and bank erosion: assessment of protection measures for Ilarion dam by physical and numerical modelling, HYDRO 2022, Proceedings, 27.02, 2022.

136-22   Yong Cheng, Yude Song, Chunye Liu, Wene Wang, Xiaotao Hu, Numerical simulation research on the diversion characteristics of a trapezoidal channel, Water, 14.17; 2706, 2022. doi.org/10.3390/w14172706

135-22   Zegao Yin, Yao Li, Jiahao Li, Zihan Zheng, Zihan Ni, Fuxiang Zheng, Experimental and numerical study on hydrodynamic characteristics of a breakwater with inclined perforated slots under regular waves, Ocean Engineering, 264; 112190, 2022. doi.org/10.1016/j.oceaneng.2022.112190

133-22   Azin Amini, Martin Wickenhauser, Azad Koliji, Three-dimensional numerical modelling of Al-Salam storm water pumping station in Saudi Arabia, 39th IAHR World Congress, 2022. doi.org/10.3850/IAHR-39WC2521716X20221013

131-22   Alireza Koshkonesh, Mohammad Daliri, Khuram Riaz, Fariba Ahmadi Dehrashid, Farhad Bahmanpouri, Silvia Di Francesco, Dam-break flow dynamics over a stepped channel with vegetation, Journal of Hydrology, 613.A; 128395, 2022. doi.org/10.1016/j.jhydrol.2022.128395

129-22   Leona Repnik, Samuel Vorlet, Mona Seyfeddine, Asin Amini, Romain Dubuis, Giovanni De Cesare, Pierre Bourqui, Pierre-Adil Abdelmoula, Underground flow section modification below the new M3 Flon Metro station in Lausanne, Advances in Hydroinformatics, Eds. P. Gourbesville, G. Caignaert, pp. 979-999, 2022. doi.org/10.1007/978-981-19-1600-7_61

127-22   Qin Panpan, Huang Bolin, Li Bin, Chen Xiaoting, Jiang Xiannian, Hazard analysis of landslide blocking a river in Guang’an Village, Wuxi County, Chongqing, China, Landslides, 2022. doi.org/10.1007/s10346-022-01943-2

124-22   Vaishali P. Gadhe, S.R. Patnaik, M.R. Bhajantri, V.V. Bhosekar, Physical and numerical modeling of flow pattern near upstream guide wall of Jigaon Dam spillway, Maharashtra, River and Coastal Engineering, Water Science and Technology Library 117; pp. 237-247, 2022. doi.org/10.1007/978-3-031-05057-2_21

123-22   M.Z. Qamar, M.K. Verma, A.P. Meshram, Neena Isaac, Numerical simulation of desilting chamber using Flow 3D, River and Coastal Engineering, Water Science and Technology Library 117; pp. 177-186, 2022. doi.org/10.1007/978-3-031-05057-2_16

122-22   Abbas Parsaie, Saleh Jaafer Suleiman Shareef, Amir Hamzeh Haghiabi, Raad Hoobi Irzooki, Rasul M. Khalaf, Numerical simulation of flow on circular crested stepped spillway, Applied Water Science, 12; 215, 2022. doi.org/10.1007/s13201-022-01737-w

121-22   Kazuki Kikuchi, Hajime Naruse, Morphological function of trace fossil Paleodictyon: An approach from fluid simulation, Paleontological Research, 26.4; pp. 378-389, 2022. doi.org/10.2517/PR210001

120-22   Najam us Saqib, Muhammad Akbar, Huali Pan, Guoqiang Ou, Numerical investigation of pressure profiles and energy dissipation across the stepped spillway having curved treads using FLOW 3D, Arabian Journal of Geosciences, 15; 1363, 2022. doi.org/10.1007/s12517-022-10505-8

116-22   Ayşegül Özgenç Aksoy, Mustafa Doğan, Semire Oğuzhan Güven, Görkem Tanır, Mehmet Şükrü Güney, Experimental and numerical investigation of the flood waves due to partial dam break, Iranian Journal of Science and Technology: Transactions of Civil Engineering, 2022. doi.org/10.1007/s40996-022-00919-5

115-22   Abdol Mahdi Behroozi, Mohammad Vaghefi, Experimental and numerical study of the effect of zigzag crests with various geometries on the performance of A-type piano key weirs, Water Resources Management, 2022. doi.org/10.1007/s11269-022-03261-7

114-22   Xun Huang, Zhijian Zhang, Guoping Xiang, Sensitivity analysis of a built environment exposed to debris flow impacts with 3-D numerical simulations, Natural Hazards and Earth Systems Sciences, 2022. doi.org/10.5194/nhess-2022-173

113-22   Ahmad Ferdowsi, Mahdi Valikhan-Anaraki, Saeed Farzin, Sayed-Farhad Mousavi, A new combination approach for optimal design of sedimentation tanks based on hydrodynamic simulation model and machine learning algorithms, Physics and Chemistry of the Earth, 103201, 2022. doi.org/10.1016/j.pce.2022.103201

103-22   Wangshu Wei, Optimization of the mixing in produced water (PW) retention tank with computational fluid dynamics (CFD) modeling, Produced Water Society Permian Basin, 2022.

100-22   Michael Rasmussen, Using computational fluid dynamics to predict flow through the West Crack Breach of the Great Salt Lake railroad causeway, Thesis, Utah State University, 2022.

99-22   Emad Khanahmadi, Amir Ahmad Dehghani, Mehdi Meftah Halaghi, Esmaeil Kordi, Farhad Bahmanpouri, Investigating the characteristic of hydraulic T-jump on rough bed based on experimental and numerical modeling, Modeling Earth Systems and Environment, 2022. doi.org/10.1007/s40808-022-01434-2

97-22   Andrea Franco, A multidisciplinary approach for landslide-generated impulse wave assessment in natural mountain basins from a cascade analysis perspective, Thesis, University of Innsbruck, 2022.

96-22   Geng Li, Binbin Wang, Simulation of the flow field and scour evolution by turbulent wall jets under a sluice gate, Journal of Hydro-environment Research, 43; pp. 22-32, 2022. doi.org/10.1016/j.jher.2022.06.002

95-22   Philippe April LeQuéré, Ioan Nistor, Abdolmajid Mohammadian, Stefan Schimmels, Hydrodynamics and associated scour around a free-standing structure due to turbulent bores, Journal of Waterway, Port, Coastal, and Ocean Engineering, 148.5; 2022.

94-22   Ramtin Sobhkhiz Foumani, Alireza Mardookhpour, Numerical simulation of geotechnical effects on local scour in inclined pier group with Flow-3D software, Water Resources Engineering Journal, 15.52; 2022. doi.org/10.30495/wej.2021.20404.2114

92-22   Geng Li, Binbin Wang, Caroline M. Elliott, Bruce C.Call, Duane C. Chapman, Robert B. Jacobson, A three-dimensional Lagrangian particle tracking model for predicting transport of eggs of rheophilic-spawning carps in turbulent rivers, Ecological Modelling, 470; 110035, 2022. doi.org/10.1016/j.ecolmodel.2022.110035

91-22   Ebrahim Hamid Hussein Al-Qadami, Zahiraniza Mustaffa, Mohamed Ezzat Al-Atroush, Eduardo Martinez-Gomariz, Fang Yenn Teo, Yasser El-Husseini, A numerical approach to understand the responses of passenger vehicles moving through floodwaters, Journal of Flood Risk Management, 2022. doi.org/10.1111/jfr3.12828

90-22   Jafar Chabokpour, Hazi Md Azamathulla, Numerical simulation of pollution transport and hydrodynamic characteristics through the river confluence using FLOW 3D, Water Supply, 2022. doi.org/10.2166/ws.2022.237

88-22   Michael Rasmussen, Som Dutta, Bethany T. Neilson, Brian Mark Crookston, CFD model of the density-driven bidirectional flows through the West Crack Breach in the Great Salt Lake causeway, Water, 13.17; 2423, 2022. doi.org/10.3390/w13172423

84-22   M. Sobhi Alasta, Ahmed Shakir Ali Ali, Saman Ebrahimi, Muhammad Masood Ashiq, Abubaker Sami Dheyab, Adnan AlMasri, Anass Alqatanani, Mahdis Khorram, Modeling of local scour depth around bridge pier using FLOW 3D, CPRASE: Transactions of Civil and Environmental Engineering, 8.2; 2781, 2022.

83-22   Mostafa Taherian, Seyed Ahmad Reza Saeidi Hosseini, Abdolmajid Mohammadian, Overview of outfall discharge modeling with a focus on turbulence modeling approaches, Advances in Fluid Mechanics: Modelling and Simulations, Eds. Dia Zeidan, Eric Goncalves Da Silva, Jochen Merker, Lucy T. Zhang, 2022.

80-22   Soraya Naderi, Mehdi Daryaee, Seyed Mahmood Kashefipour, Mohammadreza Zayeri, Numerical and experimental study of flow pattern due to a plate installed upstream of orifice in pressurized flushing of dam reservoirs, Iranian Journal of Science and Technology: Transactions of Civil Engineering, 2022. doi.org/10.1007/s40996-022-00896-9

79-22   Mahmood Nemati Qalee Maskan, Khosrow Hosseini, Effects of the simultaneous presence of bridge pier and abutment on the change of erodible bed using FLOW-3D, Journal of Iranian Water Engineering Research, 1.1; pp. 57-69, 2022. doi.org/10.22034/IJWER.2022.312074.1012

75-22   Steven Matthew Klawitter, L-shaped spillway crest leg interface geometry impacts, Thesis, University of Colorado at Denver, 2022.

72-22   Md. Mukdiul Islam, Md. Samiun Basir, Badal Mahalder, Local scour analysis around single pier and group of piers in tandem arrangement using FLOW 3D, 6th International Conference on Civil Engineering for Sustainable Development (ICCESD 2022), Khulna, Bangladesh, February 10-12, 2022.

69-22   Kuo-Wei Liao, Zhen-Zhi Wang, Investigation of air-bubble screen on reducing scour in river facility, EGU General Assembly, EGU22-1137, 2022. doi.org/10.5194/egusphere-egu22-1137

68-22   Cüneyt Yavuz, Energy dissipation scale for dam prototypes, ADYU Mühendislik Bilimleri Dergisi (Adıyaman University Journal of Engineering Sciences), 16; pp. 105-116, 2022.

66-22   Ji-jian Lian, Shu-guang Zhang, Jun-ling He, An improved numerical model of ski-jump flood discharge atomization, Journal of Mountain Science, 19; pp. 1263-1273, 2022. doi.org/10.1007/s11629-021-7158-8

62-22   Ali Montazeri, Amirabbas Abedini, Milad Aminzadeh, Numerical investigation of pollution transport around a single non-submerged spur dike, Journal of Contaminant Hydrology, 248; 104018, 2022. doi.org/10.1016/j.jconhyd.2022.104018

61-22   Junhao Zhang, Yining Sun, Zhixian Cao, Ji Li, Flow structure at reservoir-tributary confluence with high sediment load, EGU General Assembly, Vienna, Austria, May 23-27, 2022. doi.org/10.5194/egusphere-egu22-1419

60-22   S. Modalavalasa, V. Chembolu, V. Kulkarni, S. Dutta, Numerical and experimental investigation of effect of green river corridor on main channel hydraulics, Recent Trends in River Corridor Management, Lecture Notes in Civil Engineering 229, pp. 165-176, 2022.

59-22   Philippe April LeQuéré, Scouring around multiple structures in extreme flow conditions, Thesis, University of Ottawa, Ottawa, ON, Canada, 2022.

51-22   Xianzheng Zhang, Chenxiao Tang, Yajie Yu, Chuan Tang, Ning Li, Jiang Xiong, Ming Chen, Some considerations for using numerical methods to simulate possible debris flows: The case of the 2013 and 2020 Wayao debris flows (Sichuan, China), Water, 14.7; 1050, 2022. doi.org/10.3390/w14071050

50-22   Daniel Valero, Daniel B. Bung, Sebastien Erpicum, Yann Peltier, Benjamin Dewals, Unsteady shallow meandering flows in rectangular reservoirs: A modal analysis of URANS modelling, Journal of Hydro-environment Research, 42; pp. 12-20, 2022. doi.org/10.1016/j.jher.2022.03.002

49-22   Behzad Noroozi, Jalal Bazargan, Comparing the behavior of ogee and piano key weirs under unsteady flows, Journal of Irrigation and Water Engineering, 12.3; pp. 97-120. doi.org/10.22125/iwe.2022.146390

47-22   Chen Xiaoting, Huang Bolin, Li Bin, Jiang Xiannian, Risk assessment study on landslide-generated impulse waves: case study from Zhongliang Reservoir in Chongqing, China, Bulletin of Engineering Geology and the Environment, 81; 158, 2022. doi.org/10.1007/s10064-022-02629-8

45-22   Mehmet Cihan Aydin, Havva Seda Aytemur, Ali Emre Ulu, Experimental and numerical investigation on hydraulic performance of slit-check dams in subcritical flow condition, Water Resources Management, 36; pp. 1693-1710, 2022. doi.org/10.1007/s11269-022-03103-6

43-22   Suresh Modalavalasa, Vinay Chembolu, Subashisa Dutta, Vinayak Kulkarni, Combined effect of bridge piers and floodplain vegetation on main channel hydraulics, Experimental Thermal and Fluid Science, 136; 110669, 2022. doi.org/10.1016/j.expthermflusci.2022.110669

40-22   Mohammad Bagherzadeh, Farhad Mousavi, Mohammad Manafpour, Reza Mirzaee, Khosrow Hoseini, Numerical simulation and application of soft computing in estimating vertical drop energy dissipation with horizontal serrated edge, Water Supply, 127, 2022. doi.org/10.2166/ws.2022.127

39-22   Masumeh Rostam Abadi, Saeed Kazemi Mohsenabadi, Numerical study of the weir angle on the flow pattern and scour around the submerged weirs, International Journal of Modern Physics C, 2022. doi.org/10.1142/S0129183122501108

38-22   Vahid Hassanzadeh Vayghan, Mirali Mohammadi, Behzad Shakouri, Experimental and numerical examination of flow resistance in plane bed streams, Arabian Journal of Geosciences, 15; 483, 2022. doi.org/10.1007/s12517-022-09691-2

36-22   Kyong Oh Baek, Byong Jo Min, Investigation for flow characteristics of ice-harbor type fishway installed at mid-sized streams in Korea, Journal of Korea Water Resources Association, 55.1; pp. 33-42, 2022. 

34-22   Kyong Oh Baek, Jeong-Min Lee, Eun-Jin Han, Young-Do Kim, Evaluating attraction and passage efficiencies of pool-weir type fishways based on hydraulic analysis, Applied Sciences, 12.4; 1880, 2022. doi.org/10.3390/app12041880

33-22   Christopher Paschmann, David F. Vetsch, Robert M. Boes, Design of desanding facilities for hydropower schemes based on trapping efficiency, Water, 14.4; 520, 2022. doi.org/10.3390/w14040520

29-22   Mehdi Heyrani, Abdolmajid Mohammadian, Ioan Nistor, Omerul Faruk Dursun, Application of numerical and experimental modeling to improve the efficiency of Parshall flumes: A review of the state-of-the-art, Hydrology, 9.2; 26 2022. doi.org/10.3390/hydrology9020026

28-22   Kiyoumars Roushangar, Samira Akhgar, Saman Shanazi, The effect of triangular prismatic elements on the hydraulic performance of stepped spillways in the skimming flow regime: An experimental study and numerical modeling, Journal of Hydroinformatics, 2022. doi.org/10.2166/hydro.2022.031

26-22   Jorge Augusto Toapaxi Alvarez, Roberto Silva, Cristina Torres, Modelación numérica tridimensional del medidor de caudal Palmer-Bowlus aplicando el programa FLOW-3D (Three-dimensional numerical modeling of the Palmer-Bowlus measuring flume applying the FLOW-3D program), Revista Politécnica, 49.1; 2022. doi.org/10.33333/rp.vol49n1.04 

25-22   Shubing Dai, Sheng Jin, Numerical investigations of unsteady critical flow conditions over an obstacle using three models, Physics of Fluids, 34.2; 2022. doi.org/10.1063/5.0077585

23-22   Negar Ghahramani, H. Joanna Chen, Daley Clohan, Shielan Liu, Marcelo Llano-Serna, Nahyan M. Rana, Scott McDougall, Stephen G. Evans, W. Andy Take, A benchmarking study of four numerical runout models for the simulation of tailings flows, Science of the Total Environment, 827; 154245, 2022. doi.org/10.1016/j.scitotenv.2022.154245

22-22   Bahador Fatehi-Nobarian, Razieh Panahi, Vahid Nourani, Investigation of the Effect of Velocity on Secondary Currents in Semicircular Channels on Hydraulic Jump Parameters, Iranian Journal of Science and Technology: Transactions of Civil Engineering, 2022. doi.org/10.1007/s40996-021-00800-x

21-22   G. Viccione, C. Izzo, Three-dimensional CFD modelling of urban flood forces on buildings: A case study, Journal of Physics: Conference Series, 2162; 012020, 2022. doi.org/10.1088/1742-6596/2162/1/012020

20-22   Tohid Jamali Rovesht, Mohammad Manafpour, Mehdi Lotfi, Effects of flow condition and chute geometry on the shockwaves formed on chute spillway, Journal of Water Supply: Research and Technology-Aqua, 71.2; pp. 312-329, 2022. doi.org/10.2166/aqua.2022.139

17-22   Yansong Zhang, Jianping Chen, Fujun Zhou, Yiding Bao, Jianhua Yan, Yiwei Zhang, Yongchao Li, Feifan Gu, Qing Wang, Combined numerical investigation of the Gangda paleolandslide runout and associated dam breach flood propagation in the upper Jinsha River, SE Tibetan Plateau, Landslides, 2022. doi.org/10.1007/s10346-021-01768-5

16-22   I.A. Hernández-Rodríguez, J. López-Ortega, G. González-Blanco, R. Beristain-Cardoso, Performance of the UASB reactor during wastewater treatment and the effect of the biogas bubbles on its hydrodynamics, Environmental Technology, pp. 1-21, 2022. doi.org/10.1080/09593330.2022.2028015

15-22   Xu Deng, Sizhong He, Zhouhong Cao, Numerical investigation of the local scour around a coconut tree root foundation under wave-current joint actions, Ocean Engineering, 245; 110563, 2022. doi.org/10.1016/j.oceaneng.2022.110563

14-22   Rasool Kosaj, Rafid S. Alboresha, Sadeq O. Sulaiman, Comparison between numerical Flow3d software and laboratory data, for sediment incipient motion, IOP Conference Series: Earth and Environmental Science, 961; 012031, 2022. doi.org/10.1088/1755-1315/961/1/012031

13-22   Joseph M. Sinclair, S. Karan Venayagamoorthy, Timothy K. Gates, Some insights on flow over sharp-crested weirs using computational fluid dynamics: Implications for enhanced flow measurement, Journal of Irrigation and Drainage Engineering, 148.6; 2022. doi.org/10.1061/(ASCE)IR.1943-4774.0001652

12-22   Mete Koken, Ismail Aydin, Serhan Ademoglu, An iterative hydraulic design methodology based on numerical modeling for piano key weirs, Journal of Hydro-environment Research, 40; pp. 131-141, 2022. doi.org/10.1016/j.jher.2022.01.002

11-22   Najam us Saqib, Muhammad Akbar, Huali Pan, Guoqiang Ou, Muhammad Mohsin, Assad Ali, Azka Amin, Numerical analysis of pressure profiles and energy dissipation across stepped spillways having curved risers, Applied Sciences, 12.1; 448, 2022. doi.org/10.3390/app12010448

9-22   Amir Bordbar, Soroosh Sharifi, Hassan Hemida, Investigation of scour around two side-by-side piles with different spacing ratios in live-bed, Lecture Notes in Civil Engineering, 208; pp. 302-309, 2022. doi.org/10.1007/978-981-16-7735-9_33

8-22    Jian-cheng Li, Wei Wang, Yan-ming Zheng, Xiao-hao Wen, Jing Feng, Li Sheng, Chen Wang, Ming-kun Qiu, Using computational fluid dynamic simulation with Flow-3D to reveal the origin of the mushroom stone in the Xiqiao Mountain of Guangdong, China, Journal of Mountain Science, 19; pp. 1-15, 2022. doi.org/10.1007/s11629-021-7019-5

4-22   Ankur Kapoor, Aniruddha D. Ghare, Avinash M. Badar, CFD simulations of conical central baffle flumes, Journal of Irrigation and Drainage Engineering, 148.2, 2022. doi.org/10.1061/(ASCE)IR.1943-4774.0001653

2-22   Ramtin Sabeti, Mohammad Heidarzadeh, Numerical simulations of tsunami wave generation by submarine landslides: Validation and sensitivity analysis to landslide parameters, Journal of Waterway, Port, Coastal, and Ocean Engineering, 148.2; 05021016, 2022. doi.org/10.1061/(ASCE)WW.1943-5460.0000694

1-22   Juan Francisco Fuentes-Pérez, Ana L. Quaresma, Antonio Pinheiro, Francisco Javier Sanz-Ronda, OpenFOAM vs FLOW-3D: A comparative study of vertical slot fishway modelling, Ecological Engineering, 174, 2022.

145-21   Ebrahim Hamid Hussein Al-Qadami, Zahiraniza Mustaffa, Eduardo Martínez-Gomariz, Khamaruzaman Wan Yusof, Abdurrasheed S. Abdurrasheed, Syed Muzzamil Hussain Shah, Numerical simulation to assess floating instability of small passenger vehicle under sub-critical flow, Lecture Notes in Civil Engineering, 132; pp. 258-265, 2021. doi.org/10.1007/978-981-33-6311-3_30

140-21   J. Zulfan, B.M.Ginting, Investigation of spillway rating curve via theoretical formula, laboratory experiment, and 3D numerical modeling: A case study of the Riam Kiwa Dam, Indonesia, IOP Conference Series: Earth and Environmental Science, 930; 012030, 2021. doi.org/10.1088/1755-1315/930/1/012030

130-21   A.S.N. Amirah, F.Y. Boon, K.A. Nihla, Z.M. Salwa, A.W. Mahyun, N. Yaacof, Numerical simulation of flow within a storage area of HDPE modular pavement, IOP Conference Series: Earth and Environmental Science, 920; 012044, 2021. doi.org/10.1088/1755-1315/920/1/012044

129-21   Z.M. Yusof, Z.A.L. Shirling, A.K.A. Wahab, Z. Ismail, S. Amerudin, A hydrodynamic model of an embankment breaching due to overtopping flow using FLOW-3D, IOP Conference Series: Earth and Environmental Science, 920; 012036, 2021. doi.org/10.1088/1755-1315/920/1/012036

125-21   Ketaki H. Kulkarni, Ganesh A. Hinge, Comparative study of experimental and CFD analysis for predicting discharge coefficient of compound broad crested weir, Water Supply, 2021. doi.org/10.2166/ws.2021.403

119-21   Yan Liang, Yiqun Hou, Wangbin Hu, David Johnson, Junxing Wang, Flow velocity preference of Schizothorax oconnori Lloyd swimming upstream, Global Ecology and Conservation, 32; e01902, 2021. doi.org/10.1016/j.gecco.2021.e01902

116-21   Atabak Feizi, Aysan Ezati, Shadi Alizadeh Marallo, Investigation of hydrodynamic characteristics of flow caused by dam break around a downstream obstacle considering different reservoir shapes, Numerical Methods in Civil Engineering, 6.2; pp. 36-48, 2021.

114-21   Jackson Tellez-Alvarez, Manuel Gómez, Beniamino Russo, Marko Amezaga-Kutija, Numerical and experimental approaches toestimate discharge coefficients and energy loss coefficients in pressurized grated inlets, Hydrology, 8.4; 162, 2021. doi.org/10.3390/hydrology8040162

113-21   Alireza Khoshkonesh, Blaise Nsom, Fariba Ahmadi Dehrashid, Payam Heidarian, Khuram Riaz, Comparison of the SWE and 3D models in simulation of the dam-break flow over the mobile bed, 5th Scientific Conference of Applied Research in Science and Technology of Iran, 2021.

103-21   Farshid Mosaddeghi, Numerical modeling of dam breach in concrete gravity dams, Thesis, Middle East Technical University, Ankara, Turkey, 2021.

102-21   Xu Deng, Sizhong He, Zhouhong Cao, Tao Wu, Numerical investigation of the hydrodynamic response of an impermeable sea-wall subjected to artificial submarine landslide-induced tsunamis, Landslides, 2021. doi.org/10.1007/s10346-021-01773-8

100-21   Jinmeng Yang, Zhenzhong Shen, Jing Zhang, Xiaomin Teng, Wenbing Zhang, Jie Dai, Experimental and numerical investigation of flow over a spillway bend with different combinations of permeable spur dikes, Water Supply, ws2021335, 2021. doi.org/10.2166/ws.2021.335

99-21   Nigel A. Temple, Josh Adams, Evan Blythe, Zidane Twersky, Steve Blair, Rick Harter, Investigating the performance of novel oyster reef materials in Apalachicola Bay, Florida, ASBPA National Coastal Conference, New Orleans, LA, USA, September 28-October 1, 2021.

94-21   Xiaoyang Shen, Mario Oertel, Comparitive study of nonsymmetrical trapezoidal and rectangular piano key weirs with varying key width ratios, Journal of Hydraulic Engineering, 147.11, 2021. doi.org/10.1061/(ASCE)HY.1943-7900.0001942

93-21   Aysar Tuama Al-Awadi, Mahmoud Saleh Al-Khafaji, CFD-based model for estimating the river bed morphological characteristics near cylindrical bridge piers due to debris accumulation, Water Resources, 48; pp. 763-773, 2021. doi.org/10.1134/S0097807821050031

92-21   Juan Francisco Macián-Pérez, Francisco José Vallés-Morán, Rafael García-Bartual, Assessment of the performance of a modified USBR Type II stilling basin by a validated CFD model, Journal of Irrigation and Drainage Engineering , 147.11, 2021. doi.org/10.1061/(ASCE)IR.1943-4774.0001623

91-21   Ali Yıldız, Ali İhsan Martı, Mustafa Göğüş, Numerical and experimental modelling of flow at Tyrolean weirs, Flow Measurement and Instrumentation, 81; 102040, 2021. doi.org/10.1016/j.flowmeasinst.2021.102040

90-21   Yasamin Aghaei, Fouad Kilanehei, Shervin Faghihirad, Mohammad Nazari-Sharabian, Dynamic pressure at flip buckets of chute spillways: A numerical study, International Journal of Civil Engineering, 2021. doi.org/10.1007/s40999-021-00670-4

88-21   Shang-tuo Qian, Yan Zhang, Hui Xu, Xiao-sheng Wang, Jian-gang Feng, Zhi-xiang Li, Effects of surface roughness on overflow discharge of embankment weirs, Journal of Hydrodynamics, 33; pp. 773-781, 2021. doi.org/10.1007/s42241-021-0068-y

86-21   Alkistis Stergiopoulou, Vassilios Stergiopoulos, CFD simulations of tubular Archimedean screw turbines harnessing the small hydropotential of Greek watercourses, International Journal of Energy and Environment, 12.1; pp. 19-30, 2021.

85-21   Jun-tao Ren, Xue-fei Wu, Ting Zhang, A 3-D numerical simulation of the characteristics of open channel flows with submerged rigid vegetation, Journal of Hydrodynamics, 33; pp. 833-843, 2021. doi.org/10.1007/s42241-021-0063-3

84-21   Rasoul Daneshfaraz, Amir Ghaderi, Maryam Sattariyan, Babak Alinejad, Mahdi Majedi Asl, Silvia Di Francesco, Investigation of local scouring around hydrodynamic and circular pile groups under the influence of river material harvesting pits, Water, 13.6; 2192, 2021. doi.org/10.3390/w13162192

83-21   Mahdi Feizbahr, Navid Tonekaboni, Guang-Jun Jiang, Hong-Xia Chen, Optimized vegetation density to dissipate energy of flood flow in open canals, Mathematical Problems in Engineering, 2021; 9048808, 2021. doi.org/10.1155/2021/9048808

80-21   Wenjun Liu, Bo Wang, Yakun Guo, Numerical study of the dam-break waves and Favre waves down sloped wet rigid-bed at laboratory scale, Journal of Hydrology, 602; 126752, 2021. doi.org/10.1016/j.jhydrol.2021.126752

79-21   Zhen-Dong Shen, Yang Zhang, The three-dimensional simulation of granular mixtures weir, IOP Conference Series: Earth and Environmental Science, 820; 012024, 2021. doi.org/10.1088/1755-1315/820/1/012024

75-21   Mehrdad Ghorbani Mooselu, Mohammad Reza Nikoo, Parnian Hashempour Bakhtiari, Nooshin Bakhtiari Rayani, Azizallah Izady, Conflict resolution in the multi-stakeholder stepped spillway design under uncertainty by machine learning techniques, Applied Soft Computing, 110; 107721, 2021. doi.org/10.1016/j.asoc.2021.107721

73-21   Romain Van Mol, Plunge pool rehabilitation with prismatic concrete elements – Case study and physical model of Ilarion dam in Greece, Infoscience (EPFL Scientific Publications), 2021.

70-21   Khosro Morovati, Christopher Homer, Fuqiang Tian, Hongchang Hu, Opening configuration design effects on pooled stepped chutes, Journal of Hydraulic Engineering, 147.9, 2021. doi.org/10.1061%2F(ASCE)HY.1943-7900.0001897

68-21   R. Daneshfaraz, E. Aminvash, S. Di Francesco, A. Najibi, J. Abraham, Three-dimensional study of the effect of block roughness geometry on inclined drop, Numerical Methods in Civil Engineering, 6.1; pp. 1-9, 2021. 

66-21   Benjamin Hohermuth, Lukas Schmoker, Robert M. Boes, David Vetsch, Numerical simulation of air entrainment in uniform chute flow, Journal of Hydraulic Research, 59.3; pp. 378-391, 2021. doi.org/10.1080/00221686.2020.1780492

65-21   Junjun Tan, Honglin Tan, Elsa Goerig, Senfan Ke, Haizhen Huang, Zhixiong Liu, Xiaotao Shi, Optimization of fishway attraction flow based on endemic fish swimming performance and hydraulics, Ecological Engineering, 170; 106332, 2021. doi.org/10.1016/j.ecoleng.2021.106332

63-21   Erdinc Ikinciogullari, Muhammet Emin Emiroglu, Mehmet Cihan Aydin, Comparison of scour properties of classical and trapezoidal labyrinth weirs, Arabian Journal for Science and Engineering, 2021. doi.org/10.1007/s13369-021-05832-z

59-21   Elias Wehrmeister, José J. Ota, Separation in overflow spillways: A computational analysis, Journal of Hydraulic Research, 59, 2021. doi.org/10.1080/00221686.2021.1908438

53-21   Zongxian Liang, John Ditter, Riadh Atta, Brian Fox, Karthik Ramaswamy, Numerical modeling of tailings dam break using a Herschel-Bulkley rheological model, USSD Annual Conference, online, May 11-21, 2021. 

51-21   Yansong Zhang, Jianping Chen, Chun Tan, Yiding Bao, Xudong Han, Jianhua Yan, Qaiser Mehmood, A novel approach to simulating debris flow runout via a three-dimensional CFD code: A case study of Xiaojia Gully, Bulletin of Engineering Geology and the Environment, 80.5, 2021. doi.org/10.1007/s10064-021-02270-x

49-21   Ramtin Sabeti, Mohammad Heidarzadeh, Preliminary results of numerical simulation of submarine landslide-generated waves, EGU General Assembly 2021, online, April 19-30, 2021. doi.org/10.5194/egusphere-egu21-284

48-21   Anh Tuan Le, Ken Hiramatsu, Tatsuro Nishiyama, Hydraulic comparison between piano key weir and rectangular labyrinth weir, International Journal of GEOMATE, 20.82; pp. 153-160, 2021. doi.org/10.21660/2021.82.j2106

46-21   Maoyi Luo, Faxing Zhang, Zhaoming Song, Liyuan Zhang, Characteristics of flow movement in complex canal system and its influence on sudden pollution accidents, Mathematical Problems in Engineering, 6617385, 2021. doi.org/10.1155/2021/6617385

42-21   Jakub Major, Martin Orfánus, Zbyněk Zachoval, Flow over broad-crested weir with inflow by approach shaft – Numerical model, Civil Engineering Journal, 30.1; 19, 2021. doi.org/10.14311/CEJ.2021.01.0019 

41-21   Amir Ghaderi, Saeed Abbasi, Experimental and numerical study of the effects of geometric appendance elements on energy dissipation over stepped spillway, Water, 13.7; 957, 2021. doi.org/10.3390/w13070957

38-21   Ana L. Quaresma, António N. Pinheiro, Modelling of pool-type fishways flows: Efficiency and scale effects assessment, Water, 13.6; 851, 2021. doi.org/10.3390/w13060851

37-21   Alireza Khoshkonesh, Blaise Nsom, Farhad Bahmanpouri, Fariba Ahmadi Dehrashid, Atefah Adeli, Numerical study of the dynamics and structure of a partial dam-break flow using the VOF Method, Water Resources Management, 35; pp. 1513-1528, 2021. doi.org/10.1007/s11269-021-02799-2

36-21   Amir Ghaderi, Mehdi Dasineh, Francesco Aristodemo, Constanza Aricò, Numerical simulations of the flow field of a submerged hydraulic jump over triangular macroroughnesses, Water, 13.5; 674, 2021. doi.org/10.3390/w13050674

35-21   Hongliang Qi, Junxing Zheng, Chenguang Zhang, Modeling excess shear stress around tandem piers of the longitudinal bridge by computational fluid dynamics, Journal of Applied Water Engineering and Research, 2021. doi.org/10.1080/23249676.2021.1884614

31-21   Seth Siefken, Robert Ettema, Ari Posner, Drew Baird, Optimal configuration of rock vanes and bendway weirs for river bends: Numerical-model insights, Journal of Hydraulic Engineering, 147.5, 2021. doi.org/10.1061/(ASCE)HY.1943-7900.0001871

29-21   Débora Magalhães Chácara, Waldyr Lopes Oliveira Filho, Rheology of mine tailings deposits for dam break analyses, REM – International Engineering Journal, 74.2; pp. 235-243, 2021. doi.org/10.1590/0370-44672020740098

27-21   Ling Peng, Ting Zhang, Youtong Rong, Chunqi Hu, Ping Feng, Numerical investigation of the impact of a dam-break induced flood on a structure, Ocean Engineering, 223; 108669, 2021. doi.org/10.1016/j.oceaneng.2021.108669

26-21   Qi-dong Hou, Hai-bo Li, Yu-Xiang Hu, Shun-chao Qi, Jian-wen Zhou, Overtopping process and structural safety analyses of the earth-rock fill dam with a concrete core wall by using numerical simulations, Arabian Journal of Geosciences, 14; 234, 2021. doi.org/10.1007/s12517-021-06639-w

25-21   Filipe Romão, Ana L. Quaresma, José M. Santos, Susana D. Amaral, Paulo Branco, António N. Pinheiro, Performance and fish transit time over vertical slots, Water, 13.3; 275, 2021. doi.org/10.3390/w13030275

23-21   Jiahou Hu, Chengwei Na, Yi Wang, Study on discharge velocity of tailings mortar in dam break based on FLOW-3D, IOP Conference Series: Earth and Environmental Science, 6th International Conference on Hydraulic and Civil Engineering, Xi’an, China, December 11-13, 2020, 643; 012052, 2021. doi.org/10.1088/1755-1315/643/1/012052

21-21   Asad H. Aldefae, Rusul A. Alkhafaji, Experimental and numerical modeling to investigate the riverbank’s stability, SN Applied Sciences, 3; 164, 2021. doi.org/10.1007/s42452-021-04168-5

20-21   Yangliang Lu, Jinbu Yin, Zhou Yang, Kebang Wei, Zhiming Liu, Numerical study of fluctuating pressure on stilling basin slabwith sudden lateral enlargement and bottom drop, Water, 13.2; 238, 2021. doi.org/10.3390/w13020238

18-21   Prashant Prakash Huddar, Vishwanath Govind Bhave, Hydraulic structure design with 3D CFD model, Proceedings, 25th International Conference on Hydraulics, Water Resources and Coastal Engineering (HYDRO 2020), Odisha, India, March 26-28, 2021.

17-21   Morteza Sadat Helbar, Atefah Parvaresh Rizi, Javad Farhoudi, Amir Mohammadi, 3D flow simulation to improve the design and operation of the dam bottom outlets, Arabian Journal of Geosciences, 14; 90, 2021. doi.org/10.1007/s12517-020-06378-4

15-21   Charles R. Ortloff, Roman hydraulic engineering: The Pont du Gard Aqueduct and Nemausus (Nîmes) Castellum, Water, 13.1; 54, 2021. doi.org/10.3390/w13010054

12-21   Mehdi Karami Moghadam, Ata Amini, Ehsan Karami Moghadam, Numerical study of energy dissipation and block barriers in stepped spillways, Journal of Hydroinformatics, 23.2; pp. 284-297, 2021. doi.org/10.2166/hydro.2020.245

08-21   Prajakta P. Gadge, M. R. Bhajantri, V. V. Bhosekar, Numerical simulations of air entraining characteristics over high head chute spillway aerator, Proceedings, ICOLD Symposium on Sustainable Development of Dams and River Basins, New Dehli, India, February 24 – 27, 2021.

07-21   Pankaj Lawande, Computational fluid dynamics simulation methodologies for stilling basins, Proceedings, ICOLD Symposium on Sustainable Development of Dams and River Basins, New Dehli, India, February 24 – 27, 2021.

Below is a collection of technical papers in our Water & Environmental Bibliography. All of these papers feature FLOW-3D results. Learn more about how FLOW-3D can be used to successfully simulate applications for the Water & Environmental Industry.

02-21   Aytaç Güven, Ahmed Hussein Mahmood, Numerical investigation of flow characteristics over stepped spillways, Water Supply, in press, 2021. doi.org/10.2166/ws.2020.283

01-21   Le Thi Thu Hien, Nguyen Van Chien, Investigate impact force of dam-break flow against structures by both 2D and 3D numerical simulations, Water, 13.3; 344, 2021. doi.org/10.3390/w13030344

125-20   Farhad Bahmanpouri, Mohammad Daliri, Alireza Khoshkonesh, Masoud Montazeri Namin, Mariano Buccino, Bed compaction effect on dam break flow over erodible bed; experimental and numerical modeling, Journal of Hydrology, in press, 2020. doi.org/10.1016/j.jhydrol.2020.125645

209-23   Cong Trieu Tran, Cong Ty Trinh, Prediction of the vortex evolution and influence analysis of rough bed in a hydraulic jump with the Omega-Liutex method, Tehnički Vjesnik, 30.6; 2023. doi.org/10.17559/TV-20230206000327

203-23   Muhammad Waqas Zaffar, Ishtiaq Hassan, Zulfiqar Ali, Kaleem Sarwar, Muhammad Hassan, Muhammad Taimoor Mustafa, Faizan Ahmed Waris, Numerical investigation of hydraulic jumps with USBR and wedge-shaped baffle block basins for lower tailwater, AQUA – Water Infrastructure, Ecosystems and Society, 72.11; 2081, 2023. doi.org/10.2166/aqua.2023.261

201-23   E.F.R. Bollaert, Digital cloud-based platform to predict rock scour at high-head dams, Role of Dams and Reservoirs in a Successful Energy Transition, Eds. Robert Boes, Patrice Droz, Raphael Leroy, 2023. doi.org/10.1201/9781003440420

200-23   Iacopo Vona, Oysters’ integration on submerged breakwaters as nature-based solution for coastal protection within estuarine environments, Thesis, University of Maryland, 2023.

198-23   Hao Chen, Xianbin Teng, Zhibin Zhang, Faxin Zhu, Jie Wang, Zhaohao Zhang, Numerical analysis of the influence of the impinging distance on the scouring efficiency of submerged jets, Fluid Dynamics & Materials Processing, 20.2; pp. 429-445, 2023. doi.org/10.32604/fdmp.2023.030585

193-23   Chen Peng, Liuweikai Gu, Qiming Zhong, Numerical simulation of dam failure process based on FLOW-3D, Advances in Frontier Research on Engineering Structures, pp. 545-550, 2023. doi.org/10.3233/ATDE230245

189-23   Rebecca G. Englert, Age J. Vellinga, Matthieu J.B. Cartigny, Michael A. Clare, Joris T. Eggenhuisen, Stephen M. Hubbard, Controls on upstream-migrating bed forms in sandy submarine channels, Geology, 51.12; PP. 1137-1142, 2023. doi.org/10.1130/G51385.1

187-23   J.W. Kim, S.B. Woo, A numerical approach to the treatment of submerged water exchange processes through the sluice gates of a tidal power plant, Renewable Energy, 219.1; 119408, 2023. doi.org/10.1016/j.renene.2023.119408

186-23   Chan Jin Jeong, Hyung Jun Park, Hyung Suk Kim, Seung Oh Lee, Study on fish-friendly flow characteristic in stepped fishway, Proceedings of the Korean Water Resources Association Conference, 2023. (In Korean)

185-23   Jaehwan Yoo, Sedong Jang, Byunghyun Kim, Analysis of coastal city flooding in 2D and 3D considering extreme conditions and climate change, Proceedings of the Korean Water Resources Association Conference, 2023. (In Korean)

180-23   Prathyush Nallamothu, Jonathan Gregory, Jordan Leh, Daniel P. Zielinski, Jesse L. Eickholt, Semi-automated inquiry of fish launch angle and speed for hazard analysis, Fishes, 8.10; 476, 2023. doi.org/10.3390/fishes8100476

179-23   Reza Norouzi, Parisa Ebadzadeh, Veli Sume, Rasoul Daneshfaraz, Upstream vortices of a sluice gate: an experimental and numerical study, AQUA – Water Infrastructure, Ecosystems and Society, 72.10; 1906, 2023. doi.org/10.2166/aqua.2023.269

178-23   Bai Hao Li, How Tion Puay, Muhammad Azfar Bin Hamidi, Influence of spur dike’s angle on sand bar formation in a rectangular channel, IOP Conference Series: Earth and Environmental Science, 1238; 012027, 2023. doi.org/10.1088/1755-1315/1238/1/012027

177-23   Hao Zhe Khor, How Tion Puay, Influence of gate lip angle on downpull forces for vertical lift gates, IOP Conference Series: Earth and Environmental Science, 1238; 012019, 2023. doi.org/10.1088/1755-1315/1238/1/012019

175-23   Juan Francisco Macián-Pérez, Rafael García-Bartual, P. Amparo López-Jiménez, Francisco José Vallés-Morán, Numerical modeling of hydraulic jumps at negative steps to improve energy dissipation in stilling basins, Applied Water Science, 13.203; 2023. doi.org/10.1007/s13201-023-01985-4

174-23   Ahintha Kandamby, Dusty Myers, Narrows bypass chute CFD analysis, Dam Safety, 2023.

173-23   H. Jalili, R.C. Mahon, M.F. Martinez, J.W. Nicklow, Sediment sluicing from the reservoirs with high efficiency, SEDHYD, 2023.

170-23   Ramith Fernando, Gangfu Zhang, Beyond 2D: Unravelling bridge hydraulics with CFD modelling, 24th Queensland Water Symposium, 2023.

169-23   K. Licht, G. Lončar, H. Posavčić, I. Halkijević, Short-time numerical simulation of ultrasonically assisted electrochemical removal of strontium from water, 18th International Conference on Environmental Science and Technology (CEST), 2023.

166-23   Ebrahim Hamid Hussein Al-Qadami, Mohd Adib Mohammad Razi, Wawan Septiawan Damanik, Zahiraniza Mustaffa, Eduardo Martinez-Gomariz, Fang Yenn Teo, Anwar Ameen Hezam Saeed, Understanding the stability of passenger vehicles exposed to water flows through 3D CFD modelling, Sustainability, 15.17; 13262, 2023. doi.org/10.3390/su151713262

165-23   Ebrahim Hamid Hussein Al-Qadami, Mohd Adib Mohammad Razi, Wawan Septiawan Damanik, Zahiraniza Mustaffa, Eduardo Martinez-Gomariz, Fang Yenn Teo, Anwar Ameen Hezam Saeed, 3-dimensional numerical study on the critical orientation of the flooded passenger vehicles, Engineering Letters, 31.3; 2023.

124-20   John Petrie, Yan Qi, Mark Cornwell, Md Al Adib Sarker, Pranesh Biswas, Sen Du, Xianming Shi, Design of living barriers to reduce the impacts of snowdrifts on Illinois freeways, Illinois Center for Transportation Series No. 20-019, Research Report No. FHWA-ICT-20-012, 2020. doi.org/10.36501/0197-9191/20-019

123-20   Mohammad Reza Namaee, Jueyi Sui, Yongsheng Wu, Natalie Linklater, Three-dimensional numerical simulation of local scour in the vicinity of circular side-by-side bridge piers with ice cover, Canadian Journal of Civil Engineering, 2020. doi.org/10.1139/cjce-2019-0360

119-20   Tuğçe Yıldırım, Experimental and numerical investigation of vortex formation at multiple horizontal intakes, Thesis, Middle East Technical University, Ankara, Turkey, , 2020.

118-20   Amir Ghaderi, Mehdi Dasineh, Francesco Aristodemo, Ali Ghahramanzadeh, Characteristics of free and submerged hydraulic jumps over different macroroughnesses, Journal of Hydroinformatics, 22.6; pp. 1554-1572, 2020. doi.org/10.2166/hydro.2020.298

117-20   Rasoul Daneshfaraz, Amir Ghaderi, Aliakbar Akhtari, Silvia Di Francesco, On the effect of block roughness in ogee spillways with flip buckets, Fluids, 5.4; 182, 2020. doi.org/10.3390/fluids5040182

115-20   Chi Yao, Ligong Wu, Jianhua Yang, Influences of tailings particle size on overtopping tailings dam failures, Mine Water and the Environment, 2020. doi.org/10.1007/s10230-020-00725-3

114-20  Rizgar Ahmed Karim, Jowhar Rasheed Mohammed, A comparison study between CFD analysis and PIV technique for velocity distribution over the Standard Ogee crested spillways, Heliyon, 6.10; e05165, 2020. doi.org/10.1016/j.heliyon.2020.e05165

113-20   Théo St. Pierre Ostrander, Analyzing hydraulics of broad crested lateral weirs, Thesis, University of Innsbruck, Innsbruck, Austria, 2020.

111-20   Mahla Tajari, Amir Ahmad Dehghani, Mehdi Meftah Halaghi, Hazi Azamathulla, Use of bottom slots and submerged vanes for controlling sediment upstream of duckbill weirs, Water Supply, 20.8; pp. 3393-3403, 2020. doi.org/10.2166/ws.2020.238

110-20   Jian Zhou, Subhas K. Venayagamoorthy, How does three-dimensional canopy geometry affect the front propagation of a gravity current?, Physics of Fluids, 32.9; 096605, 2020. doi.org/10.1063/5.0019760

106-20   Juan Francisco Macián-Pérez, Arnau Bayón, Rafael García-Bartual, P. Amparo López-Jiménez, Characterization of structural properties in high reynolds hydraulic jump based on CFD and physical modeling approaches, Journal of Hydraulic Engineering, 146.12, 2020. doi.org/10.1061/(ASCE)HY.1943-7900.0001820

105-20   Bin Deng, He Tao, Changbo Jian, Ke Qu, Numerical investigation on hydrodynamic characteristics of landslide-induced impulse waves in narrow river-valley reservoirs, IEEE Access, 8; pp. 165285-165297, 2020. doi.org/10.1109/ACCESS.2020.3022651

102-20   Mojtaba Mehraein, Mohammadamin Torabi, Yousef Sangsefidi, Bruce MacVicar, Numerical simulation of free flow through side orifice in a circular open-channel using response surface method, Flow Measurement and Instrumentation, 76; 101825, 2020. doi.org/10.1016/j.flowmeasinst.2020.101825

101-20   Juan Francisco Macián Pérez, Numerical and physical modelling approaches to the study of the hydraulic jump and its application in large-dam stilling basins, Thesis, Universitat Politècnica de València, Valencia, Spain, 2020.

99-20   Chen-Shan Kung, Pin-Tzu Su, Chin-Pin Ko, Pei-Yu Lee, Application of multiple intake heads in engineering field, Proceedings, 30th International Ocean and Polar Engineering Conference (ISOPE), Online, October 11-17,  ISOPE-I-20-3116, 2020.

Below is a collection of technical papers in our Water & Environmental Bibliography. All of these papers feature FLOW-3D results. Learn more about how FLOW-3D can be used to successfully simulate applications for the Water & Environmental Industry.

91-20      Selahattin Kocaman, Stefania Evangelista, Giacomo Viccione, Hasan Güzel, Experimental and numerical analysis of 3D dam-break waves in an enclosed domain with a single oriented obstacle, Environmental Science Proceedings, 2; 35, 2020. doi.org/10.3390/environsciproc2020002035

89-20      Andrea Franco, Jasper Moernaut, Barbara Schneider-Muntau, Michael Strasser, Bernhard Gems, The 1958 Lituya Bay tsunami – pre-event bathymetry reconstruction and 3D numerical modelling utilising the computational fluid dynamics software Flow-3D, Natural Hazards and Earth Systems Sciences, 20; pp. 2255–2279, 2020. doi.org/10.5194/nhess-20-2255-2020

88-20      Cesar Simon, Eddy J. Langendoen, Jorge D. Abad, Alejandro Mendoza, On the governing equations for horizontal and vertical coupling of one- and two-dimensional open channel flow models, Journal of Hydraulic Research, 58.5; pp. 709-724, 2020. doi.org/10.1080/00221686.2019.1671507

87-20       Mohammad Nazari-Sharabian, Moses Karakouzian, Donald Hayes, Flow topology in the confluence of an open channel with lateral drainage pipe, Hydrology, 7.3; 57, 2020. doi.org/10.3390/hydrology7030057

84-20       Naohiro Takeichi, Takeshi Katagiri, Harumi Yoneda, Shusaku Inoue, Yusuke Shintani, Virtual Reality approaches for evacuation simulation of various disasters, Collective Dynamics (originally presented in Proceedings from the 9th International Conference on Pedestrian and Evacuation Dynamics (PED2018), Lund, Sweden, August 21-23, 2018), 5, 2020. doi.org/10.17815/CD.2020.93

83-20       Eric Lemont, Jonathan Hill, Ryan Edison, A problematic installation: CFD modelling of waste stabilisation pond mixing alternatives, Ozwater’20, Australian Water Association, Online, June 2, 2020, 2020.

77-20       Peng Yu, Ruigeng Hu, Jinmu Yang, Hongjun Liu, Numerical investigation of local scour around USAF with different hydraulic conditions under currents and waves, Ocean Engineering, 213; 107696, 2020. doi.org/10.1016/j.oceaneng.2020.107696

76-20       Alireza Mojtahedi, Nasim Soori, Majid Mohammadian, Energy dissipation evaluation for stepped spillway using a fuzzy inference system, SN Applied Sciences, 2; 1466, 2020. doi.org/10.1007/s42452-020-03258-0

74-20       Jackson D., Tellez Alvarez E., Manuel Gómez, Beniamino Russo, Modelling of surcharge flow through grated inlet, Advances in Hydroinformatics: SimHydro 2019 – Models for Extreme Situations and Crisis Management, Nice, France, June 12-14, 2019, pp. 839-847, 2020. doi.org/10.1007/978-981-15-5436-0_65

73-20       Saurav Dulal, Bhola NS Ghimire, Santosh Bhattarai, Ram Krishna Regmi, Numerical simulation of flow through settling basin: A case study of Budhi-Ganga Hydropower Project (BHP), International Journal of Engineering Research & Technology (IJERT), 9.7; pp. 992-998, 2020.

70-20       B. Nandi, S. Das, A. Mazumdar, Experimental analysis and numerical simulation of hydraulic jump, IOP Conference Series: Earth and Environmental Science, 2020 6th International Conference on Environment and Renewable Energy, Hanoi, Vietnam, February 24-26, 505; 012024, 2020. doi.org/10.1088/1755-1315/505/1/012024

69-20       Amir Ghaderi, Rasoul Daneshfaraz, Mehdi Dasineh, Silvia Di Francesco, Energy dissipation and hydraulics of flow over trapezoidal–triangular labyrinth weirs, Water (Special Issue: Combined Numerical and Experimental Methodology for Fluid–Structure Interactions in Free Surface Flows), 12.7; 1992, 2020. doi.org/10.3390/w12071992

68-20       Jia Ni, Linwei Wang, Xixian Chen, Luan Luan Xue, Isam Shahrour, Effect of the fish-bone dam angle on the flow mechanisms of a fish-bone type dividing dyke, Marine Technology Society Journal, 54.3; pp. 58-67, 2020. doi.org/10.4031/MTSJ.54.3.9

67-20       Yu Zhuang, Yueping Yin, Aiguo Xing, Kaiping Jin, Combined numerical investigation of the Yigong rock slide-debris avalanche and subsequent dam-break flood propagation in Tibet, China, Landslides, 17; pp. 2217-2229, 2020. doi.org/10.1007/s10346-020-01449-9

66-20       A. Ghaderi, R. Daneshfaraz, S. Abbasi, J. Abraham, Numerical analysis of the hydraulic characteristics of modified labyrinth weirs, International Journal of Energy and Water Resources, 4.2, 2020. doi.org/10.1007/s42108-020-00082-5

65-20      D.P. Zielinski, S. Miehls, G. Burns, C. Coutant, Adult sea lamprey espond to induced turbulence in a low current system, Journal of Ecohydraulics, 5, 2020. doi.org/10.1080/24705357.2020.1775504

63-20       Raffaella Pellegrino, Miguel Ángel Toledo, Víctor Aragoncillo, Discharge flow rate for the initiation of jet flow in sky-jump spillways, Water, Special Issue: Planning and Management of Hydraulic Infrastructure, 12.6; 1814, 2020. doi.org/10.3390/w12061814

59-20       Nesreen Taha, Maged M. El-Feky, Atef A. El-Saiad, Ismail Fathy, Numerical investigation of scour characteristics downstream of blocked culverts, Alexandria Engineering Journal, 59.5; pp. 3503-3513, 2020. doi.org/10.1016/j.aej.2020.05.032

57-20       Charles Ortloff, The Hydraulic State: Science and Society in the Ancient World, Routledge, London, UK, eBook ISBN: 9781003015192, 2020. doi.org/10.4324/9781003015192

54-20       Navid Aghajani, Hojat Karami, Hamed Sarkardeh, Sayed‐Farhad Mousavi, Experimental and numerical investigation on effect of trash rack on flow properties at power intakes, Journal of Applied Mathematics and Mechanics (ZAMM), online pre-issue, 2020. doi.org/10.1002/zamm.202000017

53-20     Tian Zhou, Theodore Endreny, The straightening of a river meander leads to extensive losses in flow complexity and ecosystem services, Water (Special Issue: A Systems Approach of River and River Basin Restoration), 12.6; 1680, 2020. doi.org/10.3390/w12061680

50-20       C.C. Battiston, F.A. Bombardelli, E.B.C. Schettini, M.G. Marques, Mean flow and turbulence statistics through a sluice gate in a navigation lock system: A numerical study, European Journal of Mechanics – B/Fluids, 84; pp.155-163, 2020. doi.org/10.1016/j.euromechflu.2020.06.003

47-20       Mohammad Nazari-Sharabian, Aliasghar Nazari-Sharabian, Moses Karakouzian, Mehrdad Karami, Sacrificial piles as scour countermeasures in river bridges: A numerical study using FLOW-3D, Civil Engineering Journal, 6.6; pp. 1091-1103, 2020. doi.org/10.28991/cej-2020-03091531

44-20    Leena Jaydeep Shevade, L. James Lo, Franco A. Montalto, Numerical 3D model development and validation of curb-cut inlet for efficiency prediction, Water, 12; 1791, 2020. doi.org/10.3390/w12061791

43-20       Vitor Hugo Pereira de Morais, Tiago Zenker Gireli, Paulo Vatavuk, Numerical and experimental models applied to an ogee crest spillway and roller bucket stilling basin, Brazilian Journal of Water Resources, 2020. doi.org/10.1590/2318-0331.252020190005

42-20       Chen Xie, Qin Chen, Gang Fan, Chen Chen, Numerical simulation of the natural erosion and breaching process of the “10.11” Baige Landslide Dam on the Jinsha River, Dam Breach Modelling and Risk Disposal, pp. 376-377, International Conference on Embankment Dams (ICED), Beijing, China, June 5 – 7, 2020. doi.org/10.1007/978-3-030-46351-9_40

41-20       Niloofar Aghili Mahabadi, Hamed Reza Zarif Sanayei, Performance evaluation of bilateral side slopes in piano key weirs by numerical simulation, Modeling Earth Systems and Environment, 6; pp. 1477-1486, 2020. doi.org/10.1007/s40808-020-00764-3

40-20       P. April Le Quéré, I. Nistor, A. Mohammadian, Numerical modeling of tsunami-induced scouring around a square column: Performance assessment of FLOW-3D and Delft3D, Journal of Coastal Research (preprint), 2020. doi.org/10.2112/JCOASTRES-D-19-00181

39-20       Jian Zhou, Subhas K. Venayagamoorthy, Impact of ambient stable stratification on gravity currents propagating over a submerged canopy, Journal of Fluid Mechanics, 898; A15, 2020. doi.org/10.1017/jfm.2020.418

37-20     Aliasghar Azma, Yongxiang Zhang, The effect of variations of flow from tributary channel on the flow behavior in a T-shape confluence, Processes, 8; 614, 2020. doi.org/10.3390/pr8050614

35-20     Selahattin Kocaman, Hasan Güzel, Stefania Evangelista, Hatice Ozmen-Cagatay, Giacomo Viccione, Experimental and numerical analysis of a dam-break flow through different contraction geometries of the channel, Water, 12; 1124, 2020. doi.org/10.3390/w12041124

32-20       Adriano Henrique Tognato, Modelagem CFD da interação entre hidrodinâmica costeira e quebra-mar submerso: estudo de caso da Ponta da Praia em Santos, SP (CFD modeling of interaction between sea waves and submerged breakwater at Ponta de Praia – Santos, SP: a case study, Thesis, Universidad Estadual de Campinas, Campinas, Brazil, 2020.

31-20   Hamidreza Samma, Amir Khosrojerdi, Masoumeh Rostam-Abadi, Mojtaba Mehraein and Yovanni Cataño-Lopera, Numerical simulation of scour and flow field over movable bed induced by a submerged wall jet, Journal of Hydroinformatics, 22.2, pp. 385-401, 2020. doi.org/10.2166/hydro.2020.091

28-20   Halah Kais Jalal and Waqed H. Hassan, Three-dimensional numerical simulation of local scour around circular bridge pier using FLOW-3D software, IOP Conference Series: Materials Science and Engineering, art. no. 012150, 3rd International Conference on Engineering Sciences, Kerbala, Iraq, November 4-6, 2019745. doi.org/10.1088/1757-899X/745/1/012150

25-20   Faizal Yusuf and Zoran Micovic, Prototype-scale investigation of spillway cavitation damage and numerical modeling of mitigation options, Journal of Hydraulic Engineering, 146.2, 2020. doi.org/10.1061/(ASCE)HY.1943-7900.0001671

24-20   Huan Zhang, Zegao Yin, Yipei Miao, Minghui Xia and Yingnan Feng, Hydrodynamic performance investigation on an upper and lower water exchange device, Aquacultural Engineering, 90, art. no. 102072, 2020. doi.org/10.1016/j.aquaeng.2020.102072

22-20   Yu-xiang Hu, Zhi-you Yu and Jian-wen Zhou, Numerical simulation of landslide-generated waves during the 11 October 2018 Baige landslide at the Jinsha River, Landslides, 2020. doi.org/10.1007/s10346-020-01382-x

19-20   Amir Ghaderi, Mehdi Dasineh, Saeed Abbasi and John Abraham, Investigation of trapezoidal sharp-crested side weir discharge coefficients under subcritical flow regimes using CFD, Applied Water Science, 10, art. no. 31, 2020. doi.org/10.1007/s13201-019-1112-8

18-20   Amir Ghaderi, Saeed Abbasi, John Abraham and Hazi Mohammad Azamathulla, Efficiency of trapezoidal labyrinth shaped stepped spillways, Flow Measurement and Instrumentation, 72, art. no. 101711, 2020. doi.org/10.1016/j.flowmeasinst.2020.101711

16-20   Majid Omidi Arjenaki and Hamed Reza Zarif Sanayei, Numerical investigation of energy dissipation rate in stepped spillways with lateral slopes using experimental model development approach, Modeling Earth Systems and Environment, 2020. doi.org/10.1007/s40808-020-00714-z

15-20   Bo Wang, Wenjun Liu, Wei Wang, Jianmin Zhang, Yunliang Chen, Yong Peng, Xin Liu and Sha Yang, Experimental and numerical investigations of similarity for dam-break flows on wet bed, Journal of Hydrology, 583, art. no. 124598, 2020. doi.org/10.1016/j.jhydrol.2020.124598

14-20   Halah Kais Jalal and Waqed H. Hassan, Effect of bridge pier shape on depth of scour, IOP Conference Series: Materials Science and Engineering, art. no. 012001, 3rd International Conference on Engineering Sciences, Kerbala, Iraq, November 4-6, 2019671. doi.org/10.1088/1757-899X/671/1/012001

13-20   Shahad R. Mohammed, Basim K. Nile and Waqed H. Hassan, Modelling stilling basins for sewage networks, IOP Conference Series: Materials Science and Engineering, art. no. 012111, 3rd International Conference on Engineering Sciences, Kerbala, Iraq, November 4-6, 2019671. doi.org/10.1088/1757-899X/671/1/012111

11-20   Xin Li, Liping Jin, Bernie A. Engel, Zeng Wang, Wene Wang, Wuquan He and Yubao Wang, Influence of the structure of cylindrical mobile flumes on hydraulic performance characteristics in U-shaped channels, Flow Measurement and Instrumentation, 72, art. no. 101708, 2020. doi.org/10.1016/j.flowmeasinst.2020.101708

10-20   Nima Aein, Mohsen Najarchi, Seyyed Mohammad Mirhosseini Hezaveh, Mohammad Mehdi Najafizadeh and Ehsanollah Zeigham, Simulation and prediction of discharge coefficient of combined weir–gate structure, Proceedings of the Institution of Civil Engineers – Water Management (ahead of print), 2020. doi.org/10.1680/jwama.19.00047

03-20   Agostino Lauria, Francesco Calomino, Giancarlo Alfonsi, and Antonino D’Ippolito, Discharge coefficients for sluice gates set in weirs at different upstream wall inclinations, Water, 12, art. no. 245, 2020. doi.org/10.3390/w12010245

113-19   Ruidong An, Jia Li, Typical biological behavior of migration and flow pattern creating for fish schooling, E-Proceedings, 38th IAHR World Congress, Panama City, Panama, September 1-6, 2019.

112-19   Wenjun Liu, Bo Wang, Hang Wang, Jianmin Zhang, Yunliang Chen, Yong Peng, Xin Liu, Sha Yang, Experimental and numerical modeling of dam-break flows in wet downstream conditions, E-Proceedings, 38th IAHR World Congress, Panama City, Panama, September 1-6, 2019.

111-19   Zhang Chendi, Liu Yingjun, Xu Mengzhen, Wang Zhaoyin, The 3D numerical study on flow properties of individual step-pool, Proceedings: 14th International Symposium on River Sedimentation, Chengdu, China, September 16-19, 2019.

110-19   Mason Garfield, The effects of scour on the flow field at a bendway weir, Thesis: Colorado State University, Fort Collins, Colorado, Colorado State University, Fort Collins, Colorado.

109-19   Seth Siefken, Computational fluid dynamics models of Rio Grande bends fitted with rock vanes or bendway weirs, Thesis: Colorado State University, Fort Collins, Colorado, Colorado State University, Fort Collins, Colorado.

108-19   Benjamin Israel Devadason and Paul Schweiger, Decoding the drowning machines: Using CFD modeling to predict and design solutions to remediate the dangerous hydraulic roller at low head dams, The Journal of Dam Safety, 17.1, pp. 20-31, 2019.

106-19   Amir Ghaderi and Saeed Abbasi, CFD simulations of local scouring around airfoil-shaped bridge piers with and without collar, Sādhanā, art. no. 216, 2019. doi.org/10.1007/s12046-019-1196-8

105-19   Jacob van Alwon, Numerical and physical modelling of aerated skimming flows over stepped spillways, Thesis, University of Leeds, Leeds, United Kingdom, 2019.

100-19   E.H. Hussein Al-Qadami, A.S. Abdurrasheed, Z. Mustaffa, K.W. Yusof, M.A. Malek and A. Ab Ghani, Numerical modelling of flow characteristics over sharp crested triangular hump, Results in Engineering, 4, art. no. 100052, 2019. doi.org/10.1016/j.rineng.2019.100052

99-19   Agostino Lauria, Francesco Calomino, Giancarlo Alfonsi, and Antonino D’Ippolito, Discharge coefficients for sluice gates set in weirs at different upstream wall inclinations, Water, 12.1, art. no. 245, 2019. doi.org/10.3390/w12010245

98-19   Redvan Ghasemlounia and M. Sedat Kabdasli, Surface suspended sediment distribution pattern for an unexpected flood event at Lake Koycegiz, Turkey, Proceedings, 14th National Conference on Watershed Management Sciences and Engineering, Urmia, Iran, July 16-17, 2019.

97-19   Brian Fox, Best practices for simulating hydraulic structures with CFD, Proceedings, Dam Safety 2019, Orlando, Florida, USA, September 8-12, 2019.

96-19   John Wendelbo, Verification of CFD predictions of self-aeration onset on stepped chute spillways, Proceedings, Dam Safety 2019, Orlando, Florida, USA, September 8-12, 2019.

95-19   Pankaj Lawande, Anurag Chandorkar and Adhirath Mane, Predicting discharge rating curves for tainter gate controlled spillway using CFD simulations, Proceedings, 24th HYDRO 2019, International Conference, Hyderabad, India, December 18-20, 2019.

91-19   Gyeong-Bo Kim, Wei Cheng, Richards C. Sunny, Juan J. Horrillo, Brian C. McFall, Fahad Mohammed, Hermann M. Fritz, James Beget, and Zygmunt Kowalik , Three Dimensional Landslide Generated Tsunamis: Numerical and Physical Model Comparisons, Landslides, 2019. doi.org/10.1007/s10346-019-01308-2

85-19   Susana D. Amaral, Ana L. Quaresma, Paulo Branco, Filipe Romão, Christos Katopodis, Maria T. Ferreira, António N. Pinheiro, and José M. Santos, Assessment of retrofitted ramped weirs to improve passage of potamodromous fish, Water, 11, art. no. 2441, 2019. doi.org/10.3390/w11122441

82-19   Shubing Dai, Yong He, Jijian Yang, Yulei ma, Sheng Jin, and Chao Liang, Numerical study of cascading dam-break characteristics using SWEs and RANS, Water Supply, 2019. doi.org/10.2166/ws.2019.168

81-19   Kyong Oh Baek, Evaluation technique for efficiency of fishway based on hydraulic analysis, Journal of Korea Water Resources Association, 52.spc2, pp. 855-863, 2019. doi.org/10.3741/JKWRA.2019.52.S-2.855

80-19   Yongye Li, Yuan Gao, Xiaomeng Jia, Xihuan Sun, and Xuelan Zhang, Numerical simulations of hydraulic characteristics of a flow discharge measurement process with a plate flowmeter in a U-channel, Water, art. no. 2392, 2019. doi.org/10.3390/w11112382

76-19   Youtong Rong, Ting Zhang, Yanchen Zheng, Chunqi Hu, Ling Peng, and Ping Feng, Three-dimensional urban flood inundation simulation based on digital aerial photogrammetry, Journal of Hydrology, in press, 2019. doi.org/10.1016/j.jhydrol.2019.124308

74-19   Youtong Rong, Ting Zhang, Ling Peng, and Ping Feng, Three-dimensional numerical simulation of dam discharge and flood routing in Wudu Reservoir, Water, 11, art. no. 2157, 2019. doi.org/10.3390/w11102157

70-19   Le Thi Thu Hien, Study the flow over chute spillway by both numerical and physical models, Proceedings, pp. 845-851, 10th International Conference on Asian and Pacific Coasts (APAC 2019), Hanoi, Vietnam, September 25-28, 2019. doi.org/10.1007/978-981-15-0291-0_116

69-19   T. Vinh Cuong, N. Thanh Hung, V. Thanh Te, P. Anh Tuan, Analysis of spur dikes spatial layout to river bed degradation under reversing tidal flow, Proceedings, pp. 737-744, 10th International Conference on Asian and Pacific Coasts (APAC 2019), Hanoi, Vietnam, September 25-28, 2019. doi.org/10.1007/978-981-15-0291-0_101

67-19   Zongshi Dong, Junxing Wang, David Florian Vetsch, Robert Michael Boes, and Guangming Tan, Numerical simulation of air–water two-phase flow on stepped spillways behind X-shaped flaring gate piers under very high unit discharge, Water, 11, art. no. 1956, 2019. doi.org/10.3390/w11101956

66-19   Tony L. Wahl, Effect of boundary layer conditions on uplift pressures at open offset spillway joints, Sustainable and Safe Dams Around the World: Proceedings, 2019. doi.org/10.1201/9780429319778-182

65-19   John Petrie, Kun Zhang, and Mahmoud Shehata, Numerical simulation of snow deposition around living snow fences, Community Center for Environmentally Sustainable Transportation in Cold Climates (CESTiCC), Project Report, 2019.

64-19   Andrea Franco, Jasper Moernaut, Barbara Schneider-Muntau, Markus Aufleger, Michael Strasser, and Bernhard Gems, Lituya Bay 1958 Tsunami – detailed pre-event bathymetry reconstruction and 3D-numerical modelling utilizing the CFD software FLOW-3D, Natural Hazards and Earth Systems Sciences, under review, 2019. doi.org/10.5194/nhess-2019-285

63-19   J. Patarroyo, D. Damov, D. Shepherd, G. Snyder, M. Tremblay, and M. Villeneuve, Hydraulic design of stepped spillway using CFD supported by physical modelling: Muskrat Falls hydroelectric generating facility, Sustainable and Safe Dams Around the World: Proceedings, , pp. 205-219, 2019. doi.org/10.1201/9780429319778-19

61-19   A.S. Abdurrasheed, K.W. Yusof, E.H. Hussein Alqadami, H. Takaijudin, A.A. Ghani, M.M. Muhammad, A.T. Sholagberu, M.K. Zainalfikry, M. Osman, and M.S. Patel, Modelling of flow parameters through subsurface drainage modules for application in BIOECODS, Water, 11, art. no. 1823, 2019. doi.org/10.3390/w11091823

59-19     Brian Fox and Robert Feurich, CFD analysis of local scour at bridge piers, Proceedings of the Federal Interagency Sedimentation and Hydraulic Modeling Conference (SEDHYD), Reno, Nevada, June 24-28, 2019.

56-19     Pankaj Lawande, Brian Fox, and Anurag Chandorkar, Three dimensional CFD modeling of flow over a tainter gate spillway, International Dam Safety Conference, Bhubaneswar, Odisha, India, February 13-14, 2019.

49-19     Yousef Sangsefidi, Bruce MacVicar, Masoud Ghodsian, Mojtaba Mehraein, Mohammadamin Torabi, and Bruce M. Savage, Evaluation of flow characteristics in labyrinth weirs using response surface methodology, Flow Measurement and Instrumentation, Vol. 69, 2019. doi: 10.1016/j.flowmeasinst.2019.101617

43-19     Gongyun Liao, Zancheng Tang, and Fei Zhu, Self-cleaning performance of double-layer porous asphalt pavements with different granular diameters and layer combinations, 19th COTA International Conference of Transportation, Nanjing, China, July 6-8, 2019.

42-19     Tsung-Chun Ho, Gwo-Jang Hwang, Kao-Shu Hwang, Kuo-Cheng Hsieh, and Lung-Wei Chen, Experimental and numerical study on desilting efficiency of the bypassing tunnel for Nan-Hua reservoir, 3rd International Workshop on Sediment Bypass Tunnels, Taipei, Taiwan, April 9-12, 2019.

41-19     Chang-Ting Hsieh, Sheng-Yung Hsu, and Chin-Pin Ko, Planning of sluicing tunnel in front of the Wushe dam – retrofit the existing water diversion tunnel as an example, 3rd International Workshop on Sediment Bypass Tunnels, Taipei, Taiwan, April 9-12, 2019.

40-19     Chi-Lin Yang, Pang-ku Yang, Fu-June Wang, and Kuo-Cheng Hsieh, Study on the transportation of high-concentration sediment flow and the operation of sediment de-silting in Deji Reservoir, 3rd International Workshop on Sediment Bypass Tunnels, Taipei, Taiwan, April 9-12, 2019.

39-19   Sam Glovik and John Wendelbo, Advanced CFD air entrainment capabilities for baffle drop structure design, NYWEA 91st Annual Meeting, New York, NY, February 3-6, 2019.

36-19     Ahmed M. Helmi, Heba T. Essawy, and Ahmed Wagdy, Three-dimensional numerical study of stacked drop manholes, Journal of Irrigation and Drainage Engineering, Vol. 145, No. 9, 2019. doi: 10.1061/(ASCE)IR.1943-4774.0001414

33-19     M. Cihan Aydin, A. Emre Ulu, and Çimen Karaduman, Investigation of aeration performance of Ilısu Dam outlet using two-phase flow model, Applied Water Science, Vol. 9, No. 111, 2019. doi: 10.1007/s13201-019-0982-0

16-19     Bernard Twaróg, The analysis of the reactive work of the Alden Turbine, Technical Transactions I, Environmental Engineering, 2019. doi: 10.4467/2353737XCT.19.010.10050

14-19     Guodong Li, Xingnan Li, Jian Ning, and Yabing Deng, Numerical simulation and engineering application of a dovetail-shaped bucket, Water, Vol. 11, No. 2, 2019. doi: 10.3390/w11020242

13-19     Ilaria Rendina, Giacomo Viccione, and Leonardo Cascini, Kinematics of flow mass movements on inclined surfaces, Theoretical and Computational Fluid Dynamics, Vol. 33, No. 2, pp. 107-123, 2019. doi: 10.1007/s00162-019-00486-y

10-19     O.K. Saleh, E.A. Elnikhely, and Fathy Ismail, Minimizing the hydraulic side effects of weirs construction by using labyrinth weirs, Flow Measurement and Instrumentation, Vol. 66, pp. 1-11, 2019. doi: 10.1016/j.flowmeasinst.2019.01.016

05-19   Hakan Ersoy, Murat Karahan, Kenan Gelişli, Aykut Akgün, Tuğçe Anılan, M. Oğuz Sünnetci, Bilgehan Kul Yahşi, Modelling of the landslide-induced impulse waves in the Artvin Dam reservoir by empirical approach and 3D numerical simulation, Engineering Geology, Vol. 249, pp. 112-128, 2019. doi: 10.1016/j.enggeo.2018.12.025

96-18     Kyung-Seop Sin, Robert Ettema, Christopher I. Thornton, Numerical modeling to assess the influence of bendway weirs on flow distribution in river beds, Task 4 of Study: Native Channel Topography and Rock-Weir Structure Channel-Maintenance Techniques, U.S. Dept. of the Interior. CSU-HYD Report No. 2018-1, 2018.

95-18   Thulfikar Razzak Al-Husseini, Hayder A. Al-Yousify and Munaf A. Al-Ramahee, Experimental and numerical study of the effect of the downstream spillway face’s angle on the stilling basin’s energy dissipation, International Journal of Civil Engineering and Technology, 9.8, pp. 1327-1337, 2018.

94-18   J. Michalski and J. Wendelbo, Utilizing CFD methods as a forensic tool in pipeline systems to assess air/water transient issues, Proceedings, 7, pp. 5519-5527, 91st Water Environment Federation Technical Exhibition & Conference (WEFTEC), New Orleans, LA, United States, September 29 – October 3, 2018. doi.org/10.2175/193864718825138817

79-18 Harold Alvarez and John Wendelbo, Estudio de 3 modelos matemáticos para similar olas producidas por derrumbes en embalses y esfuerzos en compuertas, XXVIII Congreso Latinoamericano de Hidráulica, Buenos Aires, Argentina, September 2018. (In Spanish)

70-18   Michael Pfister, Gaetano Crispino, Thierry Fuchsmann, Jean-Marc Ribi and Corrado Gisonni, Multiple inflow branches at supercritical-type vortex drop shaft, Journal of Hydraulic Engineering, Vol. 144, No. 11, 2018. doi.org/10.1061/(ASCE)HY.1943-7900.0001530

67-18   F. Nunes, J. Matos and I. Meireles, Numerical modelling of skimming flow over small converging spillways, 3rd International Conference on Protection against Overtopping, June 6-8, 2018, Grange-over-Sands, UK, 2018.

66-18   Maria João Costa, Maria Teresa Ferreira, António N. Pinheiro and Isabel Boavida, The potential of lateral refuges for Iberian barbel under simulated hydropeaking conditions, Ecological Engineering, Vol. 124, 2018. doi.org/10.1016/j.ecoleng.2018.07.029

63-18   Michael J. Seluga, Frederick Vincent, Samuel Glovick and Brad Murray, A new approach to hydraulics in baffle drop shafts to address dry and wet weather flow in combined sewer tunnels, North American Tunneling Conference Proceedings, June 24-27, 2018, Washington, D.C. pp. 448-461, 2018. © Society for Mining, Metallurgy & Exploration

62-18   Ana Quaresma, Filipe Romão, Paulo Branco, Maria Teresa Ferreira and António N. Pinheiro, Multi slot versus single slot pool-type fishways: A modelling approach to compare hydrodynamics, Ecological Engineering, Vol. 122, pp. 197-206, 2018. doi.org/10.1016/j.ecoleng.2018.08.006

57-18   Amir Isfahani, CFD modeling of piano key weirs using FLOW-3D, International Dam Safety Conference, January 23-24, 2018, Thiruvananthapuram, Kerala, India; Technical Session 1A, Uncertainties and Risk Management in Dams, 2018.

49-18   Jessica M. Thompson, Jon M. Hathaway and John S. Schwartz, Three-dimensional modeling of the hydraulic function and channel stability of regenerative stormwater conveyances, Journal of Sustainable Water in the Built Environment, vol. 4, no.3, 2018. doi.org/10.1061/JSWBAY.0000861

46-18   A.B. Veksler and S.Z. Safin, Hydraulic regimes and downstream scour at the Kama Hydropower Plant, Power Technology and Engineering, vol. 51, no. 5, pp. 2-13, 2018. doi.org/10.1007/s10749-018-0862-z

45-18   H. Omara and A. Tawfik, Numerical study of local scour around bridge piers, 9th Annual Conference on Environmental Science and Development, Paris, France, Feb. 7-9, 2018; IOP Conference Series: Earth and Environmental Sciences, vol. 151, 2018. doi.org:10.1088/1755-1315/151/1/012013

40-18   Vincent Libaud, Christophe Daux and Yanis Oukid, Practical Capacities and Challenges of 3D CFD Modelling: Feedback Experience in Engineering Projects, Advances in Hydroinformatics, pp. 767-780, 2018. doi.org/10.1007/978-981-10-7218-5_55

39-18   Khosro Morovati and Afshin Eghbalzadeh, Study of inception point, void fraction and pressure over pooled stepped spillways using FLOW-3D, International Journal of Numerical Methods for Heat & Fluid Flow, vol. 28, no. 4, pp.982-998, 2018. doi.org/10.1108/HFF-03-2017-0112

34-18   Tomasz Siuta, The impact of deepening the stilling basin on the characteristics of hydraulic jump, Technical Transactions, vol. 3, pp. 173-186, 2018.

32-18   Azin Movahedi, M.R. Kavianpour, M. R and Omid Aminoroayaie Yamini, Evaluation and modeling scouring and sedimentation around downstream of large dams, Environmental Earth Sciences, vol. 77, no. 8, pp. 320, 2018. doi.org/10.1007/s12665-018-7487-2

31-18   Yang Song, Ling-Lei Zhang, Jia Li, Min Chen and Yao-Wen Zhang, Mechanism of the influence of hydrodynamics on Microcystis aeruginosa, a dominant bloom species in reservoirs, Science of The Total Environment, vol. 636, pp. 230-239, 2018. doi.org/10.1016/j.scitotenv.2018.04.257

30-18   Shaolin Yang, Wanli Yang, Shunquan Qin, Qiao Li and Bing Yang, Numerical study on characteristics of dam-break wave, Ocean Engineering, vol. 159, pp.358-371, 2018. doi.org/10.1016/j.oceaneng.2018.04.011

27-18   Rachel E. Chisolm and Daene C. McKinney, Dynamics of avalanche-generated impulse waves: three-dimensional hydrodynamic simulations and sensitivity analysis, Natural Hazards and Earth System Sciences, vol. 18, pp. 1373-1393, 2018. doi.org/10.5194/nhess-18-1373-2018.

24-18   Han Hu, Zhongdong Qian, Wei Yang, Dongmei Hou and Lan Du, Numerical study of characteristics and discharge capacity of piano key weirs, Flow Measurement and Instrumentation, vol. 62, pp. 27-32, 2018. doi.org/10.1016/j.flowmeasinst.2018.05.004

23-18   Manoochehr Fathi-Moghaddam, Mohammad Tavakol Sadrabadi and Mostafa Rahmanshahi, Numerical simulation of the hydraulic performance of triangular and trapezoidal gabion weirs in free flow condition, Flow Measurement and Instrumentation, vol. 62, pp. 93-104, 2018. doi.org/10.1016/j.flowmeasinst.2018.05.005

22-18   Anastasios I.Stamou, Georgios Mitsopoulos, Peter Rutschmann and Minh Duc Bui, Verification of a 3D CFD model for vertical slot fish-passes, Environmental Fluid Mechanics, June 2018. doi.org/10.1007/s10652-018-9602-z

17-18   Nikou Jalayeri, John Wendelbo, Joe Groeneveld, Andrew John Bearlin, and John Gulliver, Boundary dam total dissolved gas analysis using a CFD model, Proceedings from the U.S. Society on Dams Annual Conference, April 30 – May 4, 2018, © 2018 U.S. Society on Dams.

12-18   Bernard Twaróg, Interaction between hydraulic conditions and structures – fluid structure interaction problem solving. A case study of a hydraulic structure, Technical Transactions 2/2018, Environmental Engineering, DOI: 10.4467/2353737XCT.18.029.8002

06-18   Oscar Herrera-Granados, Turbulence Flow Modeling of One-Sharp-Groyne Field, © Springer International Publishing AG 2018, M. B. Kalinowska et al. (eds.), Free Surface Flows and Transport Processes, GeoPlanet: Earth and Planetary Sciences, https://doi.org/10.1007/978-3-319-70914-7_12

05-18  Shangtuo Qian, Jianhua Wu, Yu Zhou and Fei Ma, Discussion of “Hydraulic Performance of an Embankment Weir with Rough Crest” by Stefan Felder and Nushan Islam, J. Hydraul. Eng., 2018, 144(4): 07018003, © ASCE.

04-18   Faezeh Tajabadi, Ehsan Jabbari and Hamed Sarkardeh, Effect of the end sill angle on the hydrodynamic parameters of a stilling basin, DOI 10.1140/epjp/i2018-11837-y, Eur. Phys. J. Plus (2018) 133: 10

03-18   Dhemi Harlan, Dantje K. Natakusumah, Mohammad Bagus Adityawan, Hernawan Mahfudz and Fitra Adinata, 3D Numerical Modeling of Flow in Sedimentation Basin, MATEC Web of Conferences 147, 03012 (2018), https://doi.org/10.1051/matecconf/201814703012 SIBE 2017

02-18   ARKAN IBRAHIM, AZHEEN KARIM and Mustafa GÜNAL, Simulation of local scour development downstream of broad-crested weir with inclined apron, European Journal of Science and Technology Special Issue, pp. 57-61, January 2018, Copyright © 2017 EJOSAT.

62-17   Abbas Mansoori, Shadi Erfanian and Farhad Khamchin Moghadam, A study of the conditions of energy dissipation in stepped spillways with A-shaped step using FLOW-3D, Civil Engineering Journal, 3.10, 2017.

57-17   Ben Modra, Brett Miller, Nigel Moon and Andrew Berghuis, Physical model testing of a bespoke articulated concrete block (ACB) fishway, 13th Hydraulics in Water Engineering Conference, Sydney, Nov. 13-18, 2017; Engineers Australia, pp. 301-309, 2017.

53-17   C. Gonzalez, U. Baeumer and C. Russell, Natural disaster relief and recovery arrangements Fitzroy project, bridge scour remediation, 13th Hydraulics in Water Engineering Conference, Sydney. Nov. 13-18, 2017; Engineers Australia, pp. 274-281, 2017.

52-17   Nigel Moon, Russell Merz, Sarah Luu and Daley Clohan, Utilising CFD modelling to conceptualise a novel rock ramp fishway design, 13th Hydraulics in Water Engineering Conference, Sydney, Nov. 13-18, 2017; Engineers Australia, pp. 382-389, 2017.

50-17   B.M. Crookston, R.M. Anderson and B.P. Tullis, Free-flow discharge estimation method for Piano Key weir geometries, Journal of Hydro-environment Research (2017), http://dx.doi.org/10.1016/j.jher.2017.10.003.

48-17   Jian Zhou, Physics of Environmental Flows Interacting with Obstacles, PhD Thesis: Colorado State University, Copyright by Jian Zhou 2017, All Rights Reserved.

46-17   Michael Sturn, Bernhard Gems, Markus Aufleger, Bruno Mazzorana, Maria Papathoma-Köhle and Sven Fuchs, Scale Model Measurements of Impact Forces on Obstacles Induced by Bed-load Transport Processes, Proceedings of the 37th IAHR World Congress August 13 – 18, 2017, Kuala Lumpur, Malaysia.

43-17   Paula Beceiro, Maria do Céu Almeida and Jorge Matos, Numerical modelling of air-water flows in sewer drops, Available Online 28 April 2017, wst2017246; DOI: 10.2166/wst.2017.246

42-17   Arnau Bayon, Juan Pablo Toro,  Fabián A.Bombardelli, Jorge Matose and Petra Amparo López-Jiménez, Influence of VOF technique, turbulence model and discretization scheme on the numerical simulation of the non-aerated, skimming flow in stepped spillways, Journal of Hydro-environment Research, Available online 26 October 2017

40-17   Sturm M, Gems B, Mazzorana B, Gabl R and Aufleger M, Validation of physical and 3D numerical modelling of hydrodynamic flow impacts on objects (Validierung experimenteller und 3-D-numerischer Untersuchungen zur Einwirkung hydrodynamischer Fließprozesse auf Objekte), Bozen-Bolzano Institutional Archive (BIA), ISSN: 0043-0978, https://bia.unibz.it/handle/10863/3893, 2017

38-17   Tsung-Hsien Huang, Chyan-Deng Jan, and Yu-Chao Hsu, Numerical Simulations of Water Surface Profiles and Vortex Structure in a Vortex Settling Basin by using FLOW-3D, Journal of Marine Science and Technology, Vol. 25, No. 5, pp. 531-542 (2017) 531, DOI: 10.6119/JMST-017-0509-1

36-17   Jacob van Alwon, Duncan Borman and Andrew Sleigh, Numerical Modelling of Aerated Flows Over Stepped Spillways, 37th IAHR World Congress, 2017.

35-17   Abolfazl Nazari Giglou, John Alex Mccorquodale and Luca Solari, Numerical study on the effect of the spur dikes on sedimentation pattern, Ain Shams Engineering Journal, Available online 8 March 2017.

33-17   Giovanni De Cesare, Khalid Essyad, Paloma Furlan, Vu Nam Khuong, Sean Mulligan, Experimental study at prototype scale of a self-priming free surface siphon, Congrès SHF : SIMHYDRO 2017, Nice, 14-16 June

32-17   Kathryn Plymesser and Joel Cahoon, Pressure gradients in a steeppass fishway using a computational fluid dynamics model, Ecological Engineering 108 (2017) 277–283.

31-17   M. Ghasemi, S. Soltani-Gerdefaramarzi, The Scour Bridge Simulation around a Cylindrical Pier Using FLOW-3D, Journal of Hydrosciences and Environment 1(2): 2017 46-54

27-17   John Wendelbo and Brian Fox, CFD modeling of Piano Key weirs: validation and numerical parameter space analysis, 2017 Dam Safety, San Antonio, September 10-14, 2017, Copyright © 2017 Association of State Dam Safety Officials, Inc. All Rights Reserved.

26-17   Brian Fox and John Wendelbo, Numerical modeling of Piano Key Weirs using FLOW-3D, USSD Annual Conference, Anaheim, CA, April 3- 7, 2017

25-17   Rasoul Daneshfaraz, Sina Sadeghfam and Ali Ghahramanzadeh, Three-dimensional Numerical Investigation of Flow through Screens as Energy Dissipators, Canadian Journal of Civil Engineering, https://doi.org/10.1139/cjce-2017-0273

23-17   J.M, Duguay, R.W.J. Lacey and J. Gaucher, A case study of a pool and weir fishway modeled with OpenFOAM and FLOW-3D, Ecological Engineering, Volume 103, Part A, June 2017, Pages 31-42

22-17   Hanif Pourshahbaz, Saeed Abbasi and Poorya Taghvaei, Numerical scour modeling around parallel spur dikes in FLOW-3D, https://doi.org/10.5194/dwes-2017-21, Drinking Water Engineering and Science, © Author(s) 2017

21-17   Hamid Mirzaei, Zohreh Heydari and Majid Fazli, The effect of meshing and comparing different models of turbulence in topographic prediction of bed and amplitude of flow around the groin in 90-degree arc with movable bed, Modeling Earth Systems and Environment, pp 1–16, July 2017

13-17   Lan Qi, Hui Chen, Xiao Wang, Wencai Fei and Donghai Liu, Establishment and application of three-dimensional realistic river terrain in the numerical modeling of flow over spillways, Water Science & Technology: Water Supply | in press | 2017.

11-17   Allison, M.A., Yuill, B.T., Meselhe, E.A., Marsh, J.K., Kolker, A.S., Ameen, A.D., Observational and numerical particle tracking to examine sediment dynamics in a Mississippi River delta diversion, Estuarine, Coastal and Shelf Science (2017), doi: 10.1016/j.ecss.2017.06.004.

09-17   Hamid Mirzaei, Zohreh Heydari and Majid Fazli, The effect of meshing and comparing different turbulence models in predicting the topography of bed and flow field in the 90 degree bend with moving bed, M. Model. Earth Syst. Environ. (2017). doi:10.1007/s40808-017-0336-6

03-17   Luis G. Castillo and José M. Carrillo, Comparison of methods to estimate the scour downstream of a ski jump, Civil Engineering Department, Universidad Politécnica de Cartagena, UPCT Paseo Alfonso XIII, 52 – 30203 Cartagena, Spain, International Journal of Multiphase Flow 92 (2017) 171–180.

103-16 Daniel Valero and Rafael Garcia-Bartual, Calibration of an Air Entrainment Model for CFD Spillway Applications, Advances in Hydroinformatics, P. Gourbesville et al. (eds), pp. 571-582, 2016. doi.org/10.1007/978-981-287-615-7_38

97-16   M. Taghavi and H. Ghodousi, A Comparison on Discharge Coefficients of Side and Normal Weirs with Suspended Flow Load using FLOW-3D, Indian Journal of Science and Technology, Vol 9(3), doi.org/10.17485/ijst/2016/v9i3/78537, January 2016.

96-16   Luis G. Castillo and José M. Carrillo, Scour, Velocities and Pressures Evaluations Produced by Spillway and Outlets of DamWater 2016, 8(3), 68; doi.org/10.3390/w8030068.

95-16   Majid Heydari and Alireza KhoshKonesh, The Comparison of the Performance of Prandtl Mixing Length, Turbulence Kinetic Energy, K-e, RNG and LES Turbulence Models in Simulation of the Positive Wave Motion Caused by Dam Break on the Erodible Bed, Indian Journal of Science and Technology, Vol 9(7), 2016. doi.org/10.17485/ijst/2016/v9i7/87856

93-16   Saleh I. Khassaf, Ali N. Attiyah and Hayder A. Al-Yousify, Experimental investigation of compound side weir with modeling using computational fluid dynamic, International Journal of Energy and Environment, Volume 7, Issue 2, 2016 pp.169-178

92-16   Jason Duguay and Jay Lacey, Modeling: OpenFOAM CFD Modeling Case Study of a Pool and Weir Fishway with Implications for Free-Surface Flows, International Conference on Engineering and Ecohydrology for Fish Passage 2016

90-16   Giacomo Viccione, Vittorio Bovolin and Eugenio Pugliese Carratelli, A numerical investigation of liquid impact on planar surfaces, ECCOMAS Congress 2016 VII European Congress on Computational Methods in Applied Sciences and Engineering, Greece, June 2016.

89-16   Giacomo Viccione, A numerical investigation of flow dynamics over a trapezoidal smooth open channel, ECCOMAS Congress 2016 VII European Congress on Computational Methods in Applied Sciences and Engineering, Greece, June 2016.

87-16  Jian Zhou and Subhas K. Venayagamoorthy, Numerical simulations of intrusive gravity currents interacting with a bottom-mounted obstacle in a continuously stratified ambient, Environmental Fluid Mechanics, 17; 191–209, 2016. doi: 10.1007/s10652-016-9454-3

86-16   Charles R. Ortloff, Similitude in Archaeology: Examining Agricultural System Science in PreColumbian Civilizations of Ancient Peru and Bolivia, Hydrol Current Res 7:259. doi: 10.4172/2157-7587.1000259, October 2016.

85-16   Charles R. Ortloff, New Discoveries and Perspectives on Water Management at 300 Bc – Ad 1100 Tiwanaku’s Urban Center (Bolivia), MOJ Civil Eng 1(3): 00014. DOI: 10.15406/mojce.2016.01.00014.

82-16   S. Paudel and N. Saenger, Grid refinement study for three dimensional CFD model involving incompressible free surface flow and rotating object, Computers & Fluids, Volume 143, http://dx.doi.org/10.1016/j.compfluid.2016.10.025, 17 January 2017, Pages 134–140

77-16   José A. Vásquez, Daniel M. Robb, MODELACIÓN CFD DE ROTURA DE PRESAS EN PRESENCIA DE OBSTÁCULOS, XXVII CONGRESO LATINOAMERICANO DE HIDRÁULICA, LIMA, PERÚ, 28 AL 30 DE SETIEMBRE DE 2016.

76-16   José A. Vásquez and Guilherme de Lima, MODELACIÓN CFD DE ONDAS TSUNAMI EN RESERVORIOS, LAGOS Y MINAS CAUSADAS POR DESLIZAMIENTOS DE LADERAS, XXVII CONGRESO LATINOAMERICANO DE HIDRÁULICA, LIMA, PERÚ, 28 AL 30 DE SETIEMBRE DE 2016.

75-16   Bernhard Gems, Bruno Mazzorana, Thomas Hofer, Michael Sturm, Roman Gabl and Markus Aufleger, 3-D hydrodynamic modelling of flood impacts on a building and indoor flooding processes, Nat. Hazards Earth Syst. Sci., 16, 1351-1368, 2016, http://www.nat-hazards-earth-syst-sci.net/16/1351/2016/, doi:10.5194/nhess-16-1351-2016 © Author(s) 2016. This work is distributed under the Creative Commons Attribution 3.0 License.

74-16   Roman Gabl, Jakob Seibl, Manfred Pfeifer, Bernhard Gems and Markus Aufleger, 3D-numerische Modellansätze für die Berechnung von Lawineneinstößen in Speicher (Concepts to simulate avalanche impacts into a reservoir based on 3D-numerics), Österr Wasser- und Abfallw (2016). doi:10.1007/s00506-016-0346-z.

73-16   Sebastian Krzyzagorski, Roman Gabl, Jakob Seibl, Heidi Böttcher and Markus Aufleger, Implementierung eines schräg angeströmten Rechens in die 3D-numerische Berechnung mit FLOW-3D (Implementation of an angled trash rack in the 3D-numerical simulation with FLOW-3D), Österr Wasser- und Abfallw (2016) 68: 146. doi:10.1007/s00506-016-0299-2.

71-16   Khosro Morovati, Afshin Eghbalzadeh and Saba Soori, Numerical Study of Energy Dissipation of Pooled Stepped Spillways, Civil Engineering Journal Vol. 2, No. 5, May, 2016.

66-16   Sooyoung Kim, Seo-hye Choi and Seung Oh Lee, Analysis of Influence for Breach Flow According to Asymmetry of Breach Cross-section, Journal of the Korea Academia-Industrial cooperation Society, Vol. 17, No. 5 pp. 557-565, 2016, http://dx.doi.org/10.5762/KAIS.2016.17.5.557, ISSN 1975-4701 / eISSN 2288-4688.

65-16   Dae-Geun Kim, Analysis of Overflow Characteristics around a Circular-Crested Weir by Using Numerical Model, Journal of Korean Society of Water and Wastewater Vol. 30, No. 2, April 2016.

63-16   Farzad Ferdos and Bijan Dargahi, A study of turbulent flow in largescale porous media at high Reynolds numbers. Part II: flow physics, Journal of Hydraulic Research, 2016, DOI: 10.1080/00221686.2016.1211185.

62-16   Farzad Ferdos and Bijan Dargahi, A study of turbulent flow in largescale porous media at high Reynolds numbers. Part I: numerical validation, Journal of Hydraulic Research, 2016, DOI: 10.1080/00221686.2016.1211184.

60-16   Chia-Lin Chiu, Chia-Ming Fan and Shun-Chung Tsung, Numerical modeling for  periodic oscillation of free overfall in a vertical drop pool, DOI: 10.1061/(ASCE)HY.1943-7900.0001236. © 2016 American Society of Civil Engineers.

54-16   Serife Yurdagul Kumcu, Investigation of Flow Over Spillway Modeling and Comparison between Experimental Data and CFD Analysis, KSCE Journal of Civil Engineering, (0000) 00(0):1-10, Copyright 2016 Korean Society of Civil Engineers, DOI 10.1007/s12205-016-1257-z.

52-16   Gharehbaghi, A., Kaya, B. and Saadatnejadgharahassanlou, Two-Dimensional Bed Variation Models Under Non-equilibrium Conditions in Turbulent Streams, H. Arab J Sci Eng (2016). doi:10.1007/s13369-016-2258-4

48-16   M. Mohsin Munir, Taimoor Ahmed, Javed Munir and Usman Rasheed, Application of Computational Flow Dynamics Analysis for Surge Inception and Propagation for Low Head Hydropower Projects, Proceedings of the Pakistan Academy of Sciences: Pakistan Academy of Sciences, A. Physical and Computational Sciences 53 (2): 177–185 (2016), Copyright © Pakistan Academy of Sciences

46-16   Manuel Gómez, Joan Recasens, Beniamino Russo and Eduardo Martínez-Gomariz, Assessment of inlet efficiency through a 3D simulation: numerical and experimental comparison, wst2016326; DOI: 10.2166/wst.2016.326, August 2016

45-16   Chia-Ying Chang, Frederick N.-F. Chou, Yang-Yih Chen, Yi-Chern Hsieh, Chia-Tzu Chang, Analytical and experimental investigation of hydrodynamic performance and chamber optimization of oscillating water column system, Energy 113 (2016) 597-614

42-16   Bung, D. and Valero, D., Application of the Optical Flow Method to Velocity Determination, In B. Crookston & B. Tullis (Eds.), Hydraulic Structures and Water System Management, 6th IAHR International Symposium on Hydraulic Structures, Portland, OR, 27-30 June 2016, doi:10.15142/T3150628160853 (ISBN 978-1-884575-75-4).

41-16   Valero, D., Bung, D., Crookston, B. and Matos, J., Numerical investigation of USBR type III stilling basin performance downstream of smooth and stepped spillways, In B. Crookston & B. Tullis (Eds.), Hydraulic Structures and Water System Management. 6th IAHR International Symposium on Hydraulic Structures, Portland, OR, 27-30 June 2016, doi:10.15142/T340628160853 (ISBN 978-1-884575-75-4).

40-16   Bruce M. Savage, Brian M. Crookston and Greg S. Paxson, Physical and Numerical Modeling of Large Headwater Ratios for a 15° Labyrinth Spillway, J. Hydraul. Eng., 10.1061/(ASCE)HY.1943-7900.0001186, 04016046.

36-16   Kai-Wen Hsiao, Yu-Chao Hsu, Chyan-Deng Jan, and Yu-Wen Su, Characteristics of Hydraulic Shock Waves in an Inclined Chute Contraction by Using Three Dimensional Numerical Model, Geophysical Research Abstracts, Vol. 18, EGU 2016-11505, 2016, EGU General Assembly 2016, © Author(s) 2016. CC Attribution 3.0 License.

34-16   Dunlop, S., Willig, I., Paul, G., Cabinet Gorge Dam Spillway Modifications for TDG Abatement – Design Evolution and Field Performance, In B. Crookston & B. Tullis (Eds.), Hydraulic Structures and Water System Management. 6th IAHR International Symposium on Hydraulic Structures, Portland, OR, 27-30 June, 2016, doi:10.15142/T3650628160853 (ISBN 978-1-884575-75-4).

33-16   Crispino, G., Dorthe, D., Fuchsmann, T., Gisonni, C., Pfister, M., Junction chamber at vortex drop shaft: case study of Cossonay, In B. Crookston & B. Tullis (Eds.), Hydraulic Structures and Water System Management, 6th IAHR International Symposium on Hydraulic Structures, Portland, OR, 27-30 June 2016, doi:10.15142/T350628160853 (ISBN 978-1-884575-75-4).

32-16  Brown, K., Crookston, B., Investigating Supercritical Flows in Curved Open Channels with Three Dimensional Numerical Modeling, In B. Crookston & B. Tullis (Eds.), Hydraulic Structures and Water System Management, 6th IAHR International Symposium on Hydraulic Structures, Portland, OR, 27-30 June, 2016, doi:10.15142/T3580628160853 (ISBN 978-1-884575-75-4).

31-16  Cicero, G, Influence of some geometrical parameters on Piano Key Weir discharge efficiency,In B. Crookston & B. Tullis (Eds.), Hydraulic Structures and Water System Management, 6th IAHR International Symposium on Hydraulic Structures, Portland, OR, 27-30 June, 2016, doi:10.15142/T3320628160853 (ISBN 978-1-884575-75-4).

28-16   Anthoula Gkesouli, Maria Nitsa, Anastasios I. Stamou, Peter Rutschmann and Minh Duc Bui, Modeling the effect of wind in rectangular settling tanks for water supply, DOI: 10.1080/19443994.2016.1195290, Desalination and Water Treatment, June 22, 2016.

27-16   Eugenio Pugliese Carratelli, Giacomo Viccione and Vittorio Bovolin, Free surface flow impact on a vertical wall: a numerical assessment, Theor. Comput. Fluid Dyn., DOI 10.1007/s00162-016-0386-9, February 2016.

25-16   Daniel Valero and Daniel B. Bung, Sensitivity of turbulent Schmidt number and turbulence model to simulations of jets in crossflow, Environmental Modelling & Software 82 (2016) 218e228.

24-16   Il Won Seo, Young Do Kim, Yong Sung Park and Chang Geun Song, Spillway discharges by modification of weir shapes and overflow surroundings, Environmental Earth Sciences, March 2016, 75:496, 14 March 2016

23-16   Du Han Lee, Myounghwan Kim and Dong Sop Rhee, Evacuation Safety Evaluation of Inundated Stairs Using 3D Numerical Simulation, International Journal of Smart Home Vol. 10, No. 3, (2016), pp.149-158 http://dx.doi.org/10.14257/ijsh.2016.10.3.15

22-16   Arnau Bayon, Daniel Valero, Rafael García-Bartual, Francisco Jose Valles-Moran and Amparo Lopez-Jimenez, Performance assessment of OpenFOAM and FLOW-3D in the numerical modeling of a low Reynolds number hydraulic jump, Environmental Modelling & Software 80 (2016) 322e335.

21-16   Shima Bahadori and Mehdi Behdarvandi Askar, Investigating the Effect of Relative Width on Momentum Transfer between Main Channel and Floodplain in Rough Rectangular Compound Channel Sunder Varius Relative Depth Condition, Open Journal of Geology, 2016, 6, 225-231, Published Online April 2016 in SciRes.

18-16   Ali Ahrari,  Hong Lei, Montassar Aidi Sharif, Kalyanmoy Deb and  Xiaobo Tan, Optimum Design of Artificial Lateral Line Systems for Object Tracking under Uncertain Conditions, COIN Report Number: 2016006

16-16   Elena Battisacco, Giovanni De Cesare and Anton J. Schleiss, Re-establishment of a uniform discharge on the Olympic fountain in Lausanne, Journal of Applied Water Engineering and Research, (2016) DOI: 10.1080/23249676.2016.1163648.

14-16   Shima Bahadori, Mehdi and Behdarvandi Askar, Investigating the Simultaneous Effect of Relative Width and Relative Roughness on Apparent Shear Stress in Symmetric Compound Rectangular Channels, JOURNAL OF CURRENT RESEARCH IN SCIENCE, ISSN 2322-5009 CODEN (USA): JCRSDJ, S (1), 2016: 654-660

12-16   Charles R. Ortloff, Hydraulic Engineering Innovations at 100 BC- AD 300 Nabataean Petra (Jordan), In conference proceedings: De Aquaeductu atque Aqua Urbium Lyciae Pamphyliae Pisidiae. The Legacy of Sextus Julius Frontinus, Antalya, Turkey, G. Wiplinger, ed.  ISBN: 978-90-429-3361-3, 2016 Peeters Publisher, Leuven, Belgium.

11-16 G. Robblee, S. Kees and B.M. Crookston, Schnabel Engineering; and K. Keel, Town of Hillsborough, Ensuring Water Supply Reliability with Innovative PK Weir Spillway Design, 36th USSD Annual Meeting and Conference, Denver, CO, April 11-15, 2016

10-16 Tina Stanard and Victor Vasquez, Freese and Nichols, Inc.; Ruth Haberman, Upper Brushy Creek Water Control and Improvement District; Blake Tullis, Utah State University; and Bruce Savage, Idaho State University, Importance of Site Considerations for Labyrinth Spillway Hydraulic Design — Upper Brushy Creek Dam 7 Modernization, 36th USSD Annual Meeting and Conference, Denver, CO, April 11-15, 2016

09-16 James R. Crowder, Brian M. Crookston, Bradley T. Boyer and J. Tyler Coats, Schnabel Engineering, Cultivating Ingenuity and Safety in Alabama: The Taming of Lake Ogletree Reservoir, 36th USSD Annual Meeting and Conference, Denver, CO, April 11-15, 2016

08-16 Frank Lan, Robert Waddell and Michael Zusi, AECOM; and Brian Grant, Montana DNRC, Replacing Ruby Dam Outlet Uses Computational Fluid Dynamics to Model Energy Dissipation, 36th USSD Annual Meeting and Conference, Denver, CO, April 11-15, 2016

07-16 Elise N. Dombeck, Federal Energy Regulatory Commission, Applications of FLOW-3D for Stability Analyses of Concrete Spillways at FERC Projects, 36th USSD Annual Meeting and Conference, Denver, CO, April 11-15, 2016

06-16   Farhad Ghazizadeh and M. Azhdary Moghaddam, An Experimental and Numerical Comparison of Flow Hydraulic Parameters in Circular Crested Weir Using FLOW-3D, Civil Engineering Journal Vol. 2, No. 1, January, 2016

05-16   Sadegh Dehdar-behbahani and Abbas Parsaie, Numerical modeling of flow pattern in dam spillway’s guide wall. Case study: Balaroud dam, Iran, doi:10.1016/j.aej.2016.01.006, February 2016.

04-16   Oscar Herrera-Granados and Stanisław W. Kostecki, Numerical and physical modeling of water flow over the ogee weir of the new Niedów barrage, DOI: 10.1515/johh-2016-0013, J. Hydrol. Hydromech., 64, 2016, 1, 67–74

03-16   B. Gems, B. Mazzorana, T. Hofer, M. Sturm, R. Gabl, M. Aufleger, 3D-hydrodynamic modelling of flood impacts on a building and indoor flooding processes, Nat. Hazards Earth Syst. Sci. Discuss., doi:10.5194/nhess-2015-326, 2016, Manuscript under review for journal Nat. Hazards Earth Syst. Sci., Published: 19 January 2016 © Author(s) 2016. CC-BY 3.0 License.

124-15 Yousef Sangsefidi, Mojtaba Mehraein, and Masoud Ghodsian, Numerical simulation of flow over labyrinth spillways, Scientia Iranica, Transaction A, 22(5), 1779–1787, 2015.

120-15   Du Han Lee, Myounghwan Kim and Dong Sop Rhee, Analysis of Critical Evacuation Condition on Inundated Stairs Using Numerical Simulation, Advanced Science and Technology Letters Vol.120 (GST 2015), pp.522-525 http://dx.doi.org/10.14257/astl.2015.120.104

119-15  Shiqiang Ye and Paul Toth, Bank Erosion Control at Frederickhouse Dam, Ontario, CDA 2015 Annual Conference, Congrès annuel 2015 de l’ACB, Mississauga, ON, Canada, 2015 Oct 5-8

118-15  D.M. Robb and J.A. Vasquez, Numerical simulation of dam-break flows using depth-averaged hydrodynamic and three-dimensional CFD models, 22nd Canadian Hydrotechnical Conference, Montreal, Quebec, April 29 – May 2, 2015

117-15 Ashkan. Reisi, Parastoo. Salah, and Mohamad Reza. Kavianpour, Impact of Chute Walls Convergence Angle on Flow Characteristics of Spillways using Numerical Modeling, International Journal of Chemical, Environmental & Biological Sciences (IJCEBS), Volume 3, Issue 3 (2015) ISSN 2320–4087 (Online)

115-15  Ivana Vouk, Field and Numerical Investigation of Mixing and Transport of Ammonia in the Ottawa River, Master’s Thesis: Department of Civil Engineering, University of Ottawa, August 2015, © Ivana Vouk, Canada 2016.

113-15   J. Amblard, C. Pams Capoccioni, D. Nivon, L. Mellal, G. De Cesare, T. Ghilardi, M. Jafarnejad and E. Battisacco, Analysis of Ballast Transport in the Event of Overflowing of the Drainage System on High Speed Lines, International Journal of Railway Technology, Volume 4, 2015. doi:10.4203/ijr, t.4.xx.xx , ©Saxe-Coburg Publications, 2015

111-15   Y. Oukid, V. Libaud and C. Daux, 3D CFD modelling of spillways -Practical feedback on capabilities and challenges, Hydropower & Dams Issue Six, 2015

110-15  Zhiyong Zhang and Yuanping Yang, Numerical Study on Onset Condition of Scour Below Offshore Pipeline Under Reversing Tidal Flow, © EJGE, Vol. 20 [2015], Bund. 25

109-15  He Baohua, Numerical Simulation Analysis of Karst Tunnel Water Bursting Movement, © EJGE, Vol. 20 [2015], Bund. 25

105-15   Ali Yıldız and A. İhsan Martı, Comparison of Experimental Study and CFD Analysis of the Flow Under a Sluice Gate, Proceedings of International Conference on Structural Architectural and Civil Engineering Held on 21-22, Nov, 2015, in Dubai, ISBN:9788193137321

104-15  Yehui Zhu and Liquan Xie, Numerical Analysis of Flow Effects on Water Interface over a Submarine Pipeline, Resources, Environment and Engineering II: Proceedings of the 2nd Technical Congress on Resources, Environment and Engineering (CREE 2015, Hong Kong, 25-26 September 2015), Edited by Liquan Xie, CRC Press 2015, Pages 99–104, DOI: 10.1201/b19136-16.

100-15  Yizhou Xiao, Wene Wang, Xiaotao Hu, and Yan Zhou, Experimental and numerical research on portable short-throat flume in the field, Flow Measurement and Instrumentation, doi:10.1016/j.flowmeasinst.2015.11.003, Available online December 8, 2015

99-15   Mehdi Taghavi and Hesam Ghodousi, Simulation of Flow Suspended Load in Weirs by Using FLOW-3D Model, Civil Engineering Journal Vol. 1, No. 1, November 2015

98-15   Azin Movahedi, Ali Delavari and Massoud Farahi, Designing Manhole in Water Transmission Lines Using FLOW-3D Numerical Model, Civil Engineering Journal Vol. 1, No. 1, November 2015

97-15   R. Gabl, J. Seibl, B. Gems, and M. Aufleger, 3-D numerical approach to simulate the overtopping volume caused by an impulse wave comparable to avalanche impact in a reservoir, Nat. Hazards Earth Syst. Sci., 15, 2617-2630, doi:10.5194/nhess-15-2617-2015, 2015.

94-15   Jason Matthew Duguay and Jay Lacey, Numerical Study of an Innovative Fish Ladder Design for Perched Culverts, Canadian Journal of Civil Engineering, 10.1139/cjce-2014-0436, November 2015

92-15   H. A. Hussein, R. Abdulla and  M. A. Md Said, Computational Investigation of Inlet Baffle Height on the Flow in a Rectangular Oil/Water Separator Tanks, Applied Mechanics and Materials, Vol. 802, pp. 587-592, Oct. 2015

91-15   Mahmoud Mohammad Rezapour Tabari and Shiva Tavakoli, Effects of Stepped Spillway Geometry on Flow Pattern and Energy DissipationArabian Journal for Science and Engineering, October 2015

87-15   Erin R. Ryan, Effects of Hydraulic Structures on Fish Passage – An Evaluation of 2D vs 3D Hydraulic Analysis Methods, Master’s Thesis: Civil and Environmental Engineering, Colorado State University, Summer 2015, Copyright by Erin Rose Ryan 2015

79-15   Ana L. Quaresma, Is CFD an efficient tool to develop pool type fishways? International Conference on Engineering and Ecohydrology for Fish Passage. Paper 20, June 24, 2015

78-15   Amir Alavi, Don Murray, Claude Chartrand and Derek McCoy, CFD Modeling Provides Value Engineering, Hydro Review, October 2015

75-15   Rebekka Czerny, Classification of flow patterns in a nature-oriented fishway based on 3D hydraulic simulation results, International Conference on Engineering and Ecohydrology for Fish Passage. Paper 39, June 22, 2015

73-15   Frank Seidel, Hybrid model approach for designing fish ways – example fish lift system at Baldeney/Ruhr and fishway at Geesthacht /Elbet, International Conference on Engineering and Ecohydrology for Fish Passage 2015

72-15   G. Guyot, B. Huber, and A. Pittion-Rossillon, Assessment of a numerical method to forecast vortices with a scaled model, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

71-15   Abbas Parsaie, Amir Hamzeh Haghiabi and Amir Moradinejad, CFD modeling of flow pattern in spillway’s approach channel, Sustainable Water Resources Management, September 2015, Volume 1, Issue 3, pp 245-251

70-15   T. Liepert, A. Kuhlmann, G. Haimer, M.D. Bui and P. Rutschmann, Optimization of Fish Pass Entrance Location at a Hydropower Plant Considering Site-Specific Constraints, Proceedings of the 14th International Conference on Environmental Science and Technology, Rhodes, Greece, 3-5 September 2015

67-15   Alkistis Stergiopoulou and Efrossini Kalkani, Towards a first CFD study of modern horizontal axis Archimedean water current turbines, Volume: 02 Issue: 04, ISO 9001:2008 Certified Journal © 2015, IRJET, July 2015

66-15   Won Choi, Jeongbae Jeon, Jinseon Park, Jeong Jae Lee and Seongsoo Yoon, System reliability analysis of downstream spillways based on collapse of upstream spillways, Int J Agric & Biol Eng, 2015; 8(4): 140-150.

64-15   Szu-Hsien Peng and Chuan Tang, Development and Application of Two-Dimensional Numerical Model on Shallow Water Flows Using Finite Volume Method, Journal of Applied Mathematics and Physics, 2015, 3, 989-996, Published Online August 2015 in SciRes. http://www.scirp.org/journal/jamp, http://dx.doi.org/10.4236/jamp.2015.38121

62-15   Cuneyt Yavuz, Ali Ersin Dincer, Kutay Yilmaz and Samet Dursun, Head Loss Estimation of Water Jets from Flip Bucket of Cakmak-1 Diversion Weir and HEPP, RESEARCH GATE, August 2015 DOI: 10.13140/RG.2.1.3650.5440

54-15   Guo-bin Xu, Li-na Zhao, and Chih Ted Yang, Derivation and verification of minimum energy dissipation rate principle of fluid based on minimum entropy production rate principle, International Journal of Sediment Research, August 2015

50-15   Vafa Khoolosi, Sedat Kabdaşli, and Sevda Farrokhpour, Modeling and Comparison of Water Waves Caused by Landslides into Reservoirs, Watershed Management 2015 © ASCE 2015.

48-15   Mohammad Rostami and Maaroof Siosemarde, Human Life Saving by Simulation of Dam Break using FLOW-3D (A Case Study: Upper Gotvand Dam), www.sciencejournal.in, Volume- 4 Issue- 3 (2015) ISSN: 2319–4731 (p); 2319–5037 (e) © 2015 DAMA International. All rights reserved.

47-15   E. Kolden, B. D. Fox, B. P. Bledsoe and M. C. Kondratieff, Modelling Whitewater Park Hydraulics and Fish Habitat in Colorado, River Res. Applic., doi: 10.1002/rra.2931, 2015

43-15   Firouz Ghasemzadeh, Behzad Parsa, and Mojtaba Noury, Numerical Study of Overflow Capacity of Spillways, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

42-15   Mario Oertel, Numerical Modeling of Free-Surface Flows in Practical Applications, Chapter 8 in Rivers – Physical, Fluvial and Environmental Processes (GeoPlanet: Earth and Planetary Sciences), by Pawel Rowiński and Artur Radecki-Pawlik, July 2, 2015

39-15   R. Gabl, J. Seibl, B. Gems, and M. Aufleger, 3-D-numerical approach to simulate an avalanche impact into a reservoir, Nat. Hazards Earth Syst. Sci. Discuss., 3, 4121–4157, 2015, www.nat-hazards-earth-syst-sci-discuss.net/3/4121/2015/, doi:10.5194/nhessd-3-4121-2015, © Author(s) 2015. CC Attribution 3.0 License.

37-15   Mario Oertel, Discharge Coefficients of Piano Key Weirs from Experimental and Numerical Models, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

36-15   Jessica Klein and Mario Oertel, Comparison between Crossbar Block Ramp and Vertical Slot Fish Pass via Numerical 3D CFD Simulation, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

35-15   Mario Oertel, Jan P. Balmes and Daniel B. Bung, Numerical Simulation of Erosion Processes on Crossbar Block Ramps, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

33-15   Daniel Valero and Daniel B. Bung, Hybrid Investigation of Air Transport Processes in Moderately Sloped Stepped Spillway Flows, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

32-15   Deniz Velioglu, Nuray Denli Tokyay, and Ali Ersin Dincer, A Numerical and Experimental Study on the Characteristics of Hydraulic Jumps on Rough Beds, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

31-15   J.C.C. Amorim, R.C.R. Amante, and V.D. Barbosa, Experimental and Numerical Modeling of Flow in a Stilling Basin, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

30-15   Luna B.J. César, Salas V. Christian, Gracia S. Jesús, and Ortiz M. Victor, Comparative Analysis of the Modification of Turbulence and Its Effects on a Trapezoidal Section Stilling Basin, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

27-15   L. Castillo, J. Carrillo, and M. Álvarez, Complementary Methods for Determining the Sedimentation and Flushing in a Reservoir, J. Hydraul. Eng., 10.1061/(ASCE)HY.1943-7900.0001050 , 05015004, 2015.

22-15   Mohammad Vaghefi, Mohammad Shakerdargah and Maryam Akbari, Numerical investigation of the effect of Froude number on flow pattern around a submerged T-shaped spur dike in a 90º bend, © Turkish Journal of Engineering & Environmental Sciences, 03.04.2015, doi:10.3906/muh-1405-2

18-15   S. Michael Scurlock, Amanda L. Cox, Drew C. Baird, Christopher I. Thornton and Steven R. Abt, Hybrid Modeling of River Training Structures in Sinuous Channels, SEDHYD 2015, Joint 10th Federal Interagency Sedimentation Conference, 5th Federal Interagency Hydrologic Modeling Conference, April 19-23, 2015, Reno, Nevada

13-15   Selahattin Kocaman and Hatice Ozmen-Cagatay, Investigation of dam-break induced shock waves impact on a vertical wall, Journal of Hydrology (2015), doi: http://dx.doi.org/10.1016/j.jhydrol.2015.03.040.

12-15   Nguyen Cong Thanh and Wang Ling-Ling, Physical and Numerical Model of Flow through the Spillways with a Breast Wall, KSCE Journal of Civil Engineering (0000) 00(0):1-8, Copyright 2015 Korean Society of Civil Engineers, DOI 10.1007/s12205-015-0742-0, April 10, 2015.

10-15   Yueping Yin, Bolin Huang, Guangning Liu and Shichang Wang, Potential risk analysis on a Jianchuandong dangerous rockmass-generated impulse wave in the Three Gorges Reservoir, China, Environ Earth Sci, DOI 10.1007/s12665-015-4278-x, © Springer-Verlag Berlin Heidelberg 2015

08-15   Yue-ping Yin, Bolin Huang, Xiaoting Chen, Guangning Liu and Shichang Wang, Numerical analysis on wave generated by the Qianjiangping landslide in Three Gorges Reservoir, China, 10.1007/s10346-015-0564-7, © Springer-Verlag Berlin Heidelberg 2015

07-15   M. Vaghefi, A. Ahmadi and B. Faraji, The Effect of Support Structure on Flow Patterns Around T-Shape Spur Dike in 90° Bend Channel, Arabian Journal for Science and Engineering, February 2015,

06-15   Sajjad Mohammadpour Zalaki, Hosein Fathian, Ebrahim Zalaghi and Farhad Kalantar Hormozi, Investigation of hydraulic parameters and cavitation in Kheir Abad flood release structure, Canadian Journal of Civil Engineering, February 2015

04-15  Der-Chang Lo, Jin-Shuen Liou, and Shyy Woei Chang, Hydrodynamic Performances of Air-Water Flows in Gullies with and without Swirl Generation Vanes for Drainage Systems of Buildings, Water 2015, 7(2), 679-696; doi:10.3390/w7020679

01-15   William Daley Clohan, Three-Dimensional Numerical Simulations of Subaerial Landslide Generated Waves, Master’s Thesis: Civil Engineering, The University of British Columbia (Vancouver), January 2015 © William Daley Clohan, 2015. Available upon request.

136-14   Charles R. Ortloff, Hydraulic Engineering in 300 BCE- CE 300 Petra (Jordan), Encyclopedia of Ancient Science, Technology and Medicine in Nonwestern Cultures, Springer Publishing, Berlin Germany, 2014.

135-14   Charles R. Ortloff, Land, Labor, Water and Technology in Precolumbian South America, Encyclopedia of Ancient Science, Technology and Medicine in Nonwestern Cultures, Springer Publishing, Berlin Germany, 2014.

134-14   Charles R. Ortloff, Hydrologic Engineering of the 300 BCE- CE 1100 Precolumbian Tiwanaku State (Bolivia), Encyclopedia of Ancient Science, Technology and Medicine in Nonwestern Cultures, Springer Publishing, Berlin Germany, 2014.

133-14   Charles R. Ortloff, Water engineering at Petra (Jordan): Recreating the decision process underlying hydraulic engineering of the Wadi Mataha pipeline system, Journal of Archaeological Science, April 2014. 44. 91–97. 10.1016/j.jas.2014.01.015.

132-14   Charles R. Ortloff, Hydraulic Engineering in Ancient Peru and Bolivia, Encyclopedia of Ancient Science, Technology and Medicine in Nonwestern Cultures, Springer Publishing, Berlin Germany, 2014.

131-14    Charles R. Ortloff, Water Management in Ancient Peru, Living Reference Work Entry, Encyclopedia of Ancient Science, Technology and Medicine in Nonwestern Cultures, Springer Publishing, Berlin Germany, 2014.

130-14  Kordula Schwarzwälder and Peter Rutschmann, Sampling bacteria with a laser, Geophysical Research Abstracts Vol. 16, EGU2014-15144, 2014 EGU General Assembly 2014 © Author(s) 2014. CC Attribution 3.0 License.

129-14   Kordula Schwarzwälder, Eve Walters and Peter Rutschmann, Bacteria fate and transport in a river, Geophysical Research Abstracts Vol. 16, EGU2014-14022, 2014 EGU General Assembly 2014 © Author(s) 2014. CC Attribution 3.0 License.

127-14   Charles R. Ortloff, Hydraulic Engineering in Petra, Living Reference Work Entry, Encyclopedia of the History of Science, Technology, and Medicine in Non-Western Cultures, pp 1-13, 03 July 2014

124-14  G. Wei. M. Grünzner and F. Semler, Combination of 2D shallow water and full 3D numerical modeling for sediment transport in reservoirs and basins, Reservoir Sedimentation – Schleiss et al. (Eds) © 2014 Taylor & Francis Group, London, ISBN 978-1-138-02675-9.

121-14    A. Bayón-Barrachina, D. Valero, F. Vallès-Morán, and P.A. López-Jiménez, Comparison of CFD Models for Multiphase Flow Evolution in Bridge Scour Processes, 5th International Junior Researcher and Engineer Workshop on Hydraulic Structures, Spa, Belgium, 28-30 August 2014

120-14  D. Valero, R. García-Bartual and J. Marco, Optimisation of Stilling Basin Chute Blocks Using a Calibrated Multiphase RANS Model, 5th International Junior Researcher and Engineer Workshop on Hydraulic Structures, Spa, Belgium, 28-30 August 2014

119-14   R. Gabl, B. Gems, M. Plörer, R. Klar, T. Gschnitzer, S. Achleitner, and M. Aufleger, Numerical Simulations in Hydraulic Engineering, Computational Engineering, 2014, pp 195-224, April 2014

118-14  Kerilyn Ambrosini, Analysis of Flap Gate Design and Implementations for Water Delivery Systems in California and Nevada, BioResource and Agricultural Engineering, BioResource and Agricultural Engineering Department, California Polytechnic State University, San Luis Obispo, 2014

117-14  Amir Moradinejad, Abas Parssai, Mohamad Noriemamzade, Numerical Modeling of Flow Pattern In Kamal Saleh Dam Spillway Approach Channel, App. Sci. Report.10 (2), 2014: 82-89, © PSCI Publications

116-14  Luis G. Castillo and José M. Carrillo, Characterization of the Dynamic Actions and Scour Estimation Downstream of a Dam, 1st International Seminar on Dam Protection against Overtopping and Accidental Leakage, M.Á. Toledo, R. Morán, E. Oñate (Eds), Madrid, 24-25 November 2014

115-14  Luis G. Castillo, José M. Carrillo, Juan T. García, Antonio Vigueras-Rodríguez, Numerical Simulations and Laboratory Measurements in Hydraulic Jumps, 11th International Conference on Hydroinformatics, HIC 2014, New York City, USA

114-14  Du Han Lee, Young Joo Kim, and Samhee Lee, Numerical modeling of bed form induced hyporheic exchangePaddy and Water Environment, August 2014, Volume 12, Issue 1 Supplement, pp 89-97

112-14  Ed Zapel, Hank Nelson, Brian Hughes, Steve Fry, Options for Reducing Total Dissolved Gas at the Long Lake Hydroelectric Facility, Hydrovision International, July 22-24, 2014, Nashville, TN

111-14  Jason Duguay, Jay Lace, Dave Penny and Ken Hannaford, Evolution of an Innovative Fish Ladder Design to Address Issues of Perched Culverts, 2014 Conference of the Transportation Association of Canada, Montreal, Quebec

106-14   Manuel Gomez and Eduardo Martinez, 1D, 2D and 3D Modeling of a PAC-UPC Laboratory Canal Bend, SimHydro 2014: Modelling of rapid transitory flows, 11-13 June 2014, Sophia Antipolis

105-14 Jason Duguay and Jay Lacey, Numerical Validation of an Innovative Fish Baffle Design in Response to Fish Passage Issues at Perched Culverts, CSPI Technical Bulletin, January 14, 2014

104-14  Di Ning, Di,  A Computational Study on Hydraulic Jumps, including Air Entrainment, Master’s Thesis: Civil and Environmental Engineering, University of California, Davis, 2014, 1569799, Copyright ProQuest, UMI Dissertations Publishing 2014

103-14  S. M. Sayah, S. Bonanni, Ph. Heller, and M. Volpato, Physical and Numerical Modelling of Cerro del Águila Dam -Hydraulic and Sedimentation, DOI: 10.13140/2.1.5042.1122 Conference: Hydro 2014

102-14   Khosrow Hosseini, Shahab Rikhtegar, Hojat Karami, Keivan Bina, Application of Numerical Modeling to Assess Geometry Effect of Racks on Performance of Bottom Intakes, Arabian Journal for Science and Engineering, December 2014

98-14  Aysel Duru, Numerical Modelling of Contracted Sharp Crested Weirs, Master’s Thesis: The Graduate School of Natural and Applied Sciences of Middle East Technical University, November 2014

97-14  M Angulo, S Liscia, A Lopez and C Lucino, Experimental validation of a low-head turbine intake designed by CFD following Fisher and Franke guidelines, 27th IAHR Symposium on Hydraulic Machinery and Systems (IAHR 2014), IOP Publishing, IOP Conf. Series: Earth and Environmental Science 22 (2013) 042014 doi:10.1088/1755-1315/22/4/042014

94-14   Hamidreza Babaali, Abolfazl Shamsai, and Hamidreza Vosoughifar, Computational Modeling of the Hydraulic Jump in the Stilling Basin with ConvergenceWalls Using CFD Codes, Arab J Sci Eng, DOI 10.1007/s13369-014-1466-z, October 2014

93-14   A.J. Vellinga, M.J.B. Cartigny, J.T. Eggenhuisen, E.W.M. Hansen, and R. Rouzairol, Morphodynamics of supercritical-flow bedforms using depth-resolved computational fluid dynamics model, International Association of Sedimentologists, Geneva, 2014.

88-14   Marcelo A. Somos-Valenzuela, Rachel E. Chisolm, Daene C. McKinney, and Denny Rivas, Inundation Modeling of a Potential Glacial Lake Outburst Flood in Huaraz, Peru, CRWR Online Report 14-01, March 2014

84-14   Hossein Shahheydari, Ehsan Jafari Nodoshan, Reza Barati, and Mehdi Azhdary Moghadam, Discharge coefficient and energy dissipation over stepped spillway under skimming flow regimeKSCE Journal of Civil Engineering, 10.1007/s12205-013-0749-3, November 2014

81-14   Gaël Epely-Chauvin, Giovanni De Cesare and Sebastian Schwindt, Numerical Modelling of Plunge Pool Scour Evolution in Non-Cohesive Sediments, Engineering Applications of Computational Fluid Mechanics Vol. 8, No. 4, pp. 477–487 (2014).

79-14   Liquan Xie, Yanhui Xu, and Wenrui Huang, Numerical Study on Hydrodynamic Mechanism of Sediment Trapping by Geotextile Mattress with Sloping Curtain (GMSC), Proceedings of the Eleventh (2014) Pacific/Asia Offshore Mechanics Symposium Shanghai, China, October 12-16, 2014 Copyright © 2014 by The International Society of Offshore and Polar Engineers, ISBN 978–1 880653 90-6: ISSN 1946-004X.

78-14  D. N. Powell and A. A. Khan, Flow Field Upstream of an Orifice under Fixed Bed and Equilibrium Scour ConditionsJ. Hydraul. Eng., 10.1061/(ASCE)HY.1943-7900.0000960, 04014076, 2014.

76-14   Berk Sezenöz, Numerical Modelling of Continuous Transverse Grates for Hydraulic Efficiency, Master’s Thesis: The Graduate School of Natural and Applied Sciences of Middle East Technical University, October 2014

75-14   Francesco Calomino and Agostino Lauria, 3-D Underflow of a Sluice Gate at a Channel Inlet; Experimental Results and CFD Simulations, Journal of Civil Engineering and Urbanism, Volume 4, Issue 5: 501-508 (2014)

73-14   Som Dutta, Talia E. Tokyay, Yovanni A. Cataño-Lopera, Sergio Serafinod and Marcelo H. Garcia, Application of computational fluid dynamic modeling to improve flow and grit transport in Terence J. O’Brien Water Reclamation Plant, Chicago, Illinois, Journal of Hydraulic Research, DOI: 10.1080/00221686.2014.949883, October 2014

72-14   Ali Heidari, Poria Ghassemi, Evaluation of step’s slope on energy dissipation in stepped spillway, International Journal of Engineering & Technology, 3 (4) (2014) 501-505, ©Science Publishing Corporation, www.sciencepubco.com/index.php/IJET, doi: 10.14419/ijet.v3i4.3561

70-14   M. Tabatabai, M. Heidarnejad, A. Bordbar, Numerical Study of Flow Patterns in Stilling Basin with Sinusoidal Bed using FLOW-3D Model, Advances in Environmental Biology, 8(13) August 2014, Pages: 787-792

66-14   John S. Schwartz, Keil J. Neff, Frank E. Dworak, Robert R. Woockman, Restoring riffle-pool structure in an incised, straightened urban stream channel using an ecohydraulic modeling approach, Ecol. Eng. (2014), doi.org/10.1016/j.ecoleng.2014.06.002

65-14  Laura Rozumalski and Michael Fullarton, CFD Modeling to Design a Fish Lift Entrance, Hydro Review, July 2014

64-14   Pam Waterman, Scaled for Success: Computational Fluid Dynamics Analysis Prompts Swift Stormwater System Improvements in Indianapolis, WaterWorld, August 2014.

63-14   Markus Grünzner and Peter Rutschmann, Large Eddy Simulation  – Ein Beitrag zur Auflösung turbulenter Strömungsstrukturen in technischen Fischaufstiegshilfen; (LES – resolving turbulent flow in technical fish bypasses), Tagungsband Internationales Symposium in Zurich, Wasser- und Flussbau im Alpenraum, Versuchsanstalt fur Wasserbau, Hydrologie und Glaziologie, ETH Zurich. In German.

62-14   Jason Duguay, Jay Lace, Dave Penny, and Ken Hannaford, Evolution of an Innovative Fish Ladder Design to Address Issues of Perched Culverts, 2014 Conference of the Transportation Association of Canada, Montreal, Quebec

60-14   Kordula Schwarzwälder, Minh Duc Bui, and Peter Rutschmann, Simulation of bacteria transport processes in a river with FLOW-3D, Geophysical Research Abstracts, Vol. 16, EGU2014-12993, 2014, EGU General Assembly 2014, © Author(s) 2014. CC Attribution 3.0 License.

58-14   Eray Usta, Numercial Investigation of Hydraulic Characteristics of Laleili Dam Spillway and Comparison with Physical Model Study, Master’s Thesis: The Graduate School of Natural and Applied Sciences of Middle East Technical University, May 2014

57-14   Selahattin Kocaman, Prediction of Backwater Profiles due to Bridges in a Compound Channel Using CFD, Hindawi Publishing Corporation, Advances in Mechanical Engineering, Volume 2014, Article ID 905217, 9 pages, http://dx.doi.org/10.1155/2014/905217

54-14   Ines C. Meireles, Fabian A. Bombardelli, and Jorge Matos, Air entrainment onset in skimming flows on steep stepped spillways: an analysis, (2014) Journal of Hydraulic Research, 52:3, 375-385, DOI: 10.1080/00221686.2013.878401

53-14   Charles R Ortloff, Groundwater Management in the 300 bce-1100ce Pre-Columbian City of Tiwanaku (Bolivia), Hydrol Current Res 5: 168. doi:10.4172/2157-7587.1000168, 2014

50-14   Mohanad A. Kholdier, Weir-Baffled Culvert Hydrodynamics Evaluation for Fish Passage using Particle Image Velocimetry and Computational Fluid Dynamic Techniques, Ph.D. Thesis: Utah State University (2014). All Graduate Theses and Dissertations. Paper 3078. http://digitalcommons.usu.edu/etd/3078

48-14   Yu-Heng Lin, Study on raceway pond for microalgae culturing system, Master Thesis: Department of Marine Environment and Engineering, National Sun Yat-sen University, August 2014. In Chinese

38-14   David Ingram, Robin Wallacey, Adam Robinsonz and Ian Bryden, The design and commissioning of the first, circular, combined current and wave test basin, Proceedings of Oceans 2014 MTS/IEEE, Taipei, Taiwan, IEEE, April 2014

36-14   Charles R. Ortloff, Hydraulic Engineering in Precolumbian Peru and Bolivia, The Encyclopedia of the History of Science, Technology and Medicine in Non-Western Cultures, Springer-Verlag, Volumes II and III, Heidelberg, Germany, 2014.

35-14   Charles R. Ortloff, Hydraulic Engineering in BC 100- AD 300 Petra (Jordan), The Encyclopedia of the History of Science, Technology and Medicine in Non-Western Cultures, Springer-Verlag, Volumes II and III, Heidelberg, Germany, 2014.

34-14   Charles R. Ortloff, Hydraulic Engineering in Precolumbian Peru and Bolivia, The Encyclopedia of the History of Science, Technology and Medicine in Non-Western Cultures, Springer-Verlag, Volumes II and III, Heidelberg, Germany, 2014.

33-14   Roman Gabl, Bernhard Gems, Giovanni De Cesare, and Markus Aufleger, Contribution to Quality Standards for 3D-Numerical Simulations with FLOW-3D, Wasserwirtschaft (ISSN: 0043-0978), vol. 104, num. 3, p. 15-20, Wiesbaden: Springer Vieweg-Springer Fachmedien Wiesbaden Gmbh, 2014. Available for download at the University of Innsbruck. In German.

31-14   E. Fadaei-Kermani and G.A. Barani, Numerical simulation of flow over spillway based on the CFD method, Scientia Iranica A, 21(1), 91-97, 2014

30-14   Luis G. Castillo  and José M. Carrillo, Scour Analysis Downstream of Paute-Cardenillo Dam, © 3rd IAHR Europe Congress, Book of Proceedings, 2014, Porto, Portugal.

29-14    L. G. Castillo, M. A. Álvarez, and J. M. Carrillo, Numerical modeling of sedimentation and flushing at the Paute-Cardenillo Reservoir, ASCE-EWRI. International Perspective on Water Resources and Environment Quito, January 8-10, 2014

28-14   L. G. Castillo and J. M. CarrilloScour estimation of the Paute-Cardenillo Dam, ASCE-EWRI. International Perspective on Water Resources and Environment Quito, January 8-10, 2014.

27-14   Luis G. Castillo, Manual A. Álvarez and José M. Carrillo, Analysis of Sedimentation and Flushing into the Reservoir Paute-Cardenillo© 3rd IAHR Europe Congress, Book of Proceedings, 2014, Porto, Portugal.

24-14   Carter R. Newell and John Richardson, The Effects of Ambient and Aquaculture Structure Hydrodynamics on the Food Supply and Demand of Mussel Rafts, Journal of Shellfish Research, 33(1):257-272, DOI: http://dx.doi.org/10.2983/035.033.0125, 0125, 2014.

16-14   Han Hu, Jiesheng Huang, Zhongdong Qian, Wenxin Huai, and Genjian Yu, Hydraulic Analysis of Parabolic Flume for Flow Measurement, Flow Measurement and Instrumentation, http://dx.doi.org/10.1016/j.flowmeasinst.2014.03.002, 2014.

14-14   Seung Oh Lee, Sooyoung Kim, Moonil Kim, Kyoung Jae Lim and Younghun Jung, The Effect of Hydraulic Characteristics on Algal Bloom in an Artificial Seawater Canal: A Case Study in Songdo City, South Korea, Water 2014, 6, 399-413; doi:10.3390/w6020399, ISSN 2073-4441, www.mdpi.com/journal/water

13-14   Kathryn Elizabeth Plymesser, Modeling Fish Passage and Energy Expenditure for American Shad in a Steeppass Fishway using Computational Fluid Dynamics, Ph.D. Thesis: Montana State University, January 2014, © Kathryn Elizabeth Plymesser, 2014, All Rights Reserved.

12-14   Sangdo An and Pierre Y. Julien, Three-Dimensional Modeling of Turbid Density Currents in Imha Reservoir, J. Hydraul. Eng., 10.1061/(ASCE)HY.1943-7900.0000851, 05014004, 2014.

09-14   B. Gems, M. Wörndl, R. Gabl, C. Weber, and M. Aufleger, Experimental and numerical study on the design of a deposition basin outlet structure at a mountain debris cone, Nat. Hazards Earth Syst. Sci., 14, 175–187, 2014, www.nat-hazards-earth-syst-sci.net/14/175/2014/, doi:10.5194/nhess-14-175-2014, © Author(s) 2014. CC Attribution 3.0 License.

07-14   Charles R. Ortloff, Water Engineering at Petra (Jordan): Recreating the Decision Process underlying Hydraulic Engineering of the Wadi Mataha Pipeline System, Journal of Archaeological Science, Available online January 2014.

06-14   Hatice Ozmen-Cagatay, Selahattin Kocaman, Hasan Guzel, Investigation of dam-break flood waves in a dry channel with a hump, Journal of Hydro-environment Research, Available online January 2014.

05-14   Shawn P. Clark, Jonathan Scott Toews, and Rob Tkach, Beyond average velocity: Modeling velocity distributions in partially-filled culverts to support fish passage guidelines, International Journal of River Basin Management, DOI10.1080/15715124.2013.879591, January 2014.

04-14   Giovanni De Cesare, Martin Bieri, Stéphane Terrier, Sylvain Candolfi, Martin Wickenhäuser and Gaël Micoulet, Optimization of a Shared Tailrace Channel of Two Pumped-Storage Plants by Physical and Numerical Modeling, Advances in Hydroinformatics Springer Hydrogeology 2014, pp 291-305.

03-14   Grégory Guyot, Hela Maaloul and Antoine Archer, A Vortex Modeling with 3D CFD, Advances in Hydroinformatics Springer Hydrogeology 2014, pp 433-444.

02-14   Géraldine Milési and Stéphane Causse, 3D Numerical Modeling of a Side-Channel Spillway, Advances in Hydroinformatics Springer Hydrogeology 2014, pp 487-498.

01-14   Mohammad R. Namaee, Mohammad Rostami, S. Jalaledini and Mahdi Habibi, A 3-Dimensional Numerical Simulation of Flow Over a Broad-Crested Side Weir, Advances in Hydroinformatics, Springer Hydrogeology 2014, pp 511-523.

104-13   Alireza Nowroozpour, H. Musavi Jahromi and A. Dastgheib, Studying different cases of wedge shape deflectors on energy dissipation in flip bucket using CFD model, Proceedings, 6th International Perspective on Water Resources & the Environment Conference (IPWE), Izmir, Turkey, January 7-9, 2013.

102-13   Shari Dunlop, Isaac Willig and Roger L. Kay, Emergency Response to Erosion at Fort Peck Spillway: Hydraulic Analysis and Design, ICOLD 2013 International Symposium, Seattle, WA.

101-13   Taeho Kang and Heebeom Shin, Dam Emergency Action Plans in Korea, ICOLD 2013 International Symposium, Seattle, WA.

100-13   John Hess, Jeffrey Wisniewski, David Neff and Mike Forrest, A New Auxiliary Spillway for Folsom Dam, ICOLD 2013 International Symposium, Seattle, WA.

98-13   Neda Sharif and Amin Rostami Ravori, Experimental and Numerical Study of the Effect of Flow Separation on Dissipating Energy in Compound Bucket, 2013 5th International Conference on Chemical, Biological and Environmental Engineering (ICBEE 2013); 2013 2nd International Conference on Civil Engineering (ICCEN 2013)

97-13  A. Stergiopoulou, V. Stergiopoulos, and E. Kalkani, Contributions to the Study of Hydrodynamic Behaviour of Innovative Archimedean Screw Turbines Recovering the Hydropotential of Watercourses and of Coastal Currents, Proceedings of the 13th International Conference on Environmental Science and Technology Athens, Greece, 5-7 September 2013

96-13   Shokry Abdelaziz, Minh Duc Bui, Namihira Atsushi, and Peter Rutschmann, Numerical Simulation of Flow and Upstream Fish Movement inside a Pool-and-Weir Fishway, Proceedings of 2013 IAHR World Congress, Chengdu, China

95-13  Guodong Li, Lan Lang, and Jian Ning, 3D Numerical Simulation of Flow and Local Scour around a Spur Dike, Proceedings of 2013 IAHR World Congress, Chengdu, China

93-13   Matthew C. Kondratieff and Eric E. Richer, Stream Habitat Investigations and Assistance, Federal Aid Project F-161-R19, Federal Aid in Fish and Wildlife Restoration, Job Progress Report, Colorado Parks & Wildlife, Aquatic Wildlife Research Section, Fort Collins, Colorado, August 2013. Available upon request

92-13   Matteo Tirindelli, Scott Fenical and Vladimir Shepsis, State-of-the-Art Methods for Extreme Wave Loading on Bridges and Coastal Highways, Seventh National Seismic Conference on Bridges and Highways (7NSC), May 20-22, 2013, Oakland, CA

91-13   Cecia Millán Barrera, Víctor Manuel Arroyo Correa, Jorge Armando Laurel Castillo, Modeling contaminant transport with aerobic biodegradation in a shallow water body, Proceedings of 2013 IAHR Congress © 2013 Tsinghua University Press, Beijing

80-13  Brian Fox, Matthew Kondratieff, Brian Bledsoe, Christopher Myrick, Eco-Hydraulic Evaluation of Whitewater Parks as Fish Passage Barriers, International Conference on Engineering and Ecohydrology for Fish Passage, June 25-27, 2013, Oregon State University. Presentation available for download on the Scholarworks site.

79-13  Changsung Kim, Jongtae Kim, Joongu Kang, Analysis of the Cause for the Collapse of a Temporary Bridge Using Numerical Simulation, Engineering, 2013, 5, 997-1005, (http://www.scirp.org/journal/eng), Copyright © 2013 Changsung Kim et al. Published Online December 2013

76-13   Riley J. Olsen, Michael C. Johnson, and Steven L. Barfuss, Low-Head Dam Reverse Roller Remediation Options, Journal of Hydraulic Engineering, November 2013; doi:10.1061/(ASCE)HY.1943-7900.0000848.

72-13  M. Pfister, E. Battisacco, G. De Cesare, and A.J. Schleiss, Scale effects related to the rating curve of cylindrically crested Piano Key weirs, Labyrinth and Piano Key Weirs II – PKW 2013 – Erpicum et al. (eds), © 2014 Taylor & Francis Group, London, ISBN 978-1-138-00085-8.

71-13  F. Laugier, J. Vermeulen, and V. Lefebvre, Overview of Piano KeyWeirs experience developed at EDF during the past few years, Labyrinth and Piano Key Weirs II – PKW 2013 – Erpicum et al. (eds), © 2014 Taylor & Francis Group, London, ISBN 978-1-138-00085-8.

70-13   G.M. Cicero, J.R. Delisle, V. Lefebvre, and J. Vermeulen, Experimental and numerical study of the hydraulic performance of a trapezoidal Piano Key weir, Labyrinth and Piano Key Weirs II – PKW 2013 – Erpicum et al. (eds, © 2014 Taylor & Francis Group, London, ISBN 978-1-138-00085-8.

69-13   V. Lefebvre, J. Vermeulen, and B. Blancher, Influence of geometrical parameters on PK-Weirs discharge with 3D numerical analysis, Labyrinth and Piano Key Weirs II – PKW 2013 – Erpicum et al. (eds), © 2014 Taylor & Francis Group, London, ISBN 978-1-138-00085-8.

65-13 Alkistis Stergiopoulou and Efrossini Kalkani, Towards a First CFD Study of Innovative Archimedean Inclined Axis Hydropower Turbines, International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, Vol. 2 Issue 9, September 2013.

58-13  Timothy Sassaman, Andrew Johansson, Ryan Jones, and Marianne Walter, Hydraulic Analysis of a Pumped Storage Pond Using Complementary Methods, Hydrovision 2013 Conference Proceedings, Denver, CO, July 2013.

57-13  Jose Vasquez, Kara Hurtig, and Brian Hughes, Computational Fluid Dynamics (CFD) Modeling of Run-of-River Intakes, Hydrovision 2013 Conference Proceedings, Denver, CO July 2013.

56-13  David Souders, Jayesh Kariya, and Jeff Burnham, Validation of a Hybrid 3-Dimensional and 2-Dimensional Flow Modeling Technique for an Instanenous Dam-Break, Hydrovision 2013 Conference Proceedings, Denver, CO July 2013.

55-13  Keith Moen, Dan Kirschbaum, Joe Groeneveld, Steve Smith and Kimberly Pate, Sluiceway Deflector Design as part of the Boundary TDG Abatement Program, Hydrovision 2013 Conference Proceedings, Denver, CO, July 2013.

54-13  S. Temeepattanapongsa, G. P. Merkley, S. L. Barfuss and B. Smith, Generic unified rating for Cutthroat flumes, Irrig Sci, DOI 10.1007/s00271-013-0411-3, Springer-Verlag Berlin Heidelberg 2013, August 2013.

53-13 Hossein Afshar and Seyed Hooman Hoseini, Experimental and 3-D Numerical Simulation of Flow over a Rectangular Broad-Crested Weir, International Journal of Engineering and Advanced Technology (IJEAT), ISSN: 2249-8958, Volume 2, Issue 6, August 2013

52-13  Abdulmajid Matinfard (Kabi), Mohammad Heidarnejad, Javad Ahadian, Effect of Changes in the Hydraulic Conditions on the Velocity Distribution around a L-Shaped Spur Dike at the River Bend, Technical Journal of Engineering and Applied Sciences Available online at www.tjeas.com ©2013 TJEAS Journal-2013-3-16/1862-1868 ISSN 2051-0853 ©2013 TJEAS

51-13  Elham Radaei, Sahar Nikbin, and Mahdi Shahrokhi, Numerical Investigation of Angled Baffle on the Flow Pattern in a Rectangular Primary Sedimentation Tank, RCEE, Research in Civil and Environmental Engineering 1 (2013) 79-91.

48-13   Mohammad Kayser, Mohammed A. Gabr, Assessment of Scour on Bridge Foundations by Means of In Situ Erosion Evaluation Probe, Transportation Research Record: Journal of the Transportation Research Board, 0361-1981 (Print), Volume 2335 / 2013, pp 72-78. 10.3141/2335-08, August 2013.

47-13  Wei Ping Yin et al., 2013, Three-Dimensional Water Temperature and Hydrodynamic Simulation of Xiangxi River Estuary, Advanced Materials Research, 726-731, 3212, August, 2013.

41-13   N. Nekoue, R. Mahajan, J. Hamrick, and H. Rodriguez, Selective Withdrawal Hydraulic Study Using Computational Fluid Dynamics Modeling, World Environmental and Water Resources Congress 2013: pp. 1808-1813. doi: 10.1061/9780784412947.177.

40-13  Eleanor Kolden, Modeling in a three-dimensional world: whitewater park hydraulics and their impact on aquatic habitat in Colorado, Thesis: Master of Science, Civil and Environmental Engineering, Colorado State University. Full thesis available online at Colorado State University.

38-13  Prashant Huddar P.E. and Yashodhan Dhopavkar, CFD Use in Water – Insight, Foresight, and Efficiency, CFD Application in Water Engineering, Bangalore, India, June 2013.

37-13 B. Gems, M. Wörndl, R. Gabl, C. Weber, and M. Aufleger, Experimental and numerical study on the design of a deposition basin outlet structure at a mountain debris cone, Nat. Hazards Earth Syst. Sci. Discuss., 1, 3169–3200, 2013, www.nat-hazards-earth-syst-sci-discuss.net/1/3169/2013/, doi:10.5194/nhessd-1-3169-2013, © Author(s) 2013. Full paper online at: Natural Hazards and Earth System Sciences.

33-13   Tian Zhou and Theodore A. Endreny, Reshaping of the hyporheic zone beneath river restoration structures: Flume and hydrodynamic experiments, Water Resources Research, DOI: 10.1002/wrcr.20384, ©2013. American Geophysical Union. All Rights Reserved.

31-13  Francesco Calomino and Agostino Lauria, MOTO ALL’IMBOCCO DI UN CANALE RETTANGOLARE CONTROLLATO DA PARATOIA PIANA. Analisi sperimentale e modellazione numerica 3DFLOW AT THE INTAKE OF THE RECTANGULAR CHANNEL ;CONTROLLED BY A FLAT SLUICE GATE. Experimental and Numerical 3D ModelL’acqua, pp. 29-36, © Idrotecnica Italiana, 2013. In Italian and English.

30-13  Vinod V. Nair and S.K. Bhattacharyya, Numerical Study of Water Impact of Rigid Sphere under the Action of Gravity CFD Application in Water Engineering, Bangalore, India, June 2013. Abstract only.

29-13   Amar Pal Singh, Faisal Bhat, Ekta Gupta, 3-D Spillway Simulations of Ratle HEP (J&K) for the Assessment of Design Alternatives to be Tested in Model Studies, CFD Application in Water Engineering, Bangalore, India, June 2013.

28-13  Shun-Chung Tsung, Jihn-Sung Lai, and Der-Liang Young, Velocity distribution and discharge calculation at a sharp-crested weir, Paddy Water Environ, DOI 10.1007/s10333-013-0378-y, © Springer Japan 2013, May 2013.

27-13  Karen Riddette and David Ho, Assessment of Spillway Modeling Using Computational Fluid DynamicsANCOLD Proceedings of Technical Groups, 2013.

21-13  Tsung-Hsien Huang and Chyan-Deng Jan, Simulation of Velocity Distribution for Water Flow in a Vortex-Chamber-Type Sediment Extractor, EGU General Assembly 2013, held 7-12 April, 2013 in Vienna, Austria, id. EGU2013-7061. Online at: http://adsabs.harvard.edu/abs/2013EGUGA..15.7061H

19-13  Riley J. Olsen, Hazard Classification and Hydraulic Remediation Options for Flat-Topped and Ogee-Crested Low- Head Dams, Thesis: Master of Science in Civil and Environmental Engineering, Utah State University, All Graduate Theses and Dissertations. Paper 1538. http://digitalcommons.usu.edu/etd/1538, 2013.

17-13  Mohammad-Hossein Erfanain-Azmoudeh and Amir Abbas Kamanbedast, Determine the Appropriate Location of Aerator System on Gotvandolia Dam’s Spillway Using FLOW-3D, American-Eurasian J. Agric. & Environ. Sci., 13 (3): 378-383, 2013, ISSN 1818-6769, © IDOSI Publications, 2013.

13-13   Chia-Cheng Tsai, Yueh-Ting Lin, and Tai-Wen Hsu, On the weak viscous effect of the reflection and transmission over an arbitrary topography, Phys. Fluids 25, 043103 (2013); http://dx.doi.org/10.1063/1.4799099 (21 pages).

07-13  M. Kayser and M. A. Gabr, Scour Assessment of Bridge Foundations Using an In Situ Erosion Evaluation Probe (ISEEP), 92nd Transportation Research Board Annual Meeting, January 13-17, 2013, Washington, D.C.

06-13   Yovanni A. Cataño-Lopera, Blake J. Landry, Jorge D. Abad, and Marcelo H. García, Experimental and Numerical Study of the Flow Structure around Two Partially Buried Objects on a Deformed Bed, Journal of Hydraulic Engineering © ASCE /March 2013, 269-283.

04-13  Safinaz El-Solh, SPH Modeling of Solitary Waves and Resulting Hydrodynamic Forces on Vertical and Sloping Walls, Thesis: Master of Applied Science in Civil Engineering, Department of Civil Engineering, University of Ottawa, October 2012, © Safinaz El-Solh, Ottawa, Canada, 2013. Full paper available online at uOttawa.

108-12  Hatice Ozmen-Cagatay and Selahattin Kocaman, Investigation of Dam-Break Flow Over Abruptly Contracting Channel With Trapezoidal-Shaped Lateral Obstacles, Journal of Fluids Engineering © 2012 by ASME August 2012, Vol. 134 / 081204-1

102-12 B.M. Crookston, G.S. Paxson, and B.M. Savage, Hydraulic Performance of Labryinth Weirs for High Headwater Ratios, 4th IAHR International Symposium on Hydraulic Structures, 9-11 February 2012, Porto, Portugal, ISBN: 978-989-8509-01-7.

101-12 Jungseok Ho and Wonil Kim, Discrete Phase Modeling Study for Particle Motion in Storm Water Retention, KSCE Journal of Civil Engineering (2012) 16(6):1071-1078, DOI 10.1007/s12205-012-1304-3.

99-12  Charles R. Ortloff and Michael E. Mosely, Environmental change at a Late Archaic period site in north central coast Perú, Ñawpa Pacha, Journal of Andean Archaeology, Volume 32, Number 2 / December 2012, ISSN: 0077-6297 (Print); 2051-6207 (Online), Left Coast Press, Inc.

98-12  Tao Wang and Vincent H. Chu, Manning Friction in Steep Open-channel Flow, Seventh International Conference on Computational Fluid Dynamics (ICCFD7), Big Island, Hawaii, July 9-13, 2012.

96-12  Zhi Yong Dong, Qi Qi Chen, Yong Gang, and Bin Shi, Experimental and Numerical Study of Hydrodynamic Cavitation of Orifice Plates with Multiple Triangular Holes, Applied Mechanics and Materials, Volumes 256-259, Advances in Civil Engineering, December 2012.

95-12  Arjmandi H., Ghomeshi M.,  Ahadiayn J., and Goleij G., Prediction of Plunge Point in the Density Current using RNG Turbulence Modeling, Water and Soil Science (Agricultural Science) Spring 2012; 22(1):171-185. Abstract available online at the Scientific Online Database.

84-12  Li Ping Zhao, Jian Qiu Zhang, Lei Chen, Xuan Xie, Jun Qiang Cheng, Study of Hydrodynamic Characteristics of the Sloping Breakwater of Circular Protective Facing, Advanced Materials Research (Volumes 588 – 589), Advances in Mechanics Engineering, 1781-1785, 10.4028/www.scientific.net/AMR.588-589.1781.

83-12 Parviz Ghadimi, Abbas Dashtimanesh, and Seyed Reza Djeddi, Study of water entry of circular cylinder by using analytical and numerical solutions, J. Braz. Soc. Mech. Sci. & Eng. 2012, vol.34, n.3, pp. 225-232 . ISSN 1678-5878. http://dx.doi.org/10.1590/S1678-58782012000300001.

81-12  R. Gabl, S. Achleitner, A. Sendlhofer, T. Höckner, M. Schmitter and M. Aufleger, Side-channel spillway – Hybrid modeling, Hydraulic Measurements and Experimental Methods 2012, EWRI/ASCE, August 12-15, 2012, Snowbird, Utah.

80-12  Akin Aybar, Computational Modelling of Free Surface Flow in Intake Structures using FLOW-3D Software, Thesis: MS in Civil Engineering, The Graduate School of Natural and Applied Sciences of Middle East Technical University, June 2012.

74-12  Mahdi Shahrokhi, Fatemeh Rostami, Md Azlin Md Said, Saeed Reza Sabbagh Yazdi, and Syafalni Syafalni, Computational investigations of baffle configuration effects on the performance of primary sedimentation tanks, Water and Environment Journal, 22 October 2012, © 2012 CIWEM.

68-12  Jalal Attari and Mohammad Sarfaraz, Transitional Steps Zone in Steeply Stepped Spillways, 9th International Congress on Civil Engineering, May 8-10, 2012, Isfahan University of Technology (IUT), Isfahan, Iran

67-12  Mohammad Sarfaraz, Jalal Attari and Michael Pfister, Numerical Computation of Inception Point Location for Steeply Sloping Stepped Spillways, 9th International Congress on Civil Engineering, May 8-10, 2012, Isfahan University of Technology (IUT), Isfahan, Iran

64-12  Anders Wedel Nielsen, Xiaofeng Liu, B. Mutlu Sumer, Jørgen Fredsøe, Flow and bed shear stresses in scour protections around a pile in a current, Coastal Engineering, Volume 72, February 2013, Pages 20–38.

62-12  Ehab A. Meselhe, Ioannis Georgiou, Mead A. Allison, John A McCorquodale, Numerical Modeling of Hydrodynamics and Sediment Transport in Lower Mississippi at a Proposed Delta Building Diversion, Journal of Hydrology, October 2012.

60-12  Markus Grünzner and Gerhard Haimerl, Numerical Simulation Downstream Attraction Flow at Danube Weir Donauwörth, 9th ISE 2012, Vienna, Austria.

59-12 M. Grünzner, A 3 Dimensional Numerical (LES) and Physical ‘Golf Ball’ Model in Comparison to 1 Dimensional Approach, Hydraulic Measurements and Experimental Methods 2012, EWRI/ASCE, August 12-15, 2012, Snowbird, Utah

58-12  Shawn P. Clark, Jonathan S. Toews, Martin Hunt and Rob Tkach, Physical and Numerical Modeling in Support of Fish Passage Regulations, 9th ISE 2012, Vienna, Austria.

57-12  Mahdi Shahrokhi, Fatemeh Rostami, Md Azlin Md Said, Syafalni, Numerical Modeling of Baffle Location Effects on the Flow Pattern of Primary Sedimentation Tanks, Applied Mathematical Modelling, Available online October 2012, http://dx.doi.org/10.1016/j.apm.2012.09.060.

50-12  Gricelda Ramirez, A Virtual Flow Meter to Develop Velocity-Index Ratings and Evaluate the Effect of Flow Disturbances on these Ratings, Master’s Thesis: Department of Civil Engineering in the Graduate College of the University of Illinois at Urbana-Champaign, 2012.

43-12  A. A. Girgidov, A. D. Girgidov and M. P. Fedorov, Use of dispersing springboards to reduce near-bottom velocity in a toe basin, Power Technology and Engineering (formerly Hydrotechnical Construction), Volume 46, Number 2 (2012), 113-115, DOI: 10.1007/s10749-012-0316-y.

40-12  Jong Pil Park, Kyung Sik Choi, Ji Hwan Jeong, Gyung Min Choi, Ju Yeop Park, and Man Woong Kim, Experimental and numerical evaluation of debris transport augmentation by turbulence during the recirculation-cooling phase, Nuclear Engineering and Design 250 (2012) 520-537

39-12  Hossein Basser, Abdollah Ardeshir, Hojat Karami, Numerical simulation of flow pattern around spur dikes series in rigid bed, 9th International Congress on Civil Engineering, May 8-10, 2012 Isfahan University of Technology (IUT), Isfahan, Iran

38-12  Sathaporn Temeepattanapongsa, Unified Equations for Cutthroat Flumes Derived from a Three-Dimensional Hydraulic Model, (2012). Thesis: Utah State University, All Graduate Theses and Dissertations. Paper 1308. Available online at: http://digitalcommons.usu.edu/etd/1308

36-12 Robert Feurich, Jacques Boubée, Nils Reidar B. Olsen, Improvement of fish passage in culverts using CFD, Ecological Engineering, Volume 47, October 2012, Pages 1–8.

35-12 Yovanni A. Cataño-Lopera and Jorge D. Abad, Flow Structure around a Partially Buried Object in a Simulated River Bed, World Environmental And Water Resources Congress 2012, Albuquerque, New Mexico, United States, May 20-24, 2012.

33-12  Fatemeh Rostami, Saeed Reza Sabbagh Yazdi, Md Azlin Md Said and Mahdi Shahrokhi, Numerical simulation of undular jumps on graveled bed using volume of fluid method, Water Science & Technology Vol 66 No 5 pp 909–917 © IWA Publishing 2012 doi:10.2166/wst.2012.213.

30-12  Saman Abbasi and Amir Abbas Kamanbedast, Investigation of Effect of Changes in Dimension and Hydraulic of Stepped Spillways for Maximization Energy Dissipation, World Applied Sciences Journal 18 (2): 261-267, 2012, ISSN 1818-4952, © IDOSI Publications, 2012, DOI: 10.5829/idosi.wasj.2012.18.02.492

24-12  Mario Oertel, Jan Mönkemöller and Andreas Schlenkhoff, Artificial stationary breaking surf waves in a physical and numerical model, Journal of Hydraulic Research, 50:3, 338-343, 2012.

23-12  Mario Oertel, Cross-bar block ramps:Flow regimes – flow resistance – energy dissipation – stability, thesis, Bericht Nr. 20, 2012, © 2011/12 Dr. Mario Oertel, Hydraulic Engineering Section, Bergische University of Wuppertal. Duplication only with author’s permission.

20-12  M. Oertel and A. Schlenkhoff, Crossbar Block Ramps: Flow Regimes, Energy Dissipation, Friction Factors, and Drag Forces, Journal of Hydraulic Engineering © ASCE, May 2012, pp. 440-448.

19-12  Mohsen Maghrebi, Saeed Alizadeh, and Rahim Lotfi, Numerical Simulation of Flow Over Rectangular Broad Crested Weir, 1st International and 3rd National Conference on Dams and Hydropower in Iran, Tehran, Iran, February 8 – February 9, 2012

18-12  Alireza Daneshkhah and Hamidreza Vosoughifar, Solution of Flow Field Equations to Investigate the Best Turbulent Model of Flow over a Standard Ogee Spillway, 1st International and 3rd National Conference on Dams and Hydropower in Iran, Tehran, Iran, February 8 – February 9, 2012

03-12  Hamed Taghizadeh, Seyed Ali Akbar Salehi Neyshabour and Firouz Ghasemzadeh, Dynamic Pressure Fluctuations in Stepped Three-Side Spillway, Iranica Journal of Energy & Environment 3 (1): 95-104, 2012, ISSN 2079-2115

02-12   Kim, Seojun, Yu, Kwonkyu, Yoon, Byungman, and Lim, Yoonsung, A numerical study on hydraulic characteristics in the ice Harbor-type fishway, KSCE Journal of Civil Engineering, 2012-02-01, Issn: 1226-7988, pp 265- 272, Volume: 16, Issue: 2, Doi: 10.1007/s12205-012-0010-5.

105-11 Hatice Ozmen Cagatay and Selahattin Kocaman, Dam-break Flow in the Presence of Obstacle: Experiment and CFD Simulation, Engineering Applications of Computational Fluid Mechancis, Vol. 5, No. 4, pp. 541-552, 2011

102-11 Sang Do An, Interflow Dynamics and Three-Dimensional Modeling of Turbid Density Currents in IMHA Reservoir, South Korea, thesis: Doctor of Philosophy, Department of Civil and Environmental Engineering at Colorado State University, 2011.

101-11 Tsunami – A Growing Disaster, edited by Mohammad Mokhtari, ISBN 978-953-307-431-3, 232 pages, Publisher: InTech, Chapters published December 16, 2011 under CC BY 3.0 license, DOI: 10.5772/922. Available for download at Intech.

98-11  Selahattin Kocaman and Hasan Guzel, Numerical and Experimental Investigation of Dam-Break Wave on a Single Building Situated Downstream, Epoka Conference Systems, 1st International Balkans Conference on Challenges of Civil Engineering, 19-21 May 2011, EPOKA University, Tirana, Albania.

97-11   T. Endreny, L. Lautz, and D. I. Siegel, Hyporheic flow path response to hydraulic jumps at river steps: Flume and hydrodynamic models, WATER RESOURCES RESEARCH, VOL. 47, W02517, doi:10.1029/2009WR008631, 2011.

96-11   Mahdi Shahrokhi, Fatemeh Rostami, Md Azlin Md Said and Syafalni, Numerical Simulation of Influence of Inlet Configuration on Flow Pattern in Primary Rectangular Sedimentation Tanks, World Applied Sciences Journal 15 (7): 1024-1031, 2011, ISSN 1818-4952, © IDOSI Publications, 2011. Full article available online at IODSI.

94-11  Kathleen H. Frizell, Summary of Hydraulic Studies for Ladder and Flume Fishway Design- Nimbus Hatchery Fish Passage Project, Hydraulic Laboratory Report HL-2010-04, U.S. Department of the Interior Bureau of Reclamation Technical Service Center Hydraulic Investigations and Laboratory Services Group, December 2011

88-11   Abdelaziz, S, Bui, MD, Rutschmann, P, Numerical Investigation of Flow and Sediment Transport around a Circular Bridge Pier, Proceedings of the 34th World Congress of the International Association for Hydro- Environment Research and Engineering: 33rd Hydrology and Water Resources Symposium and 10th Conference on Hydraulics in Water Engineering, ACT: Engineers Australia, 2011: 2624-2630.

86-11  M. Heidarnejad, D. Halvai and M. Bina, The Proper Option for Discharge the Turbidity Current and Hydraulic Analysis of Dez Dam Reservoir, World Applied Sciences Journal 13 (9): 2052-2056, 2011, ISSN 1818-4952 © IDOSI Publications, 2011

84-11  Martina Reichstetter and Hubert Chanson, Physical and Numerical Modelling of Negative Surges in Open Channels, School of Civil Engineering at the University of Queensland, Report CH84/11, ISBN No. 9781742720388, © Reichstetter and Chanson, 2011.

83-11  Reda M. Abd El-Hady Rady, 2D-3D Modeling of Flow Over Sharp-Crested Weirs, Journal of Applied Sciences Research, 7(12): 2495-2505, ISSN 1819-544X, 2011.

78-11  S. Abbasi, A. Kamanbedast and J. Ahadian, Numerical Investigation of Angle and Geometric of L-Shape Groin on the Flow and Erosion Regime at River Bends, World Applied Sciences Journal 15 (2): 279-284, 2011, ISSN 1818-4952 © IDOSI Publications, 2011.

75-11  Mario Oertel and Daniel B. Bung, Initial stage of two-dimensional dam-break waves: laboratory versus VOF, Journal of Hydraulic Research, DOI: 10.1080/00221686.2011.639981, Available online: 08 Dec 2011.

73-11  T.N. Aziz and A.A. Khan, Simulation of Vertical Plane Turbulent Jet in Shallow Water, Advances in Civil Engineering, vol. 2011, Article ID 292904, 10 pages, 2011. doi:10.1155/2011/292904.

67-11   Chung R. Song, ASCE, Jinwon Kim, Ge Wang, and Alexander H.-D. Cheng, Reducing Erosion of Earthen Levees Using Engineered Flood Wall SurfaceJournal of Geotechnical and Geoenvironmental Engineering, Vol. 137, No. 10, October 2011, pp. 874-881, http://dx.doi.org/10.1061/(ASCE)GT.1943-5606.0000500.

64-11  Mahdi Shahrokhi, Fatemeh Rostami, Md Azlin Md Said, Syafalni, The Effect of Number of Baffles on the Improvement Efficiency of Primary Sedimentation Tanks, Available online 11 November 2011, ISSN 0307-904X, 10.1016/j.apm.2011.11.001.

62-11  Jana Hadler, Klaus Broekel, Low head hydropower – its design and economic potential, World Renewable Energy Congress 2011, Sweden, May 8-13, 2011.

60-11 Md. Imtiaj Hassan and Nahidul Khan, Performance of a Quarter-Pitch Twisted Savonius Turbine, The International Conference and Utility Exhibition 2011, Pattaya City, Thailand, 28-30 September 2011.

59-11   Erin K. Gleason, Ashraful Islam, Liaqat Khan, Darrne Brinker and Mike Miller, Spillway Analysis Techniques Using Traditional and 3-D Computational Fluid Dynamics Modeling, Dam Safety 2011, National Harbor, MD, September 25-29, 2011.

58-11  William Rahmeyer, Steve Barfuss, and Bruce Savage, Composite Modeling of Hydraulic Structures, Dam Safety 2011, National Harbor, MD, September 25-29, 2011.

57-11  B. Dasgupta, K. Das, D. Basu, and R. Green, Computational Methodology to Predict Rock Block Erosion in Plunge Pools, Dam Safety 2011, National Harbor, MD, September 25-29, 2011.

56-11  Jeff Burnham, Modeling Dams with Computational Fluid Dynamics- Past Success and New Directions, Dam Safety 2011, National Harbor, MD, September 25-29, 2011.

52-11  Madhi Shahrokhi, Fatemeh Rostami, Md Azlin Md Said, and Syafalni, The Computational Modeling of Baffle Configuration in the Primary Sedimentation Tanks, 2011 2nd International Conference on Environmental Science and Technology IPCBEE vol 6. (2011) IACSIT Press, Singapore.

47-11  Stefan Haun, Nils Reidar B. Olsen and Robert Feurich, Numerical Modeling of Flow over Trapezoidal Broad-Crested Weir, Engineering Applications of Computational Fluid Mechanics Vol 5., No. 3, pp. 397-405, 2011.

42-11  Anu Acharya, Experimental Study and Numerical Simulation of Flow and Sediment Transport around a Series of Spur Dikes, thesis: The University of Arizona Graduate College, Copyright © Anu Acharya 2011, July 2011.

38-11  Mehdi Shahosseini, Amirabbas Kamanbedast and Roozbeh Aghamajidi, Investigation of Hydraulic Conditions around Bridge Piers and Determination of Shear Stress using Numerical Methods, World Environmental and Water Resources Congress 2011, © ASCE 2011.

35-11  L. Toombes and H. Chanson, Numerical Limitations of Hydraulic Models, 34th IAHR World Congress, 33rd Hydrology & Water Resources Symposium, 10th Hydraulics Conference, Brisbane, Australia, 26 June – 1 July 2011.

34-11  Mohammad Sarfaraz, and Jalal Attari, Numerical Simulation of Uniform Flow Region over a Steeply Sloping Stepped Spillway, 6th National Congress on Civil Engineering, Semnan University, Semnan, Iran, April 26-27, 2011.

30-11  John Richardson and Pamela Waterman, Stemming the Flood, Mechanical Engineering, Vol. 133/No.7 July 2011

29-11  G. Möller & R. Boes, D. Theiner & A. Fankhauser, G. De Cesare & A. Schleiss, Hybrid modeling of sediment management during drawdown of Räterichsboden reservoir, Dams and Reservoirs under Changing Challenges – Schleiss & Boes (Eds), © 2011 Taylor & Francis Group, London, ISBN 978-0-415-68267-1.

24-11  Liaqat A. Khan, Computational Fluid Dynamics Modeling of Emergency Overflows through an Energy Dissipation Structure of a Water Treatment Plant, ASCE Conf. Proc. doi:10.1061/41173(414)155, World Environmental and Water Resources Congress 2011.

23-11  Anu Acharya and Jennifer G. Duan, Three Dimensional Simulation of Flow Field around Series of Spur Dikes, ASCE Conf. Proc. doi:10.1061/41173(414)218, World Environmental and Water Resources Congress 2011.

22-11  Mehdi Shahosseini, Amirabbas Kamanbedast, and Roozbeh Aghamajidi, Investigation of Hydraulic Conditions around Bridge Piers and Determination of Shear Stress Using Numerical Method, ASCE Conf. Proc. doi:10.1061/41173(414)435, World Environmental and Water Resources Congress 2011.

20-11  Jong Pil Park, Ji Hwan Jeong, Won Tae Kim, Man Woong Kim and Ju Yeop Park, Debris transport evaluation during the blow-down phase of a LOCA using computational fluid dynamics, Nuclear Engineering and Design, June 2011, ISSN 0029-5493, DOI: 10.1016/j.nucengdes.2011.05.017.

13-11 Ehab A. Meselhe, Myrtle Grove Delta Building Diversion Project, The Geological Society of America, South-Central Section – 45th Annual Meeting, New Orleans, Louisiana, March 2011.

12-11  Bryan Heiner and Steven L. Barfuss, Parshall Flume and Discharge Corrections Wall Staff Gauge and Centerline Measurements, Journal of Irrigation and Drainage Engineering, posted ahead of print February 1, 2011, DOI:10.1061/(ASCE)IR.1943-4774.0000355, © 2011 by the American Society of Civil Engineers.

06-11  T. Endreny, L. Lautz, and D. Siegel, Hyporheic flow path response to hydraulic jumps at river steps- Hydrostatic model simulations, Water Resources Research, Vol. 47, W02518, doi: 10.1029/2010WR010014, 2011, © 2011 by the American Geophysical Union, 0043-1397/11/2010WR010014

03-11  Jinwon Kim, Chung R. Song, Ge Wang and Alexander H.-D. Cheng Reducing Erosion of Earthen Levees Using Engineered Flood Wall Surface, Journal of Geotechnical and Geoenvironmental Engineering, © ASCE, January 2011.

02-11  F. Montagna, G. Bellotti and M. Di Risio, 3D numerical modeling of landslide-generated tsunamis around a conical island, Springer Link, Earth and Environmental Science, Natural Hazards, DOI: 10.1007/s11069-010-9689-0, Online First™, 7 January 2011.

83-10   S. Abdelaziz, M.D. Bui and P. Rutschmann, Numerical simulation of scour development due to submerged horizontal jet, River Flow 2010, eds. Dittrich, Koll, Aberle & Geisenhainer, © 2010 Bundesanstalt für Wasserbau, ISBN 978-3-939230-00-7.

79-10  Daniel J. Howes, Charles M. Burt, and Brett F. Sanders, Subcritical Contraction for Improved Open-Channel Flow Measurement Accuracy with an Upward-Looking ADVM, J. Irrig. Drain Eng. 2010.136:617-626.

78-10  M. Kaheh, S. M. Kashefipour, and A. Dehghani, Comparison of k-ε and RNG k-ε Turbulent Models for Estimation of Velocity Profiles along the Hydraulic Jump, presented at the 6th International Symposium on Environmental Hydraulics, Athens, Greece, June 2010.

75-10  Shahrokh Amiraslani, Jafar Fahimi, Hossein Mehdinezhad, The Numerical Investigation of Free Falling Jet’s Effect on the Scour of Plunge Pool, XVIII International Conference on Water Resources CMWR 2010 J. Carrera (Ed) CIMNE, Barcelona 2010

74-10  M. Ho Ta Khanh, Truong Chi Hien, and Dinh Sy Quat, Study and construction of PK Weirs in Vietnam (2004 to 2011), 78th Annual Meeting of the International Commission on Large Dams,  VNCOLD, Hanoi, Vietnam, May 23-26, 2010.

72-10  DKH Ho and KM Riddette, Application of computational fluid dynamics to evaluate hydraulic performance of spillways in Australia, © Institution of Engineers Australia, 2010, Australian Journal of Civil Engineering, Vol 6 No 1, 2010.

71-10  Cecilia Lucino, Sergio Liscia y Gonzalo Duro, Vortex Detection in Pump Sumps by Means of CFD, XXIV Latin American Congress on Hydraulics, Punta Del Este, Uruguay, November 2010; Deteccion de Vortices en Darsenas de Bombeo Mediante Modelacion MatematicaAvailable in English and Spanish.

64-10 Jose (Pepe) Vasquez, Assessing Sediment Movement by CFD Particle Tracking, 2nd Joint Federal Interagency Conference, Las Vegas, Nevada, June 27-July 1, 2010.

63-10 Sung-Min Cho, Foundation Design of the Incheon Bridge, Geotechnical Engineering Journal of the SEAGS & AGSSEA Vol 41 No.4, ISSN0046-5828, December 2010.

61-10  I. Meireles, F.A. Bombardelli and J. Matos, Experimental and Numerical Investigation of the Non-Aerated Skimming Flow on Stepped Spillways Over Embankment Dams, Presented at the 2010 IAHR European Congress, Edinburgh, UK, May 4-6, 2010.

60-10  Mario Oertel, G. Heinz and A. Schlenkhoff, Physical and Numerical Modelling of Rough Ramps and Slides, Presented at the 2010 IAHR European Congress, Edinburgh, UK, May 4-6, 2010.

59-10  Fatemeh Rostami, Mahdi Shahrokhi, Md Azlin Md Said, Rozi Abdullah and Syafalni, Numerical modeling on inlet aperture effects on flow pattern in primary settling tanks, Applied Mathematical Modelling, Copyright © 2010 Elsevier Inc., DOI: 10.1016/j.apm.2010.12.007, December 2010.

56-10  G. B. Sahoo, F Bombardelli, D. Behrens and J.L. Largier, Estimation of Stratification and Mixing of a Closed River System Using FLOW-3D, American Geophysical Union, Fall Meeting 2010, abstract #H31G-1091

50-10  Sung-Duk Kim, Ho-Jin Lee and Sang-Do An, Improvement of hydraulic stability for spillway using CFD model, International Journal of the Physical Sciences Vol. 5(6), pp. 774-780, June 2010. Available online at http://www.academicjournals.org/IJPS, ISSN 1992

49-10  Md. Imtiaj Hassan, Tariq Iqbal, Nahidul Khan, Michael Hinchey, Vlastimil Masek, CFD Analysis of a Twisted Savonius Turbine, PKP Open Conference Systems, IEEE Newfoundland and Labrador Section, October 2010

46-10  Hatice Ozmen-Cagatay and Selahattin Kocaman, Dam-break flows during initial stage using SWE and RANS approaches, Journal of Hydraulic Research, Vol 48, No. 5 (2010), pp. 603-611, doi: 10.108/00221686.2010.507342, © 2010 International Association for Hydro-Environment Engineering and Research.

44-10  Marie-Hélène Briand, Catherine Tremblay, Yannick Bossé, Julian Gacek, Carola Alfaro, and Richard Blanchet, Ashlu Creek hydroelectric project- Design and optimization of hydraulic structures under construction, CDA 2010 Annual Conference, Congrès annuel 2010 de l’A CB, Niagra Falls, ON, Canada, 2010 Oct 2-7.

43-10 Gordon McPhail, Justin Lacelle, Bert Smith, and Dave MacMillan, Upgrading of Boundary Dam Spillway, CDA 2010 Annual Conference, Congrès annuel 2010 de l’A CB, Niagra Falls, ON, Canada, 2010 Oct 2-7.

40-10 Selahattin Kocamana; Galip Seckinb; Kutsi S. Erduran, 3D model for prediction of flow profiles around bridges, DOI: 10.1080/00221686.2010.507340, Journal of Hydraulic Research, Volume 48, Issue 4 August 2010, pages 521 – 525. Available online at: informaworld

38-10  Kevin M. Sydor and Pamela J. Waterman, Engineering and Design: The Value of CFD Modeling in Designing a Hydro Plant, Hydro Review, Volume 29, Issue 6, September 2010 Available online at HydroWorld.com

33-10  Fabián A. Bombardelli, Inês Meireles and Jorge Matos, Laboratory measurements and multi-block numerical simulations of the mean flow and turbulence, SpringerLink, Environmental Fluid Mechanics, Online First™, 26 August 2010

30-10 Bijan Dargahi, Flow characteristics of bottom outlets with moving gates, IAHR, Journal of Hydraulic Research, Vol. 48, No. 4 (2010), pp. 476-482, doi: 10.1080/00221686.20101.507001, © 2010 International Association for Hydro-Environment Engineering and Research

24-10 Shuang Ming Wang and Kevin Sydor, Power Intake Velocity Modeling Using FLOW-3D at Kelsey Generating Station, Canadian Dam Association Bulletin, Vol. 21. No. 2, Spring 2010, pp: 16-21

20-10 Jungseok Ho, Todd Marti and Julie Coonrod, Flood debris filtering structure for urban storm water treatment, DOI: 10.1080/00221686.2010.481834, Journal of Hydraulic Research, Volume 48, Issue 3, pages 320 – 328, June 2010.

16-10 J. Jacobsen and N. R. B. Olsen, Three-dimensional numerical modeling of the capacity for a complex spillway, Proceedings of the ICE – Water Management, Volume 163, Issue 6, pages 283 –288, ISSN: 1741-7589, E-ISSN: 1751-7729.

13-10 J. Ho, J. Coonrod, L. J. Hanna, B. W. Mefford, Hydrodynamic modelling study of a fish exclusion system for a river diversion, River Research and Applications Volume 9999, mIssue 9999, Copyright © 2005 John Wiley & Sons, Ltd.

12-10 Nils Rüther, Jens Jacobsen, Nils Reidar B. Olsen and Geir Vatne, Prediction of the three-dimensional flow field and bed shear stresses in a regulated river in mid-Norway, Hydrology Research Vol 41 No 2 pp 145–152 © IWA Publishing 2010, doi:10.2166/nh.2010.064.

11-10 Xing Fang, Shoudong Jiang, and Shoeb R. Alam, Numerical Simulations of Efficiency of Curb-Opening Inlets, J. Hydr. Engrg. Volume 136, Issue 1, pp. 62-66 (January 2010).

54-09    K.W. Frizell, J.P. Kubitschek, and R.F. Einhellig, Folsom Dam Joint Federal Project Existing Spillway Modeling – Discharge Capacity Studies, American River Division Central Valley Project Mid-Pacific Region, Hydraulic Laboratory Report HL-2009-02, US Department of the Interior, Bureau of Reclamation, Denver, Colorado, September 2009

50-09  Mark Fabian, Variation in Hyporheic Exchange with Discharge and Slope in a Tropical Mountain Stream, thesis: State University of New York, College of Environmental Science & Forestry, 2009. Available online: http://gradworks.umi.com/14/82/1482174.html.

48-09 Junwoo Choi, Kwang Oh Ko, and Sung Bum Yoon, 3D Numerical Simulation for Equivalent Resistance Coefficient for Flooded Built-Up Areas, Asian and Pacific Coasts 2009 (pp 245-251), Proceedings of the 5th International Conference on APAC 2009, Singapore, 13 – 16 October 2009

47-09 Young-Il Kim, Chang-Jin Ahn, Chae-Young Lee, Byung-Uk Bae, Computational Fluid Dynamics for Optimal Design of Horizontal-Flow Baffled-Channel Powdered Activated Carbon Contactors, Mary Ann Liebert, Inc. publishers, Volume: 26 Issue 1: January 15, 2009.

43-09 Charles R. Ortloff, Water Engineering in the Ancient World: Archaeological and Climate Perspectives on Societies of Ancient South America, Meso-America, the Middle East and South East Asia, Oxford University Press, ISBN13: 978-0-19-923909-2ISBN10: 0-19-923909-6, December 2009 Available at Oxford University Press (clicking on this link will take you to OUP’s website).

40-09 Ge Wang, Chung R. Song, Jinwon Kim and Alexander, H.-D Cheng, Numerical Study of Erosion-proof of Loose Sand in an Overtopped Plunging Scour Process — FLOW-3D, The 2009 Joint ASCE-ASME-SES Conference on Mechanics and Materials, Blacksburg, Virginia, June 24-27, 2009

39-09 Charles R. Ortloff, Water Engineering in the Ancient World: Archaeological and Climate Perspectives on Societies of Ancient South America, the Middle East, and South-East Asia(Hardcover), Oxford University Press, USA (October 15, 2009), ISBN-10: 0199239096; ISBN-13: 978-0199239092 Buy Water Engineering in the Ancient World on Amazon.com.

38-09 David S. Brown, Don MacDonell, Kevin Sydor, and Nicolas Barnes, An Integrated Computational Fluid Dynamics and Fish Habitat Suitability Model for the Pointe Du Bois Generating Station, CDA 2009 Annual Conference, Congres annuel 2009 de l’A CB, Whistler, BC, Canada, 2009 Oct 3-8, pdf pages: 53-66

37-09 Warren Gendzelevich, Andrew Baryla, Joe Groenveld, and Doug McNeil, Red River Floodway Expansion Project-Design and Construction of the Outlet Structure, CDA 2009 Annual Conference, Congres annuel 2009 de l’A CB, Whistler, BC, Canada, 2009 Oct 3-8, pdf pages: 13-26

36-09 Jose A. Vasquez and Jose J. Roncal, Testing River2D and FLOW-3D for Sudden Dam-Break Flow Simulations, CDA 2009 Annual Conference, Congres annuel 2009 de l’A CB, Whistler, BC, Canada, 2009 Oct 3-8, pdf pages: 44-55

33-09 Pamela J. Waterman, Modeling Commercial Aquaculture Systems Employing FLOW-3D, (clicking on this link will take you to Desktop Engineering’s website) Desktop Engineering, November 2009

29-09 Bruce M. Savage, Michael C. Johnson, Brett Towler, Hydrodynamic Forces on a Spillway- Can we calculate them?, Dam Safety 2009, Hollywood, FL, USA, October 2009

27-09 Charles “Chick” Sweeney, Keith Moen, and Daniel Kirschbaum, Hydraulic Design of Total Dissolved Gas Mitigation Measures for Boundary Dam, Waterpower XVI, © PennWell Corporation, Spokane, WA, USA, July 2009

23-09 J.A. Vasquez and B.W. Walsh, CFD simulation of local scour in complex piers under tidal flow, 33rd IAHR Congress: Water Engineering for a Sustainable Environment, © 2009 by International Association of Hydraulic Engineering & Research (IAHR), ISBN: 978-94-90365-01-1

15-09 Kaushik Das, Steve Green, Debashis Basu, Ron Janetzke, and John Stamatakos, Effect of Slide Deformation and Geometry on Waves Generated by Submarine Landslides- A Numerical Investigation, Copyright 2009, Offshore Technology Conference, Houston, Texas, USA, May 4-7, 2009

5-09 Remi Robbe, Douglas Sparks, Calculation of the Rating Curves for the Matawin Dam’s Bottom Sluice Gates using FLOW-3D, Conference of the Société Hydrotechnique de France (SHF), 20-21 January 2009, Paris, France. (in French)

4-09 Frederic Laugier, Gregory Guyot, Eric Valette, Benoit Blancher, Arnaud Oguic, Lily Lincker, Engineering Use of Hydrodynamic 3D Simulation to Assess Spillway Discharge Capacity, Conference of the Société Hydrotechnique de France (SHF), 20-21 January 2009, Paris, France. (in French)

50-08   H. Avila and R.Pitt, The Calibration and use of CFD Models to Examine Scour from Stormwater Treatment Devices – Hydrodynamic Analysis, 11th International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008

47-08    Greg Paxson, Brian Crookston, Bruce Savage, Blake Tullis, and Frederick Lux III, The Hydraulic Design Toolbox- Theory and Modeling for the Lake Townsend Spillway Replacement Project, Assoc. of State Dam Safety Officials (ASDSO), Indian Wells, CA, September 2008.

46-08  Sh. Amirslani, M. Pirestani and A.A.S. Neyshabouri, The 3D numerical simulation of scour by free falling jet and compare geometric parameters of scour hole with DOT, River flow 2008-Altinakar, Kokipar, Gogus, Tayfur, Kumcu & Yildirim (eds) © 2008 Kubaba Congress Department and Travel Services ISBN 978-605-601360201

44-08  Paul Guy Chanel, An Evaluation of Computational Fluid Dynamics for Spillway Modeling, thesis: Department of Civil Engineering, University of Manitoba, Copyright © 2008 by Paul Guy Chanel

41-08 Jinwei Qiu, Gravel transport estimation and flow simulation over low-water stream crossings, thesis: Lamar University – Beaumont, 2008, 255 pages; AAT 3415945

37-08 Dae-Geun Kim, Numerical analysis of free flow past a sluice gate, KSCE Journal of Civil Engineering, Volume 11, Number 2 / March, 2007, 127-132.

36-08 Shuang Ming Wang and Kevin Sydor, Power Intake Velocity Modeling using FLOW-3D at Kelsey Generating Station, CDA 2008 Annual Conference, Congres annuel 2008 de l’ACB, Winnipeg, MB, Canada, September 27-October 2, 2008, du 27 septembre au 2 octobre 2008

33-08 Daniel B. Bung, Arndt Hildebrandt, Mario Oertel, Andreas Schlenkhoff and Torsten Schlurmann, Bore Propagation Over a Submerged Horizontal Plate by Physical and Numerical Simulation, ICCE 2008, Hamburg, Germany

32-08 Paul G. Chanel and John C. Doering, Assessment of Spillway Modeling Using Computational Fluid Dynamics, Canadian Journal of Civil Engineering, 35: 1481-1485 (2008), doi: 10.1139/L08-094 © NRC Canada

31-08 M. Oertel & A. Schlenkhoff, Flood wave propagation and flooding of underground facilities, River Flow 2008, © 2008, International Conference on Fluvial Hydraulics, Izmir, Turkey, September, 2008

18-08 Efrem Teklemariam, Bernie Shumilak, Don Murray, and Graham K. Holder, Combining Computational and Physical Modeling to Design the Keeyask Station, Hydro Review, © HCI Publications, July 2008

15-08 Jorge D. Abad; Bruce L. Rhoads; İnci Güneralp; and Marcelo H. García, Flow Structure at Different Stages in a Meander-Bend with Bendway Weirs, Journal of Hydraulic Engineering © ASCE, August 2008

11-08 Sreenivasa C. Chopakatla, Thomas C. Lippmann and John E. Richardson, Field Verification of a Computational Fluid Dynamics Model for Wave Transformation and Breaking in the Surf Zone, J. Wtrwy., Port, Coast., and Oc. Engrg., Volume 134, Issue 2, pp. 71-80 (March/April 2008) Abstract Only

51-07   Richmond MC, TJ Carlson, JA Serkowski, CB Cook, JP Duncan, and WA Perkins, Characterizing the Fish Passage Environment at The Dalles Dam Spillway: 2001-2004, PNNL-16521, Pacific Northwest National Laboratory, Richland, WA, 2007. Available upon request

46-07 Uplift and Crack Flow Resulting from High Velocity Discharges Over Open Offset Joints, Reclamation, Managing Water in the West, U.S. Department of the Interior, Bureau of Reclamation, Report DSO-07-07, December 2007

45-07 Selahattin Kocaman, thesis: Department of Civil Engineering, Institute of Natural and Applied Sciences, University of Çukurova, Experimental and Theoretical Investigation of Dam Break Problem, 2007. In Turkish. Available on request.

44-07   Saeed-reza Sabbagh-yazdi, Fatemeh Rostami, Habib Rezaei-manizani, and Nikos E. Mastorakis, Comparison of the Results of 2D and 3D Numerical Modeling of Flow over Spillway chutes with Vertical Curvatures, International Journal of Computers, Issue 4, Volume 1, 2007.

43-07    Staša Vošnjak and Jure Mlacnik, Verification of a FLOW-3D mathematical model by a physical hydraulic model of a turbine intake structure, International Conference and exhibition Hydro 2007, 15- 17 October 2007, Granada, Spain. New approaches for a new era: proceedings. [S.l.]: Aqua-Media International Ltd., 2007, 7 str. [COBISS.SI-ID 4991329]

42-07   Merlynn D. Bender, Joseph P. Kubitschek, Tracy B. Vermeyen, Temperature Modeling of Folsom Lake, Lake Natoma, and the Lower American River, Special Report, Sacramento County, California, April 2007

37-07 Heather D. Smith, Flow and Sediment Dynamics Around Three-Dimensional Structures in Coastal Environments, thesis: The Ohio State Unviersity, 2007 (available upon request)

34-07   P.G. Chanel and J.C. Doering, An Evaluation of Computational Fluid Dynamics for Spillway Modeling, 16th Australasian Fluid Mechanics Conference, Gold Coast, Australia, December 2007

29-07   J. Groeneveld, C. Sweeney, C. Mannheim, C. Simonsen, S. Fry, K. Moen, Comparison of Intake Pressures in Physical and Numerical Models of the Cabinet Gorge Dam Tunnel, Waterpower XV, Copyright HCI Publications, July 2007

25-07   Jungseok Ho, Hong Koo Yeo, Julie Coonrod, Won-Sik Ahn, Numerical Modeling Study for Flow Pattern Changes Induced by Single Groyne, IAHR Conference Proc., Harmonizing the Demands of Art and Nature in Hydraulics, IAHR, July 2007, Venice, Italy.

24-07   Jungseok Ho, Julie Coonrod, Todd Marti, Storm Water Best Management Practice- Development of Debris Filtering Structure for Supercritical Flow, EWRI Conference Proc. of World Water and Environmental Resources Congress, ASCE, May 2007, Tampa, Florida.

21-07 David S. Mueller, and Chad R. Wagner, Correcting Acoustic Doppler Current Profiler Discharge Measurements Biased by Sediment Transport, Journal of Hydraulic Engineering, Volume 133, Issue 12, pp. 1329-1336 (December 2007), Copyright © 2007, ASCE. All rights reserved.

19-07   A. Richard Griffith, James H. Rutherford, A. Alavi, David D. Moore, J. Groeneveld, Stability Review of the Wanapum Spillway Using CFD Analysis, Canadian Dam Association Bulletin, Fall 2007

06-07   John E. Richardson, CFD Saves the Alewife- Computer simulation helps the Alewife return to its Mt. Desert Island spawning grounds, Desktop Engineering, July 2007; Hatchery International, July/August 2007

39-06    Dae Geun Kim and Hong Yeun Cho, Modeling the buoyant flow of heated water discharged from surface and submerged side outfalls in shallow and deep water with a cross flow, Environ Fluid Mech (2006) 6: 501. https://doi.org/10.1007/s10652-006-9006-3

38-06   Cook, C., B. Dibrani, M. Richmond, M. Bleich, P. Titzler, T. Fu, Hydraulic Characteristics of the Lower Snake River during Periods of Juvenile Fall Chinook Salmon Migration, 2002-2006 Final Report, Project No. 200202700, 176 electronic pages, (BPA Report DOE/BP-00000652-29)

37-06  Cook CB, MC Richmond, and JA Serkowski, The Dalles Dam, Columbia River: Spillway Improvement CFD Study, PNNL-14768, Pacific Northwest National Laboratory, Richland, WA, 2006. Available upon request

31-06 John P. Raiford and Abdul A. Khan, Numerical Modeling of Internal Flow Structure in Submerged Hydraulic Jumps, ASCE Conf. Proc. 200, 49 (2006), DOI:10.1061/40856(200)49

29-06    Michael C. Johnson and Bruce Savage, Physical and Numerical Comparison of Flow over Ogee Spillway in the Presence of Tailwater, Journal of Hydraulic Engineering © ASCE, December 2006

28-06   Greg Paxson and Bruce Savage, Labyrinth Spillways- Comparison of Two Popular U.S.A. Design Methods and Consideration of Non-standard Approach Conditions and Geometries, International Junior Researcher and Engineer Workshop on Hydraulic Structures, Report CH61/06, Div. of Civil Eng., The University of Queensland, Brisbane, Australia-ISBN 1864998687

22-06   Brent Mefford and Jim Higgs, Link River Falls Passage Investigation – Flow Velocity Simulation, Water Resources Research Laboratory, February 2006

27-06  Jungseok Ho, Leslie Hanna, Brent Mefford, and Julie Coonrod, Numerical Modeling Study for Fish Screen at River Intake Channel, EWRI Conference Proc. of World Water and Environmental Resources Congress, ASCE, May 2006, Omaha, Nebraska.

17-06  Woolgar, Robert and Eddy, Wilmore, Using Computational Fluid Dynamics to Address Fish Passage Concerns at the Grand Falls-Windsor Hydroelectric Development, Canadian Dam Association meeting, Quebec City, Canada October 2006

14-06  Fuamba, M., Role and behavior of surge chamber in hydropower- Case of the Robert Bourassa hydroelectric power plant in Quebec, Canada, Dams and Reservoirs, Societies and Environment in the 21st Century- Berga et al (eds) @ 2006 Taylor & Francis Group, London, ISBN 0 415 40423 1

13-06  D.K.H. Ho, B.W. Cooper, K.M. Riddette, S.M. Donohoo, Application of numerical modelling to spillways in Australia, Dams and Reservoirs, Societies and Environment in the 21st Century—Berga et al (eds) © 2006 Taylor & Francis Group, London, ISBN 0 415 40423 1

4-06 James Dexter, William Faisst, Mike Duer and Jerry Flanagan, Computer Simulation Helps Prevent Nitrification of Storage Reservoir, Waterworld, March 2006, pp 18-24

36-05   P. Coussot, N. Rousell, Jarny and H. Chanson, (2005), Continuous or Catastrophic Solid-Liquid Transition in Jammed Systems, Physics of Fluids, Vol. 17, No. 1, Article 011703, 4 pages (ISSN 0031-9171).

35-05    Dae Geun Kim and Jae Hyun Park, Analysis of Flow Structure over Ogee-Spillway in Consideration of Scale and Roughness Effects by Using CFD Model,  KSCE Journal of Civil Engineering. Volume 9, Number 2, March 2005, pp 161 – 169.

31-05 Frank James Dworak, Characterizing Turbulence Structure along Woody Vegetated Banks in Incised Channels: Implications for Stream Restoration, thesis: The University of Tennessee, Knoxville, December 2005 (available upon request)

29-05 Gessler, Dan and Rasmussen, Bernie, Before the Flood, Desktop Engineering, October 2005

25-05   Jorge D. Abad and Marcelo H. Garcia, Hydrodynamics in Kinoshita-generated meandering bends- Importance for river-planform evolution, 4th IAHR Symposium on River, Coastal and Estuarine Morphodynamics, October 4-7, 2005, Urbana, Illinois

23-05 Kristiansen T., Baarholm R., Stansberg C.T., Rørtveit G.J. and Hansen E.W., Steep Wave Kinematics and Interaction with a Vertical Column, Presented at The Fifth International Symposium on Ocean Wave Measurement and Analysis (Waves 2005), Spain, July, 2005

16-05 Dan Gessler, CFD Modeling of Spillway Performance, Proceedings of the 2005 World Water and Environmental Resources Congress (sponsored by Environmental and Water Resources Institute of the American Society of Civil Engineers), May 15-19, 2005, Anchorage, Alaska

12-05 Charles Ortloff, The Water Supply and Distribution System of the Nabataean City of Petra (Jordan), 300 BC- AD 300, Cambridge Archaeological Journal 15:1, 93-109

33-04    Jose Carlos C. Amorim, Cavalcanti Renata Rodrigues, and Marcelo G. Marques, A Numerical and Experimental Study of Hydraulic Jump Stilling Basin, Advances in Hydro-Science and Engineering, Volume VI, Presented at the International Conference on Hydro-Science and Engineering, 2004

23-04   Jose F. Rodriguez, Fabian A. Bombardelli, Marcelo H. Garcia, Kelly Frothingham, Bruce L. Rhoads and Jorge D. Abad, High-Resolution Numerical Simulation of Flow Through a Highly Sinuous River Reach, Water Resources Management, 18:177-199, 2004.

18-04   John Richardson and Douglas Dixon, Modeling the Hydraulics Zone of Influence of Connecticut Yankee Nuclear Plants Cooling Water Intake Structure, a chapter in The Connecticut River Ecological Study (1965-1973) Revisited: Ecology of the Lower Connecticut River 1973-2003, Paul M. Jacobson, Douglas A. Dixon, William C. Leggett, Barton C. Marcy, Jr., and Ronald R. Massengill, editors; Published by American Fisheries Society, Publication date: November 2004, ISBN 1-888569-66-2

10-04   Bruce Savage, Kathleen Frizell, and Jimmy Crowder, Brains versus Brawn- The Changing World of Hydraulic Model Studies

7-04   C. B. Cook and M. C. Richmond, Monitoring and Simulating 3-D Density Currents and the Confluence of the Snake and Clearwater Rivers, Proceedings of EWRI World

24-03  David Ho, Karen Boyes, Shane Donohoo, and Brian Cooper, Numerical Flow Analysis for Spillways, 43rd ANCOLD Conference, Hobart, Tasmania, 24-29 October 2003

15-03   Ho, Dr K H, Boyes, S M, Donohoo, S M, Investigation of Spillway Behaviour Under Increased Maximum Flood by Computational Fluid Dynamics Technique, Proc Conf 14th Australian Fluid Mechanics, Adelaide, Australia, December 2001, 577-580

14-03   Ho, Dr K H, Donohoo, S M, Boyes, K M, Lock, C C, Numerical Analysis and the Real World- It Looks Pretty, but is It Right?, Proceedings of the NAFEMS World Congress, May 2003, Orlando, FL

13-03 Brethour, J. M., Sediment Scour, Flow Science Technical Note (FSI-03-TN62)

26-02   Sungyul Yoo, Kiwon Hong and Manha Hwang, A 3-dimensional numerical study of flow patterns around a multipurpose dam, 2002 Hydroinformatics Conference, Cardiff, Wales

23-02   Christopher B. Cook, Marshall C. Richmond, John A. Serkowski, and Laurie L. Ebner, Free-Surface Computational Fluid Dynamics Modeling of a Spillway and Tailrace- Case Study of The Dalles Project, Hydrovision 2002, 29 July -†2 Aug, 2002 Portland, OR

13-02   Efrem Teklemariam, Brian W. Korbaylo, Joe L. Groeneveld & David M. Fuchs, Computational Fluid Dynamics- Diverse Applications In Hydropower Project’s Design and Analysis, June 11-14, 2002, CWRA 55th Annual Conference, Winnipeg, Manitoba, CA

12-02   Snorre Heimsund, Ernst Hansen, W Nemec, Computational 3-D Fluid Dynamics Model for Sediment Transport, Erosion, and Deposition by Turbidity Currents, 16th International Sedimentological Congress Abstract Volume (2002) XX-XX

9-02   D. T. Souders & C. W. Hirt, Modeling Roughness Effects in Open Channel Flows, Flow Science Technical Note (FSI-02-TN60), May 2002

47-01    Fabián A. Bombardelli and Marcelo H. García, Three-dimensional Hydrodynamic Modeling of Density Currents in the Chicago River, Illinois, CIVIL ENGINEERING SERIES, UILU-ENG-01-2001 Hydraulic Engineering Series No. # 68, ISSN: 0442-1744, 2001

44-01   Christopher B. Cook and Marshall C. Richmond, Simulation of Tailrace Hydrodynamics Using Computational Fluid Dynamics Models, Report Number: PNNL-13467, May 2001

40-01 Joe L. Groeneveld, Kevin M. Sydor and David M. Fuchs (Acres Manitoba Ltd., Winnipeg, Manitoba, Canada) and Efrem Teklemariam and Brian W. Korbaylo (Manitoba Hydro, Winnipeg, Manitoba, Canada), Optimization of Hydraulic Design Using Computational Fluid Dynamics, Waterpower XII, July 9-11, 2001, Salt Lake City, Utah

39-01   Savage, B.M and Johnson, M.C., Flow over Ogee Spillway- Physical and Numerical Model Case Study, Journal of Hydraulic Engineering, ASCE, August 2001, pp. 640-649

38-01   Newell, Carter, Sustainable Mussel Culture- A Millenial Perspective, Bulletin of the Aquaculture Association of Canada, August 2001, pp 15-21

36-01   Diane L. Foster, Ohio State University, Numerical Simulations of Sediment Transport and Scour Around Mines, paper presented to the Office of Naval Research, Mine Burial Prediction Program, 2001

35-01 Heather D. Smith, Diane L. Foster, Ohio State University, The Modeling of Flow Around a Cylinder and Scour Hole, Poster prepared for the Office of Naval Research, Mine Burial Prediction Program, 2002

28-01   Brethour, J.M., Transient 3D Model for Lifting, Transporting, and Depositing Solid Material, Proc. 3rd Intrn. Environmental Hydraulics, Dec. 5-8, 2001, Tempe, AZ

25-01  Yuichi Kitamura, Takahiro Kato, & Petek Kitamura, Mathematical Modeling for Fish Adaptive Behavior in a Current, Proceedings of the 2001International Symposium of Environmental Hydraulics, Chigaski R&D Center

22-01 C. R. Ortloff, D. P. Crouch, The Urban Water Supply and Distribution System of the Ionian City of Ephesos in the Roman Imperial Period, CTC/United Defense Journal of Archeological Science (2001), pp 843-860

13-01 I. Lavedrine, and Darren Woolf, ARUP Research and Development, Application of CFD Modelling to Hydraulic Structures, CCWI 2001, Leicaster United Kingdom, 3-5 September 2001, De Montfort University

4-01 Rodriguez, Garcia, Bombardelli, Guzman, Rhoads, and Herricks, Naturalization of Urban Streams Using In-Channel Structures, Joint Conference on Water Resources Engineering and Water Resources Planning and Management, ASCE, July 30-August 2, 2000, Minneapolis, Minnesota

27-00    Tony L. Wahl, John A. Replogle, Brain T. Wahlin, and James A. Higgs, New Developments in Design and Application of Long-Throated Flumes, 2000 Joint Conference on Water Resources Engineering and Water Resources Planning & Management, Minneapolis, Minnesota, July 30-August 2, 2000.

5-00   John E. Richardson and Karel Pryl, Computer Simulation Helps Prague Modernize and Expand Sewer System, Water Engineering and Management, June, 2000, pp. 10-13; and in Municipal World, June, 2000, pp. 19-20,30

3-00 Efrem Teklemariam and John L. Groeneveld, Solving Problems in Design and Dam Safety with Computational Fluid Dynamics, Hydro Review, May, 2000, pp.48-52

1-00 Scott F. Bradford, Numerical Simulation of Surf Zone Dynamics, Journal of Waterway, Port, Coastal and Ocean Engineering, January/February, 2000, pp.1-13

9-99 John E. Richardson and Karel Pryl, Computational Fluid Dynamics, CE News, October, 1999, pp. 74-76

4-99 J. Groeneveld, Computer Simulation Leads to Faster, Cheaper Options, Water Engineering & Management magazine, pp.14-17, June 1999

16-98 C. R. Ortloff, Hydraulic Analysis of a Self-Cleaning Drainage Outlet at the Hellenistic City of Priene, Journal Archaeological Science, 25, 1211-1220, Article No. as980292, 1998

13-98 J. F. Echols, M.A. Pratt, K. A. Williams, Using CFD to Model Flow in Large Circulating Water Systems, Proc. PowerGen International, Orlando, FL, Dec. 9-11, 1998.

12-98 K. A. Williams, I. A. Diaz-Tous, P. Ulovg, Reduction in Pumping Power Requirements of the Circulation Water (CW) System at TU Electric’s Martin Lake Plant Using Computation Fluid Dynamics (CFD), ASME Mechanical Engineering Magazine, Jan. 1999

8-98 D. Hrabak, K. Pryl, J. Richardson, Calibration of Flowmeters using FLOW-3D Software, Hydroinform, a.s., Prague, CTU Prague, Flow Science Inc, USA, proceedings from the 3rd International Novatech Conference, Lyon, France, May 4-6, 1998

16-96 E. J. Kent and J.E. Richardson, Three-Dimensional Hydraulic Analysis for Calculation of Scour at Bridge Piers with Fender Systems, Earth Tech, Concord, NK and Flow Science Inc, Los Alamos, NM report, December 1996

12-96 J. E. Richardson, Control of Hydraulic Jump by Abrupt Drop, XXVII IAHR Congress, Water for a Changing Global Community, San Francisco, August 10, 1997

6-96 Y. Miyamoto, A Three-Dimensional Analysis around the Open Area of a Tsunami Breakwater, technical report, SEA Corporation, Tokyo, Japan, to be presented at the HYDROINFORMATICS 96 Conference, Zurich, Switzerland, Sept. 11-13, 1996

4-95 J. E. Richardson, V. G. Panchang and E. Kent, Three-Dimensional Numerical Simulation of Flow Around Bridge Sub-structures, presented at the Hydraulics ’95 ASCE Conference, San Antonio, TX, Aug. 1995

3-95 Y. Miyamoto and K. Ishino, Three Dimensional Flow Analysis in Open Channel, presented at the IAHR Conference, HYDRA 2000, Vol. 1, Thomas Telford, London, Sept. 1995

16-94 M. S. Gosselin and D. M. Sheppard, Time Rate of Local Scour, proceedings of ASCE Conf. on Water Resources Engineering, San Antonio, TX, August 1994

8-94 C. W. Hirt, Weir Discharges and Counter Currents, Flow Science report, FSI-94-00-3, to be presented at the Hydroinformatics Conference, IHE Delft, The Netherlands, Sept. 1994

7-94 C. W. Hirt and K. A.Williams, FLOW-3D Predictions for Free Discharge and Submerged Parshall Flumes, Flow Science Technical Note #40, August 1994 (FSI-94-TN40)

11-93 K. Ishino, H. Otani, R. Okada and Y. Nakagawa, The Flow Structure Around a Cylindrical Pier for the Flow of Transcritical Reynolds Number, Taisei Corp., Honshu Shikoku Bridge Authority, Akashi Kaikyo Ohashi Substructure Construction, Proc. XXV, Congress Intern. Assoc. Hydraulic Res., V, 417-424 (1993) Tokyo, Japan

6-87 J.M. Sicilian, FLOW-3D Model for Flow in a Water Turbine Passage, Flow Science report, July 1987 (FSI-87-36-1)

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양질의 CFD 교육을받는 것은 토목, 기계, 전산 및 생화학 공학 세계에서 매우 중요합니다. 최첨단 시각화 및 고성능 컴퓨팅 기능을 제공하는 정확하고 다재다능한 CFD 소프트웨어는 학생들의 학습 경험을 향상시키고 CFD 전문가가 될 수 있도록 도와줍니다. 

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연락처 : 02-2026-0455
Hydraulic Jump Simulation | FLOW-3D
Hydraulic Jump Simulation | FLOW-3D


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연구 적용 사례 : 세종대학교 항공우주공학과 – 심형섭교수님


KNSB 고체모터를 이용한 중형과학로켓추진기관설계

박지호*† ․ 최현수* ․ 최은교* ․ 방영웅* ․ 최현창*

Design of KNSB Solid Motor for Sounding Rocket Propulsion System
Jiho Park† ․ Hyunsoo Choi ․ Eungyo Choi* ․ Yeongwoong Bang* ․ Hyunchang Choi* ․ Hyungsub Sim**

ABSTRACT
This is the final report of the Aerospace Engineering Research 1 class in the Department of
Aerospace Engineering, Sejong University. This project started out of a curiosity about whether it is
possible to design a medium-sized sounding rocket propulsion system even with the composition of
the KNSB propellant. Based on the theoretical knowledge learned from the Aerospace Engineering
Research 1 class, ballistic analysis was performed using Matlab, PEP and Flow-3D, and a trajectory
program was created to visually check the performance of the designed propulsion system.

초 록
본문은 세종대학교 항공우주공학과 항공우주공학연구1 수업의 최종보고서이다. ‘KNSB 추진제 조성으로도 중형과학로켓 추진기관을 설계할 수 있는가’에 대한 궁금증으로부터 시작된 프로젝트로, 그레인의 형상 선정을 시작으로 내탄도 해석을 수행한 과정을 담았다. 항공우주공학연구1 수업으로부터 배운 이론 지식을 바탕으로 Matlab과 PEP를 활용하여 내탄도 해석을 수행하였으며, 설계한 추진기관의 성능이 어느 정도인지 육안으로 확인할 수 있도록 궤적 프로그램을 만들었다. 또한 ㈜에스티아이씨앤디로부터 전산유체해석 프로그램인 Flow-3D 라이센스를 제공받아 이를 활용하여 설계한 추진기관의 해석이 올바른지 전산해석을 수행하였고 교차 검증하였다.

Key Words: KNSB(질산칼륨-솔비톨), Combustion Analysis(내탄도해석), Sounding Rocket(과학로켓),
Numerocal Analysis(수치해석), PEP, Flow-3D, CFD(Computational Fluid Dynamics)

KNSB 고체모터를 이용한 중형과학로켓추진기관설계
KNSB 고체모터를 이용한 중형과학로켓추진기관설계