Fig 2(b) Observed velocity field for aspect ratio 0.25(Sukhodolov 2002)

고정 베드의 불침투성 토양에서 흐름 패턴의 수치 시뮬레이션

NUMERICAL SIMULATION OF FLOW PATTERN IN SERIES OF IMPERMEABLE GROYNES IN FIXED BED

Kafle, Mukesh Raj1
1Asst. Professor, Department of Civil Engineering, Institute of Engineering, Pulchowk Campus, Nepal
Email: mkafle@pcampus.edu.np

Abstract

This paper presents a numerical simulation of recirculating flow patterns in groyne fields. Moreover, it entails the concept determination of proper spacing of vertical unsubmerged and impermeable groynesin seriesto control the bank erosion. Flow pattern between the groynes varies along their space. The flow in groyne field may significantly affect the flow change, bed change, bank erosion and condition of habitat. In this regard, an assessment of flow along the space of groynes will yield important data needed to diversify the object of groyne installation. So, knowledge about determination of the proper spacing of groynes in groyne field is important. Space of vertical groynes was set from 1.5 to 10 times the length of groynes. The velocity field between groynes was simulated by using Computational Fluid Dynamics (CFD) model Nays 2D. Simulated velocity field was compared with existing experimentaldata for the same parameter, which agreed satisfactorily. Based on simulated results,the optimal spacing of vertical groynes to control the bank erosion was recommended.

이 논문은 groyne 필드에서 재순환 흐름 패턴의 수치 시뮬레이션을 제공합니다. 더욱이, 그것은 제방 침식을 제어하기 위해 수직 비침수 및 불침투성 그로이네신 시리즈의 적절한 간격의 개념 결정을 수반합니다. groynes 사이의 흐름 패턴은 공간에 따라 다릅니다. groyne field의 흐름은 흐름 변화, 하상 변화, 제방 침식 및 서식지 상태에 중대한 영향을 미칠 수 있습니다. 이와 관련하여, groyne 공간을 따른 흐름의 평가는 groyne 설치 대상을 다양화하는 데 필요한 중요한 데이터를 산출할 것입니다. 따라서, groyne field에서 groyne의 적절한 간격 결정에 대한 지식이 중요합니다. 수직 여백의 간격은 여아 길이의 1.5배에서 10배 사이로 설정하였다. groyne 사이의 속도장은 CFD(Computational Fluid Dynamics) 모델 Nays 2D를 사용하여 시뮬레이션되었습니다. 시뮬레이션된 속도장은 동일한 매개변수에 대해 기존 실험 데이터와 비교되었으며 만족스럽게 일치했습니다. 모의 결과를 바탕으로 제방 침식을 억제하기 위한 최적의 수직 제방 간격을 제안하였다.

  1. Introduction
    Spur dikes or groynes are used to protect river banks from erosion and also keep the channel
    navigable.Depending upon the flow characteristics, spur-dikes may be classified as submerged and unsubmerged. Also, based on the permeability, spur dikes are further classified as permeable and
    impermeable. Herein, un-submerged !impermeable spur dikes are dealt. These structures are built from the river bank into the stream flow and usually built in group. Construction of groyne against the flow causes significant changes in flow pattern in channel. Those changes may result in scour phenomenon around groynes which may lead structure instability and changes in river morphology. Moreover, in series of groynes, spacing of groynes leads different types of recirculating flow patterns.Therefore, investigating the characteristics of flow pattern around groynes have been a great interest in river engineering. Numerous researchers like Sukhodolov et al. (2002), Hao Zhang et al.(2009), Beheshti (2010), Duan (2009), Naji(2010), Karami(2011) made a variety of experiments in order to determine the flow pattern around groynes. Most of these researchers studied effect of single groyne, while using series of groynes is more effective in protection of rivers. Besides experimental studies, variety of CFD models have been developed for computing flow pattern around hydraulic structures; like Fluent, Flow 3D, Nays 2D, Nays CUBE and SSIIM. In this study, Nays 2D numerical modelling has been used to investigate flow and recirculating pattern around a series of groynes and streamlines including components of velocities.
  1. Flow pattern in groyne fields
    Under conditions where the groynes are not submerged, the groyne fields are not really part of the wetted cross section of a river. Because of that, the flow pattern in the groyne-field is not directly the result of the discharge in the main channel. Reducing the main stream velocity has no effect on the flow pattern itself, whereas lowering the water level does (Uijttewaal et al.2001). Moreover, the flow pattern inside a groyne field may change with the change of its geometry, location along the river (inner curve, outer curve, or straight part), and/ or the groynes orientation( Przedwojski et al.1995). However, there is an indirect effect of the discharge on the flow pattern in the groyne field. Because of the flow that is diverted from the main channel into the groyne fields, water flows into the groyne field with low velocity through the downstream half of the interfacial section between the groyne field and the main channel. This water flows back to the main channel through a small width of, just downstream the upstream groyne of the groyne field ( Termes et al.1991). Flow separates on a groyne head and forms a secondary flow represented by a large scale vortex with a vertical axis of rotation called primary gyre. Deflection of the flow inside the groyne field by banks and upstream groynes leads to the development of a secondary gyre with an opposite direction of rotation to the primary gyre. Location, mutual interactions, and energy exchange between gyres are the factors that create a specific recirculation pattern, and, consequently assuming correspondence with sedimentation processes, they define deposition patterns.
  2. Model Formulation
    The CFD model selected for this study is the publically available software NAYS 2D (iRIC 2.0), which is an analytical solver for calculation of unsteady two-dimensional plane flow and riverbed deformation using boundary-fitted coordinates within general curvilinear coordinates. A numerical channel of length 8.0m and width 0.9m was created with grid size of 0.01m im stream wise and 0.03m in cross stream directions. Groynes or spur dikes of length 0.15 and width 0.01m were chosen in series. Groyne field with various aspect ratio (b/x) 0.7, 0.25, 0.17, 0.125 and 0.10, where b=length of spur dike, x=spacing of two dikes. Discharge of 0.0175 m3 /s was applied. For boundary conditions, water surface at downstream and velocity at upstream were considered as uniform flow. Relaxation coefficient for water surface calculation was considered as 0.8. For the finite-difference method, the CIP method was applied to the advection terms in equations of motion. For the turbulent field calculation, Constant eddy viscosity, Zero-equation model and k-G models were applied and compared. The model!s accuracy in predicting the velocity magnitudes is evaluated using statistical parameters- mean absolute error (MAE), mean square error(MSE), and root mean square error (RMSE). The comparison of results shows the importance of selecting an appropriate turbulence model in simulating flow field around a spur dike. From the comparison, k-I model is found superior over zero energy model and eddy viscosity model. So, k-I model is chosen as appropriate turbulence closure model.
  3. Model!s Validation
    The capability of CFD model Nays 2D to simulate the velocity field and recirculation pattern in groyne field was compared with experimental data of laboratory experiments by Sukhodolov et al. (2002). The numerical simulation was validated for aspect ratio (R=b/x=0.7) and R=0.25. For aspect ratio R=0.7, one gyre system occupies the whole area of the groyne field. The areas with lower-than-average velocity values are clearly seen in the central part of the gyre and near its corners. Velocities increase towards the margins of the gyre. For aspect ratio R=0.25, two gyre velocity fields were observed in the groyne field. In the downstream part of the groyne field a large gyre, covering two-thirds of the area is clearly visible. The left part(upstream) contains second gyre rotating much more slowly and in the direction opposed to the primary gyre. The simulated and observed velocity field pattern and gyre found satisfactorily agreed. Now, after validation, the model was used for further analysis of velocity field for various aspect ratios.
Fig 2(b) Observed velocity field for aspect ratio 0.25(Sukhodolov 2002)
Fig 2(b) Observed velocity field for aspect ratio 0.25(Sukhodolov 2002)
  1. Results and Discussions
    The calibrated model was applied to five different cases of un-submerged and impermeable groyne fields with aspect ratios R=0.70,0.25,0.17,0.125 & 0.10 and flow pattern was numerically simulated. For aspect ratio R=0.7 i.e x/b=1.5, Fig 1(a) only one lateral primary gyre was formed inside the groyne field. The circulation pattern in this case is distinguished by the main flow that is deflected outside the groyne field. The developed primary gyre prevents the main flow from penetrating the groyne field. Therefore, this pattern is desirable for navigation purposes as a continuous deep channel is maintained along the face of the groyne field. Simulated velocity pattern satisfactorily agrees with the observed velocity field Fig 1(b) for the same aspect ratio by Sukhodolov (2002). The spacing of the groyne was further increased maintaining aspect ratio R= 0.25 i. e x/b=4 Fig 2(a) and flow pattern inside the groyne field was simulated. In this case, in the downstream part of the groyne field, a primary gyre occupying almost two-third area was formed. In addition, deflection of the flow inside the groyne field by banks and upstream groynes leads to the development of a secondary gyre with an opposite direction of rotation to the primary gyre covering almost one-third part of the groyne field. Likewise in the first case, the main current is maintained deflected outside the groyne field. Simulated velocity pattern satisfactorily agrees with the observed velocity field Fig 2(b) for the same aspect ratio by Sukhodolov (2002). The spacing of the groyne was further increased maintaining aspect ratio R=0.17 i.e x/b=6. In this case the flow pattern was similar to the aspect ratio R=0.25. The spacing of the groynes was further increased maintaining aspect ratio R=0.125 i. e x/b=8. In this case, similar to the previous scenarios two longitudinal gyres but with different positions are formed. The main current is directed in to the groyne field (Fig 3) creating a much more stronger eddy near the upstream groyne and greater turbulence along the upstream face and at the groyne lower head. As the spacing between groynes increased maintaining aspect ratio R=0.10 i. e x/b=10 (Fig 4), still primary and secondary gyres are generated. The formed gyres deflect the main flow thus preventing to enter in to the groyne field in upstream part. However, in the downstream of the primary gyre and just upstream of the second groyne, the flow attacks the bank directly. The resultant velocity profiles at the deflected region y/b=3 were plotted and how the spacing of second groyne affect the result was analyzed. Spacing of groynes makes little change in upstream resultant velocity. However, in the deflected region, its effect is significant. Higher value of spacing of groyne leads higher average deviation in resultant velocity. For aspect ratio R=0.7, the average deviation estimated as 0.02%. In the case of aspect ratio R=0.25, this value was reached to 1.57%. Further increment of spacing i. e decreasing the aspect ratio R=0.17, average deviation was found 3.82%. For the aspect ratio R=0.125, that value was estimated as 4.16%.
  2. Conclusions
    Geometry of the groyne fields; width and length of the groyne field mainly cause the specific flow patterns including number and shape of eddies or gyres. Eddies developed inside the groyne field deflects the main flow preventing it entering into the dead zone. An aspect ratio close to unity gives rise to a single eddy. A smaller aspect ratio (higher spacing between groynes) gives room to two stationary eddies, a large one called primary eddy, in the downstream part of the groyne field, and a smaller secondary eddy emerges near the upstream groyne. The extreme long groyne field -case of length to width ratio of larger thaneight shows penetration of main flow into the groyne field. The two eddies remain in a relatively stable position, while the main flow zone starts to penetrate into groyne field further downstream. In all cases, there is an eddy detaches from the upstream groyne tip that travels along the main channel groyne field interface and eventually merges with the primary eddy. The simulated results indicate that the spacing of groynes or spur dikes from the controlling of bank erosion point of view should be limited within six times the length of groyne.
Fig 3 Computed velocity field for aspect ratio 0.125
Fig 3 Computed velocity field for aspect ratio 0.125
Fig 4 Computed velocity field for aspect ratio 0.10
Fig 4 Computed velocity field for aspect ratio 0.10
Fig 5 Resultant velocity profiles at y/b=3
Fig 5 Resultant velocity profiles at y/b=3
Fig 5 Resultant velocity profiles at y/b=3
Fig 5 Resultant velocity profiles at y/b=3

References

  1. Holtz, K.P  Numerical simulation of recirculating flow at groynes.Å Computer Methods in Water Resources, Vol 2, No 2 (1991).
  2. Hossein, Bassar; Abdollah, Ardeshir; Hojat, Karami.  Numerical simulation of flow pattern around spur dikes series in rigid bed.Å 9th international congress on civil engineering, May 8- 10,2012, Isfahan University of Technology (IUT) , Isfahan, Iran (2012).
  3. Kang, J.G; Yeo, H.K; Kim,S.J An experimental study on a characteristics of flow around groyne area by install conditions.Å www.SciRP.org/journal/eng(2012).
  4. Shimizu,Y; Nelson,JIntroduction of Nays solver in iRIC.Åwww.i-ric.org(2012).
  5. Sukhodolov, A. Uijttewaal, W. S. J., and Engelhardt, C. On the correspondence between morphological and hydro dynamical patterns of groyne fields.Å Earth Surf. Processes Landforms, 27(3) (2002).
  6. Uijttewall, W.S.J; Lehman,D; VanMazijk,A.  Exchange process between a river and its groyne fields-model experiments.Å Journal of Hydraulic Engineering, ASCE, 127(11) (2001).
  7. Uijttewall, W.S.J Groyne field velocity patterns determined with particle tracking
    velocimetryÅ.28th IAHR congress, Graz, Austria (1999).
  8. Yossef, Mohamed  Flow details near groynes: Experimental investigations.Å Journal of Hydraulic Engineering, ASCE, 137 (2011).
Figura 4.5 – Superfície de contorno de velocidades a 3,9 m do piso após 20 s de acionamento da motosserra.

전기톱 절단 시험실에서 배기 시스템의 CFD 시뮬레이션

CFD Simulation of an exhaust system in chainsaw cutting test room

Área de Concentração: Energia e Fenômenos de Transporte
Orientador: Prof. Diogo Elias da Vinha Andrade
Comissão de Avaliação:
Profa
. Letícia Jenisch Rodrigues
Prof. Francis Henrique Ramos França
Prof. Paulo Smith Schneider

Abstract

The objective of the present work is to improve an exhaust system for a chain saw
cutting test room through a fluid dynamic computational simulation (CFD). The purpose of the
designed system is to remove combustion gases, such as carbon monoxide (CO), which is
extremely toxic, colourless and inodorous. The current system consists of a set of exhaust fans,
a hood and an insufflation set. From experimental tests, the input data of the simulation were
collected to define the variables and boundary conditions such as volumetric flow of CO, its
temperature and density and the supply of fresh air in the room. The necessary means of
instrumentation are presented so that it is possible to obtain the correlation with the results of
the simulation and, once validated, a study of mesh refinement was carried out. With this, the
possible solutions to the problem are evaluated through a case study involving the geometry of
the hood and the exhaust and insufflation systems. By changing the hood geometry, the most
satisfactory result was obtained for the problem, as it was shown to be able to remove all CO
from the room, respecting the proposed operational limits.

현재 연구의 목적은 유체 역학 계산 시뮬레이션(CFD)을 통해 체인 톱 절단 시험실의 배기 시스템을 개선하는 것입니다. 설계된 시스템의 목적은 매우 유독하고 무색이며 냄새가 나는 일산화탄소(CO)와 같은 연소 가스를 제거하는 것입니다. 현재 시스템은 배기 팬 세트, 후드 및 흡입 세트로 구성됩니다. 실험 테스트에서 시뮬레이션의 입력 데이터는 CO의 체적 유량, 온도 및 밀도, 실내의 신선한 공기 공급과 같은 변수 및 경계 조건을 정의하기 위해 수집되었습니다. 시뮬레이션 결과와의 상관관계를 얻을 수 있도록 필요한 계측 수단을 제시하고 검증 후 메쉬 미세화 연구를 수행했습니다. 이를 통해 후드의 기하학적 구조와 배기 및 흡입 시스템과 관련된 사례 연구를 통해 문제에 대한 가능한 솔루션을 평가합니다. 후드 형상을 변경함으로써 제안된 작동 한계를 준수하면서 실내에서 모든 CO를 제거할 수 있는 것으로 나타났기 때문에 문제에 대해 가장 만족스러운 결과를 얻었습니다.

Keywords

carbon monoxide, exhaust system, CFD simulation.

Figura 3.2 – Geometria simplificada da sala de testes da primeira versão.
Figura 3.2 – Geometria simplificada da sala de testes da primeira versão.
Figura 3.4 – Velocidade nos sensores de velocidade para verificar independência de malha para cada refino após 20 s do acionamento da motosserra.
Figura 3.4 – Velocidade nos sensores de velocidade para verificar independência de malha para cada refino após 20 s do acionamento da motosserra.
Figura 3.4 – Velocidade nos sensores de velocidade para verificar independência de malha para cada refino após 20 s do acionamento da motosserra.
Figura 3.4 – Velocidade nos sensores de velocidade para verificar independência de malha para cada refino após 20 s do acionamento da motosserra.
Figura 3.5 – Vista em detalhe da coifa e os elementos que a compõe.
Figura 3.5 – Vista em detalhe da coifa e os elementos que a compõe.
Figura 3.6 – Geometrias das versões simuladas do Teste de Casos.
Figura 3.6 – Geometrias das versões simuladas do Teste de Casos.
Figura 4.1 – Concentração de CO medida pelos sensores da simulação.
Figura 4.1 – Concentração de CO medida pelos sensores da simulação.
Figura 4.2 – Plano indicando os três cortes realizados na simulação para as superfícies de contorno sendo (1) a altura do escape da máquina, (2) a altura dos detectores de CO e (3) a altura dos exaustores
Figura 4.2 – Plano indicando os três cortes realizados na simulação para as superfícies de contorno sendo (1) a altura do escape da máquina, (2) a altura dos detectores de CO e (3) a altura dos exaustores
Figura 4.3 – Superfície de contorno de velocidades a 1,3 m do piso após 20 s de acionamento da motosserra.
Figura 4.3 – Superfície de contorno de velocidades a 1,3 m do piso após 20 s de acionamento da motosserra.
Figura 4.4 – Superfície de contorno de velocidades a 1,5 m do piso após 20 s de acionamento da motosserra.
Figura 4.4 – Superfície de contorno de velocidades a 1,5 m do piso após 20 s de acionamento da motosserra.
Figura 4.5 – Superfície de contorno de velocidades a 3,9 m do piso após 20 s de acionamento da motosserra.
Figura 4.5 – Superfície de contorno de velocidades a 3,9 m do piso após 20 s de acionamento da motosserra.
Figura 4.6 – Superfície de contorno de massas específicas a 1,3 m do piso após 20 s de acionamento da motosserra.
Figura 4.6 – Superfície de contorno de massas específicas a 1,3 m do piso após 20 s de acionamento da motosserra.
Figura 4.7 – Superfície de contorno de massas específicas a 1,5 m do piso após 20 s de acionamento da motosserra.
Figura 4.7 – Superfície de contorno de massas específicas a 1,5 m do piso após 20 s de acionamento da motosserra.
Figura 4.8 – Superfície de contorno de massas específicas a 3,9 m do piso após 20 s de acionamento da motosserra.
Figura 4.8 – Superfície de contorno de massas específicas a 3,9 m do piso após 20 s de acionamento da motosserra.
Figura 4.9 – Volume total de monóxido ao longo do tempo na sala.
Figura 4.9 – Volume total de monóxido ao longo do tempo na sala.
Figura 4.9 – Vazão volumétrica de CO ao longo do tempo através da superfície de controle. As linhas contínuas representam curvas de ajuste aos dados simulados.
Figura 4.9 – Vazão volumétrica de CO ao longo do tempo através da superfície de controle. As linhas contínuas representam curvas de ajuste aos dados simulados.

REFERENCIAS

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Fig. 1. General view of the Ilarion Dam (image from YouTube https://www.youtube.com/watch?v=KKm203f0r_k)

Plunge pool rehabilitation with prismatic concrete elements – case study and physical model of Ilarion dam in Greece

Abstract

The 130 m high Ilarion Dam is built on the Aliakmon River in northern Greece. The dam has two spillways with ski jumps at their ends and a plunge pool to cushion the impact of the jets. This pool has suered signicant scouring during several oods in recent years. In order to determine a reliable protection measure, a 1:55 scale model and a numerical model with FLOW-3D® were created. The hydrodynamic behaviour of the ow in the plunge pool and in the spillways as well as the trajectory of the jets could be determined. The numerical modelling showed that it was probably not the impact of the jet that caused the most of the scouring but the resulting recirculation current. The ow in the plunge pool is thus highly asymmetric and a vortex forms when only one of the two spillways is operating. This vortex results in an eective ow rate in the basin that is three times greater than the ow rate from the spillway. A simple solution to this problem is to operate both spillways symmetrically. A modication of the geometry of the ski jump bucket to increase the impact surface of the jet and thus reduce its scouring potential was also investigated.

Auteur(e)s : Romain Van Mol
Encadrement : Dr Giovanni De Cesare 1

1 Plateforme de Constructions Hydrauliques (PL-LCH), EPFL

130m 높이의 Ilarion 댐은 북부 그리스의 Aliakmon 강에 건설되었습니다. 댐에는 끝에 스키 점프가 있는 2개의 여수로와 제트기의 충격을 완충하는 플런지 풀이 있습니다. 이 웅덩이는 최근 몇 년 동안 상당한 수질 피해를 입었습니다. 신뢰할 수 있는 보호 조치를 결정하기 위해 1:55 스케일 모델과 FLOW-3D®를 사용한 수치 모델이 생성되었습니다. 플런지 풀과 여수로에서의 유류의 유체역학적 거동과 제트의 궤적이 결정될 수 있었습니다. 수치 모델링은 아마도 대부분의 정련을 일으킨 제트의 영향이 아니라 결과적인 재순환 전류임을 보여주었습니다. 따라서 플런지 풀의 흐름은 매우 비대칭이며 두 개의 배수로 중 하나만 작동할 때 소용돌이가 형성됩니다. 이 와류는 배수로의 유량보다 3배 더 큰 유역의 유효 유량을 초래합니다. 이 문제에 대한 간단한 해결책은 양쪽 배수로를 대칭적으로 운영하는 것입니다. 제트기의 충돌 표면을 증가시키고 이에 따라 세척 가능성을 줄이기 위해 스키 점프 버킷의 기하학적 구조를 수정하는 것도 조사되었습니다.

Fig. 1. General view of the Ilarion Dam (image from YouTube https://www.youtube.com/watch?v=KKm203f0r_k)
Fig. 1. General view of the Ilarion Dam (image from YouTube
Fig. 2. Topography before the 2013 flood (left) and after the 2015 flood (right)
Fig. 2. Topography before the 2013 flood (left) and after the 2015 flood (right)
Fig. 3. Top view of the velocity vectors at 293.5 m.a.s.l. for a total discharge of 500 m3 /s with only one spillway operational (left) and with two spillways operational (right); the water is coloured according to its velocity in m/s
Fig. 3. Top view of the velocity vectors at 293.5 m.a.s.l. for a total discharge of 500 m3 /s with only one spillway operational (left) and with two spillways operational (right); the water is coloured according to its velocity in m/s

Conclusions

The two spillways of the Ilarion Dam in Greece were studied by numerical modelling with FLOW-3D®. The study focused on the hydrodynamic behaviour of the flow in the plunge pool. It was found that the recirculation current in the plunge pool is a problematic phenomenon. This creates an effective discharge more than 3 times larger than the one expected. A simple and cost-effective solution is to operate the spillways symmetrically. However, this may not always be possible for any given flood discharge. Indeed, the opening range of the gates may be limited for reasons of operability or vibration of the gates.

Fig. 3. Experimental angled top-view setup for laser welding of zinc-coated steel with a laser illumination.

Effect of zinc vapor forces on spattering in partial penetration laser welding of zinc-coated steels

Yu Hao a, Nannan Chen a,b, Hui-Ping Wang c,*, Blair E. Carlson c, Fenggui Lu a,*
a Shanghai Key Laboratory of Materials Laser Processing and Modification, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai,
200240, PR China b Department of Industrial and Manufacturing Eng

ABSTRACT

A three-dimensional thermal-fluid numerical model considering zinc vapor interaction with the molten pool was developed to study the occurrence of zinc vapor-induced spatter in partial penetration laser overlap welding of zinc-coated steels. The zinc vapor effect was represented by two forces: a jet pressure force acting on the keyhole rear wall as the vapor bursts into the keyhole and a drag force on the upper keyhole wall as the vapor escapes upwards. The numerical model was calibrated by comparing the predicted keyhole shape with the keyhole shape observed by high-speed X-ray imaging and applied for various weld schedules. The study showed that large jet pressure forces induced violent fluctuations of the keyhole rear wall, resulting in an unstable keyhole and turbulent melt flow. A large drag force pushed the melt adjacent to the keyhole surface upward and accelerated the movement of the melt whose velocities reached 1 m/s or even higher, potentially inducing spatter. Increased heat input facilitated the occurrence of large droplets of spatter, which agreed with experimental observations captured by high-speed camera.

아연도금강의 부분용입 레이저 겹침용접에서 아연증기유도 스패터의 발생을 연구하기 위하여 용융풀과의 아연증기 상호작용을 고려한 3차원 열유체 수치모델을 개발하였습니다.

아연 증기 효과는 증기가 열쇠 구멍으로 폭발할 때 키홀 뒤쪽 벽에 작용하는 제트 압력력과 증기가 위쪽으로 빠져나갈 때 위쪽 키홀 벽에 작용하는 항력의 두 가지 힘으로 표시됩니다.

수치 모델은 예측된 열쇠 구멍 모양과 고속 X선 영상으로 관찰된 키홀 모양을 비교하여 보정하고 다양한 용접 일정에 적용했습니다.

이 연구는 큰 제트 압력이 키홀 뒷벽의 격렬한 변동을 유발하여 불안정한 열쇠 구멍과 난류 용융 흐름을 초래한다는 것을 보여주었습니다. 큰 항력은 키홀 표면에 인접한 용융물을 위로 밀어올리고 속도가 1m/s 이상에 도달한 용융물의 이동을 가속화하여 잠재적으로 스패터를 유발할 수 있습니다.

증가된 열 입력은 고속 카메라로 포착한 실험적 관찰과 일치하는 큰 방울의 스패터 발생을 촉진했습니다.

Fig. 1. Schematic of zero-gap laser welding of zinc-coated steel.
Fig. 1. Schematic of zero-gap laser welding of zinc-coated steel.
Fig. 2. Experimental setup for capturing a side view of the laser welding of zinc-coated steel enabled by use of high-temperature glass.
Fig. 2. Experimental setup for capturing a side view of the laser welding of zinc-coated steel enabled by use of high-temperature glass.
Fig. 3. Experimental angled top-view setup for laser welding of zinc-coated steel with a laser illumination.
Fig. 3. Experimental angled top-view setup for laser welding of zinc-coated steel with a laser illumination.
Fig. 4. Schematic of the rotating Gaussian body heat source.
Fig. 4. Schematic of the rotating Gaussian body heat source.
Fig. 5. Schematic of jet pressure force caused by zinc vapor: (a) locating the outlet of zinc vapor (point A), (b) schematic of assigning the jet pressure force.
Fig. 5. Schematic of jet pressure force caused by zinc vapor: (a) locating the outlet of zinc vapor (point A), (b) schematic of assigning the jet pressure force.
Fig. 6. Schematic of drag force caused by zinc vapor.
Fig. 6. Schematic of drag force caused by zinc vapor.
Fig. 7. Procedure for calculating the outgassing velocity of zinc vapor.
Fig. 7. Procedure for calculating the outgassing velocity of zinc vapor.
Fig. 8. Schematic related to calculating the zone of vaporized zinc.
Fig. 8. Schematic related to calculating the zone of vaporized zinc.
Fig. 9. The meshed domains for the thermal-fluid simulation of laser welding.
Fig. 9. The meshed domains for the thermal-fluid simulation of laser welding.
Fig. 10. The calculated temperature field and validation: (a) 3-D temperature field; (b)-(f) Comparison of experimental and simulated weld cross section: (b) P = 2000 W, v = 50 mm/s; (c) P = 2500 W, v = 50 mm/s; (d) P = 3000 W, v = 50 mm/s; (e) P = 3000 W, v = 60 mm/s; (f) P = 3000 W, v = 70 mm/s.
Fig. 10. The calculated temperature field and validation: (a) 3-D temperature field; (b)-(f) Comparison of experimental and simulated weld cross section: (b) P = 2000 W, v = 50 mm/s; (c) P = 2500 W, v = 50 mm/s; (d) P = 3000 W, v = 50 mm/s; (e) P = 3000 W, v = 60 mm/s; (f) P = 3000 W, v = 70 mm/s.
Fig. 11. Comparison of X-Ray images of in-process keyhole profiles and the numerical predictions: (a) Single sheet penetration (P = 480 W, v = 150 mm/s); (b) Two sheet penetration (P = 532 W, v = 150 mm/s).
Fig. 11. Comparison of X-Ray images of in-process keyhole profiles and the numerical predictions: (a) Single sheet penetration (P = 480 W, v = 150 mm/s); (b) Two sheet penetration (P = 532 W, v = 150 mm/s).
Fig. 12. High-speed images of dynamic keyhole in laser welding of steels: (a) without zinc coating (b) with zinc coating.
Fig. 12. High-speed images of dynamic keyhole in laser welding of steels: (a) without zinc coating (b) with zinc coating.
Fig. 13. Mass loss and molten pool observation under different laser power and welding velocity for 1.2 mm + 1.2 mm HDG 420LA stack-up
Fig. 13. Mass loss and molten pool observation under different laser power and welding velocity for 1.2 mm + 1.2 mm HDG 420LA stack-up
Fig. 14. Numerical results of keyhole and flow field in molten pool: (a) without zinc vapor forces, (b) with zinc vapor forces.
Fig. 14. Numerical results of keyhole and flow field in molten pool: (a) without zinc vapor forces, (b) with zinc vapor forces.
Fig. 18. Calculated velocity fields for different welding parameters: (a) P = 2 kW, v = 50 mm/s, (b) P = 2.5 kW, v = 50 mm/s, (c) P = 3 kW, v = 50 mm/s, (d) P = 3 kW, v = 60 mm/s, (e) P = 3 kW, v = 70 mm/s.
Fig. 18. Calculated velocity fields for different welding parameters: (a) P = 2 kW, v = 50 mm/s, (b) P = 2.5 kW, v = 50 mm/s, (c) P = 3 kW, v = 50 mm/s, (d) P = 3 kW, v = 60 mm/s, (e) P = 3 kW, v = 70 mm/s.
Fig. 19. Schematic of the generation of spatter in different sizes: (a) small size, (b) large size.
Fig. 19. Schematic of the generation of spatter in different sizes: (a) small size, (b) large size.

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Fig. 1. Modified Timelli mold design.

Characterization of properties of Vanadium, Boron and Strontium addition on HPDC of A360 alloy

A360 합금의 HPDC에 대한 바나듐, 붕소 및 스트론튬 첨가 특성 특성

OzenGursoya
MuratColakb
KazimTurc
DeryaDispinarde

aUniversity of Padova, Department of Management and Engineering, Vicenza, Italy
bUniversity of Bayburt, Mechanical Engineering, Bayburt, Turkey
cAtilim University, Metallurgical and Materials Engineering, Ankara, Turkey
dIstanbul Technical University, Metallurgical and Materials Engineering, Istanbul, Turkey
eCenter for Critical and Functional Materials, ITU, Istanbul, Turkey

ABSTRACT

The demand for lighter weight decreased thickness and higher strength has become the focal point in the
automotive industry. In order to meet such requirements, the addition of several alloying elements has been started to be investigated. In this work, the additions of V, B, and Sr on feedability and tensile properties of A360 has been studied. A mold design that consisted of test bars has been produced. Initially, a simulation was carried out to optimize the runners, filling, and solidification parameters. Following the tests, it was found that V addition revealed the highest UTS but low elongation at fracture, while B addition exhibited visa verse. On the other hand, impact energy was higher with B additions.

더 가벼운 무게의 감소된 두께와 더 높은 강도에 대한 요구는 자동차 산업의 초점이 되었습니다. 이러한 요구 사항을 충족하기 위해 여러 합금 원소의 추가가 조사되기 시작했습니다. 이 연구에서는 A360의 이송성 및 인장 특성에 대한 V, B 및 Sr의 첨가가 연구되었습니다. 시험봉으로 구성된 금형 설계가 제작되었습니다. 처음에는 러너, 충전 및 응고 매개변수를 최적화하기 위해 시뮬레이션이 수행되었습니다. 시험 결과, V 첨가는 UTS가 가장 높지만 파단 연신율은 낮았고, B 첨가는 visa verse를 나타냈다. 반면에 충격 에너지는 B 첨가에서 더 높았다.

Fig. 1. Modified Timelli mold design.
Fig. 1. Modified Timelli mold design.
Fig. 2. Microstructural images (a) unmodified alloy, (b) Sr modified, (c) V added, (d) B added.
Fig. 2. Microstructural images (a) unmodified alloy, (b) Sr modified, (c) V added, (d) B added.
Fig. 3. Effect of Sr and V addition on the tensile properties of A360
Fig. 3. Effect of Sr and V addition on the tensile properties of A360
Fig. 4. Effect of Sr and B addition on the tensile properties of A360.
Fig. 4. Effect of Sr and B addition on the tensile properties of A360.
Fig. 5. Bubbles chart of tensile properties values obtained from Weibull statistics. | Fig. 6. Effect of Sr, V and B addition on the impact properties of A360.
Fig. 5. Bubbles chart of tensile properties values obtained from Weibull statistics.
Fig. 6. Effect of Sr, V and B addition on the impact properties of A360.
Fig. 7. SEM images on the fracture surfaces (a) V added, (b) B added.
Fig. 7. SEM images on the fracture surfaces (a) V added, (b) B added.

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Fig. 2 Model Test System

경로점을 가지는 해상풍력 석션버켓 기초의 기울기 제어 모형실험

Model tests for tilting control of suction bucket foundation for offshore wind turbine with path points

J. Korean Soc. Hazard Mitig. 2021;21(3):125-132

Publication date (electronic) : 2021 June 30

doi : https://doi.org/10.9798/KOSHAM.2021.21.3.125

You-Seok Kim*Jong-Pil Lee**

김유석*, 이종필**

* 정회원, ㈜대우건설 기술연구원 수석연구원(E-mail: youseok.kim@daewooenc.com)

* Member, Chief Research Engineer, Daewoo Institute of Construction Technology, DAEWOO E&C

** ㈜대우건설 기술연구원 과장

** Manager, Daewoo Institute of Construction Technology, DAEWOO E&C

* 교신저자, 정회원, ㈜대우건설 기술연구원 수석연구원(Tel: +82-2-2288-1050, Fax: +82-2-2288-4094, E-mail: youseok.kim@daewooenc.com)

Abstract

해상풍력단지개발에서 단일형 석션버켓 기초의 기울기 제어는 중요한 문제이다. 단일형 석션버켓 기초의 경우에는 내부에 격실을 마련하고 각 격실의 압력을 제어하는 것으로부터 기초의 기울기 제어가 가능하다. 단 각 격실의 압력은 미세하게 제어가 가능하여야 한다. 이에 대한 연구들이 수행되었으나 기울기 제어에 대한 방법론에 대해서는 구체적으로 언급이 되지 않고 있다. 본 연구에서는 3개의 내부격실을 둔 단일형 석션버켓 기초의 기울기 제어에 대한 모형실험을 실시하였다. 모형석션 기초의 기울기 제어를 위해서 격실내부압력을 각기 제어하여 실험을 수행하였다. 모형은 실제크기의 1:100으로 제작하였고 모래지반으로 수행하였다. 각 격실별로 부압 및 정압을 4가지로 조합하여 모형기초의 기울기 제어 실험을 수행하였다. 실험결과 시공 중 및 운용 중에 대해서 5°의 기울기 제어가 가능하였다. 운용중의 경우에는 부압만으로는 모형기초의 기울기 제어가 한계가 있어 정압을 조합하여 5°의 기울기 제어를 실현하였다.

In offshore wind farms, tilting control based on a single-basket suction bucket foundation is a significant problem. In a single-basket suction bucket foundation, the tilting control of the foundation is possible by arranging the cells inside and controlling the pressure of each cell. However, the pressure of each cell must be finely controlled. Studies on this topic have been conducted, but no specific tilting control method has been developed. This paper presents experimental model results for tilting control obtained during the installation of a suction bucket foundation consisting of three internal cells. Tilting control was performed by independently controlling the internal pressure of each cell. A 1:100 scale model was used, and the ground condition was sandy. Four cases of tilting control tests for the model foundation were used with multiple combinations of internal positive, negative, or both pressures of each cell. It was found that the tilting control was within 5° during the installation and operation stages. There was a tilting control limit for operation based on the model with only negative pressure; therefore, 5° tilting control was achieved by combining the positive pressure.

Keywords

1. 서 론

해상풍력발전기가 원활한 발전을 하기 위해서는 일정각도 이내의 기울기가 확보되어야 한다. 석션버켓 기초 형식은 기초하부가 단단한 암반층에 놓이지 않는다. 따라서 석션버켓 기초를 가지는 해상풍력 발전기는 조류력, 풍력, 파력 그리고 세굴 등에 의해 기울어질 수 있다. 우리나라의 경우 유럽과 달리 태풍과 같은 변수도 작용한다. 이를 극복하기 위해서는 설치단계나 운용단계에서 기울기를 보정하는 것이 중요하다. 특히 단일형 석션버켓 기초의 경우 내부에 격실을 두고 격실 내 압력을 제어하여 기울기를 보정하게 된다. 이 경우 각 격실에 부여하는 압력에 따라 기울기 보정이 이루어 질것이나 구체적으로 기울기보정을 위한 압력제어방법에 대해서는 구체적인 언급이 없는 형편이다.

Universal Foundation은 북해 Round 3에 대하여 단일형 석션버켓 기초에 대한 시험시공을 실시하였으며 수직도를 0.1° 미만으로 달성한 바 있다(Universal-foundation, 2014).

중국에서는 해상풍력 발전기용 단일형 석션버켓 기초에 내부격실을 적용하였으며 기초를 prestressed 콘크리트로 만든바 있다(Lian et al., 2011Lian et al., 2012Zhang et al., 2015). Zhang et al. (2016)에 따르면, 내부격실은 6각형이 모여있는 벌집형태를 가지며 실험은 Jiangsu성 풍력단지 예정지에서 가져온 실트질 모래로 지반을 조성하였다. 총 7개의 내부격실을 개별적으로 제어하였으나 최종 수직도는 명확하게 기술하지 않았다. 작은 기울기에 대해서는 부압을 통하여 조정하고, 큰 기울기에 대해서는 정압과 부압을 조합하여 제어를 완료하였다. 단일형 석션버켓 기초의 수직도에 대한 연구이나 구체적 절차가 언급되어 있지 않고, 격실별 정압⋅부압의 조합으로 인한 효과 등에 대해서도 자세하게 언급하지 않았다.

국내에서는 Kwag et al. (2012)은 군산항 앞바다에 단일형 석션버켓 기초를 시험 시공하였다. 단일형 석션버켓 기초를 최대 0.5° 이내의 오차로 설치가 완료하였다. 또한, Kim and Bae (2016)는 내부격실을 가지는 단일형 석션버켓 기초에 대한 기울기 보정방법을 제안하였다. 석션버켓 기초의 내부를 동일한 크기로 한가운데를 기준으로 방사형으로 3개 또는 4개의 격실로 나누고, 격실별 석션압을 제어하여 기울기를 제어하는 기술을 제안하였다. Kim et al. (2017)은 3개의 내부격실을 갖는 실내모형실험에서 시공중 1° 이상의 기울기 제어가 가능하였으며, 운용 중에는 0.25°의 기울기 제어가 가능한 것을 확인하였다. 운용단계에서는 정압을 부여하여야 큰 기울기 보정이 가능함을 밝혔다.

Kim et al. (2017)의 연구에서는 펌프구동압 제어문제로 임의 방위각을 가지는 단일형 석션버켓 기초의 실험을 수행하지 못하였고, 일방향 제어에 의한 기울기 제어의 실험이 수행되었다. 실험은 펌프구동압이 제어되지 못하여 보일링이 발생하는 문제가 있었다.

본 연구에서는 Kim et al. (2017)의 기존 연구를 보완하여 3개의 격실을 가지는 단일형 석션버켓 기초모형을 가지고 격실내부 압력을 각기 제어하여 기울기를 보정하는 실험연구를 수행하였다. 4개의 실험들은 초기에 동일한 경사각을 가지도록 하였고 이를 펌프구동에 의해 0.25° 이하가 되도록 하였으며, 기울어진 점이 내부격실위치에 상관없이 임의 방위각을 가지도록 배치하여 개별 격실내부에 부압과 정압을 조합하는 조건에서 해상풍력 발전기 시공단계 중 2가지와 운용 중 2가지에 대해서 기울기 보정실험을 수행하였다. 1개의 해상풍력기초의 경우는 수동에 의한 기울기 보정이 가능하다고 보여 지나, 해상풍력단지는 다수의 기초로 구성되며, 자동화를 위한 알고리즘 개발은 중요한 문제이다. 일련의 실험들은 동일한 방식에 의해 모형기초의 기울기 제어가 되도록 하였다. 동일한 알고리즘이 적용되는 경우에 단일형 석션버켓 기초로 이루어진 해상풍력단지 개발에 적용이 가능할 것으로 사료된다.

2. 실험방법 및 장비

본 연구에서는 Kim and Bae (2016)가 제안한 방법을 실험적으로 구현하였다. 이를 위해 Kim et al. (2017)의 시스템에서 문제가 되었던 펌프의 압력을 제어하기 위해 비례제어밸브를 추가 하였고, 임의 방위각으로 기울어진 모형석션버켓 기초를 기울기 보정하기 위해 총 6개의 펌프를 설치하였다. 펌프에 의한 격실 내 압력제어는 모형기초의 기울기를 미세하게 자세제어하기 위해서 필요하다. Kim et al. (2017)에서 사용한 펌프는 작은 용량이었으나 보일링이 일어나는 문제가 있었다. 따라서 압력을 제어하기 위해서 펌프자체의 속도를 저감하는 방법이 필요하였다. 채택된 펌프용량이 작아서 인버터와 같은 펌프속도에 맞는 속도제어기를 구하지 못하였다. 이에 따라 압력제어를 위하여 격실에 연결되는 호스 중간에 비례제어밸브를 채택하게 되었다. 비례제어밸브는 수백단계의 각도를 미세하게 제어가 가능하며 전압이나 전류 값을 입력하여 밸브의 여닫힘 제어가 가능하다. 본 실험에서 사용된 비례제어밸브는 전압제어 방식으로 0에서 5 V DC전압으로 밸브 폐쇄부터 완전개방까지를 제어할 수 있다. 본 실험에서는 제어기와 비례제어밸브간 거리가 상대적으로 멀지 않았기 때문에 제어가 쉬운 DC전압제어를 사용하였으나, 5 m 이상 거리가 먼 경우에는 전압강하 등에 의한 문제가 없는 전류 값으로도 제어가 가능한 제품을 사용하였다. Kim and Bae (2016)가 제안한 방법의 기본개념은 Fig. 1(a)와 같다. 그림에서 보는 바와 같이 각 격실의 압력을 제어하여 초기위치 pt4를 기울기원점(기울기 0°) pt0로 보내는 것으로 2번의 경로를 통하여 원점으로 보내게 된다. 여기에는 각 격실의 압력부여에 따라 3가지 방법이 있다. 우선 격실2번에 부압을 주면 pt1으로 보내고 다음 단계로 격실 2번 및 3번에 부압을 주어 pt0로 보내는 방법1, 격실3에 부압을 주어 pt2로 보낸 다음 격실 2에 부압을 주어 pt0로 보내는 방법2, 마지막으로 격실 2 및 3에 부압을 주어 pt3으로 보낸 다음 격실2에 부압을 주어 pt0로 보내는 방법3다. 이 3가지 방법 중에서 중간의 경로점 pt1, pt2, pt3와 최종위치 pt0와의 거리가 가장 짧은 쪽을 선택하는 것이 가장 효율적인 방법이다. 본 연구에서는 pt4(방위각 55°)에서 pt3를 거쳐 pt0로 보내는 방법(case 1)과 pt4의 대각선에 위치한다고 가정한(방위각 235°) pt5에서 pt0로 이동시키는 방법(case 2)에 대해 모형실험을 실시하였다(Fig. 1(b) 참조). 또한 해상풍력발전기가 운영중인 것으로 모사하기 위해 내부격실이 모래지반으로 채워져서 부압만으로는 기울기보정이 안 되는 것으로 가정하여 case 1과 case 2와 동일한 방위각 및 기울기에서 정압도 부여하는 방법(case 3, 4)에 대하여 실험을 실시하였다. Kim et al. (2017)에 의하면 3개의 격실 중 1개의 격실 만에도 내부에 모래지반으로 채워져 물로만 되어 있는 공간이 없는 경우는 더 이상 기울기 제어가 거의 되지 않았음을 확인한 바 있다. 초기 기울기각은 5°로 하였으며 방위각은 Fig. 1(b)에서와 같이 55° 및 235°에 대하여 실시하였다. 방위각 55°의 경우 위에서 언급한 격실 2와 3에 부압을 주는 경우(Fig. 1(c) 참조)가 가장 효율적이며 방위각 235°의 경우는 격실 1에 부압을 주는 방법(Fig. 1(d) 참조)이 가장 효율적이다.

Fig. 1 Basic Concept of Tilting Control Method
Fig. 1 Basic Concept of Tilting Control Method

이와 같이 동일한 방식으로 자동화를 이루면 단일형 석션버켓 기초로 이루어진 해상풍력단지에서 일정각도 이상 기울어진 경우에 자동적으로 기울기가 보정 가능할 것으로 사료된다.

실험장비는 Fig. 2와 같이 모형토조, 모형기초 내부의 부압 및 정압을 부여하는 펌프, 모형석션버켓 기초, 펌프압을 제어하는 비례제어밸브, 레이저변위용 센서거치대, 데이터 수집장비 및 실시간데이터를 볼 수 있는 PC로 구성된다. 모형토조 제원은 내경 580 mm, 내측 높이 454 mm이며 두께 10 mm의 원형아크릴로 제작되었다. 데이터 수집장비는 레이저변위계 및 압력계를 계측할 수 있는 측정장비를 사용하였고 계측간격은 초당 2회로 하였다.

Fig. 2 Model Test System
Fig. 2 Model Test System

Model Test System

모형석션버켓 기초는 두께 3 mm의 아크릴로 제작되었으며, 이의 제원은 Fig. 3(a)와 같이 지름 170 mm, 높이 130 mm이다. 내부격실은 두께 3 mm, 격실높이 78 mm로 모형석션버켓 벽체높이의 60%로 설치하였다. 모형석션버켓 기초는 원형(prototype) 구조물의 1:100의 크기로 제작되었다. 모형석션버켓 기초 내부에 격실 내부의 압력을 측정하는 압력계를 부착하였다(Figs. 3(b) and 3(e) 참조). 격실내부의 압력계는 간극수압의 측정을 위하여 격실내부에 있는 모래지반이 부압에 의하여 융기하여 격실내부천장에 있는 압력센서에 닿지 않도록 빈 공간을 두었으며 물만 유입이 되도록 가는 철망을 씌웠다. 사용된 압력계는 50 kPa의 압력까지를 측정할 수 있는 것으로 2 m 깊이의 수조에 물을 넣고 수위를 조절하여 실험에 사용된 모든 센서를 검정하여 사용하였다. 실험 중 변위는 연직변위 측정을 위하여 레이저변위계로 측정되었으며, 총 1개가 사용되었다. 모형기초의 중앙상부에 반사판을 설치하였고, 센서거치대에는 막대를 설치하고 막대 끝에 레이저변위계를 수직 Z축 방향으로 부착하였다(Figs. 3(a) and 3(c) 참조). 레이저변위계에는 변위값이 표시되며 운용중 단계인 실험 Case 3 및 Case 4에서 부압에 의해 연직변위가 더 이상 발생하지 않는 것을 확인하는 용도로 설치하였다(Fig. 3(d) 참조). 모형석션버켓 기초의 기울기 측정을 위해 경사계를 모형상부에 설치하였다. 경사계는 X, Y 2개축의 기울기를 각각 -40°~40°까지 측정가능하며, DC 전압으로 출력된다. 이를 Data logger에서 계측하고 다시 방위각 및 경사각을 계산하여 PC상에서 실시간으로 보여줄 수 있도록 하였다.

Fig. 3

Instrumented Model Suction Bucket

펌프는 일 방향으로만 구동되는 로터리식 펌프로 물이 한 방향으로만 들어가고 반대방향으로 물이 나오는 구조의 펌프이다. 펌프는 220 V AC로 구동되며 용량은 80 W이다. 사용된 펌프는 총 6개로 모든 격실에 각각 2개씩 연결되어, 격실별 제어를 하였다. 실험 case별로 각 격실별 압력이 부압인지 정압인지에 따라서, 사용되는 펌프가 다르게 하여 실험을 수행하였다.

모형석션버켓 기초는 30 mm까지는 수동으로 관입시켰으며, 이후 모형석션버켓의 매입깊이가 20 mm가 남겨질 때까지 각 격실에 부압을 작용시키면서 관입시켰다. 35 mm가 남겨진 이후에는 초기기울기를 부여하기 위해 각 격실별로 부압을 달리하였다. 마지막단계에서는 초기기울기를 모든 실험에서 동일하게 설정하기 위해 3개의 격실에 각기 다른 부압을 작동시키면서 X축으로부터 방위각 55°(또는 235°) 및 기울기가 5°가 되도록 기초상부를 강제변위를 부여하여 위치시켰다. 방위각 및 기울기는 컴퓨터화면에서 실시간으로 볼 수 있도록 하였다. Kim et al. (2017)에서는 펌프압의 크기를 제어하지 못하여 실재적인 기울기 모사가 어려워서 한쪽방향으로만 움직이게 하는 기울기 제어 실험을 실시한바 있다. 본 연구에서는 이러한 문제점을 개선하고자 펌프를 3개 추가하여 총 6개를 설치하였으며, 모든 펌프에는 비례제어밸브를 설치하여 컴퓨터프로그램으로 비례제어밸브의 여닫는 각도를 제어할 수 있도록 하여 임의 방위각을 가진 기울어진 모형석션버켓 기초의 수직도제어가 가능하도록 시스템을 개선하였다. 사용된 비례제어밸브는 600단계의 여닫힘 각도제어가 가능하다. 각 격실별로 부압펌프 1개 및 정압펌프 1개를 설치하였다. 실험조건은 설치단계에 대한 모사로서 모형석션버켓의 설치모사단계로 X축을 기준으로 55° 또는 235°의 방위각에 기울기 5°를 기준으로 하여 동일한 기초배치시 격실의 부압 및 정압제어를 실시하는 2가지 조건으로 하였다(case 1, 2). 또한 운전 중인 상태를 고려하되 앞의 조건과 동일한 방위각 55° 및 235°에 대한 2가지 실험을 실시하였다. 기초 설치시의 조건인 경우에는 격실내부에 물만 있는 공간이 있는 경우이고, 운전 중인 조건은 격실내부에 부압을 작용시켜도 모형석션버켓 기초가 움직이지 않는 경우로 가정하였다(case 3, 4). 이를 위해 3개의 격실중 적어도 하나의 격실에 모래지반으로 채워져서 부압을 가하여도 모형석션버켓이 움직이지 않아 기울기 제어가 안 되는 조건을 인위적으로 조성하였다. 따라서 운전 중인 경우에는 내부에 모래가 차있는 격실에 정압을 부여하여 인위적으로 내부공간을 만들면서 기울기를 제어하도록 하였다. 기울기 제어 실험케이스는 Table 1과 같다.

Table 1

Cases of Experiment

격실의 압력은 실험 시작 전 초기에 설정한 비례제어밸브의 열림정도를 결정하고 수행하였으며, 격실압력이 이웃격실로 전이되거나 보일링이 발생되는 경우에는 실험을 중단하였고, 비례제어밸브값을 수정하여 초기 압력을 다시 설정하였다. 또한 실험중간에 비례제어밸브를 미세하게 제어할 수 있도록 프로그램화 하였으며 PC에서 실시간으로 제어하여 기울기의 변화를 살펴가면서 기울기가 0.25 이하가 나올 때까지 제어하였다. 계측은 격실 내 압력 및 모형석션버켓의 최상단에 변위계를 설치하여 변위를 측정하였다. 사용된 지반은 모래이고 Kim et al. (2017)에서 수행한 실험과 동일한 모래를 사용하였으며 내부마찰각은 39.1°이었으며 상대밀도는 59%이었다. 모래지반조성은 강사기를 사용하였으며, 토조 하부에 관을 매설하여 물을 주입할 수 있도록 하였으며 지반조성 후 포화 시 지반의 교란이 최소가 되도록 하였다. 본 연구에서는 연구목적이 Kim et al. (2017)이 수행한 실험과의 연계 및 내부격실을 이용하여 기울기 제어 가능성을 판단하기 위한 것이기 때문에, 모래지반만을 대상으로 연구를 수행하였다. 각 격실 상부에는 부압용라인과 정압용라인, 초기 압입 시 발생되는 내압을 제거하기 위한 밸브가 같이 부착되어 있다. Kim et al. (2017)에서는 모형석션버켓 기초의 평형을 맞춘 상태로 기울기 제어 실험을 실시하였으나, 본 연구에서는 초기에 정해진 방위각 및 기울기를 확보하고자, 각 격실에 압력을 제어하면서 최종적으로는 수동으로 방위각 및 기울기를 조정하였다. 격실 내 모래가 다 차있는 공용 중 기울기 모사실험을 모사하기 위해서는 하나 또는 두 개의 격실에 다른 격실보다 큰 부압을 부여하여 보일링이 발생토록 유도하였다. 부압발생에 따른 추가적인 변위발생이 없는지를 상부에 설치된 레이저변위계의 수치를 보면서 초기 모형석션버켓 기초설치를 완료 하였다.

3. 실험결과 및 토의

실험결과를 제시한 그래프에서 측정된 격실내부 수압은 초기값을 0으로 설정하고 압력이 부여된 상태에 대한 상대 압력을 도시하였다. 경사계는 토조를 상부에서 바라볼 때 오른쪽이 X축으로 앞쪽을 Y축으로 정하였으며 방위각은 X축을 기준으로 반시계방향으로 정하였다. 경사계로 얻은 경사각은 실험 전 기초를 5°(±0.1° 이내)가 되도록 기울여 설정하였으며, 격실1에 설치된 상대압력 값은 P1으로 나머지 격실 2와 3의 상대압력은 P2와 P3으로 각각 표시하였다. 각 격실은 X축을 방위각 0°로 하여 방위각 120°까지가 격실 1, 그 다음 240°까지가 격실 2, 나머지 360°까지를 격실 3으로 하였다. 실험결과 그래프에 격실별 위치를 나타내는 모형석션버켓 기초의 평면도를 삽입하였다. 평면도에서 작은 점은 실험을 시작하기 전의 모형석션기초의 기울어진 위치이다. 둥근 원은 모형석션기초의 기울어진 경사각 5°를 뜻한다.

3.1 시공단계 기울기 제어 모사실험

3.1.1 2격실에 부압 적용한 기울기 제어 : Case 1

Case 1 실험은 Fig. 1(c)에서와 같이 3개의 격실 중 격실 2 및 3의 2개 격실에 부압을 작용시켜 모형 기초의 기울기를 보정하는 1단계 및 현 기울기 위치가 X축을 기준으로 방위각 0°에 이르면 2번 격실에 부압을 작용시켜 기울기가 0.25° 이하가 되도록 하는 2단계 실험이다. 격실내부의 수압변화와 모형석션버켓 기초의 경사각변화는 Fig. 4와 같다. Fig. 4에서 보는 바와 같이, 부압을 가한 격실에서 측정된 압력 P2 및 P3이 낮아졌으며, 아무런 압력을 가하지 않은 격실 1에서 측정된 압력 P1도 따라서 낮아 졌으나 그 값은 작았으며 보일링도 발생하지 않았다. 방위각이 0°에 가까워지면 비례제어밸브 열림 정도를 작게 하면서 격실 3 펌프를 정지시켰다. 그리고 격실 2에 연결된 펌프의 압력을 낮추기 위해 연결된 비례제어밸브의 열림 정도를 작게 조종하였으며 최종적으로 경사각은 0.25° 이하가 유지되어 기울기가 조정됨을 확인 하였다.

Fig. 4

Variations in Pressures of Internal Cells and Inclined Angle for Case 1

3.1.2 1격실에 부압 적용한 기울기 제어 : Case 2

Fig. 5는 실험결과 Case 2의 격실 내 압력변화와 경사각을 같이 도시한 그림이다. 2격실 부압 적용 조건인 Case 1과 마찬가지로 부압에 의해 경사각 변화가 발생하는 것을 확인하였으며 2개 격실에 부압이 적용된 Case 1보다 기울기보정시간이 길었다. Case 1과 마찬가지로 나머지 격실에 부압이 발생하였으나 값은 크지 않았다. Case 1과 마찬가지로 경로마다 비례제어밸브도 제어하였으며 최종적으로는 펌프를 정지시켰다. Case 2에서도 경사각 0.25° 이하로 제어가 가능함을 확인하였다.

Fig. 5

Variations in Pressures of Internal Cells and Inclined Angle for Case 2

3.2 시공완료 후 해상풍력 발전기 운용단계 모사실험

3.2.1 부압2격실 및 정압1격실에 적용한 기울기 제어 : Case 3

Case 3의 실험결과는 Fig. 6과 같다. Case 3에서는 격실 1이 모래로 차있기 때문에 격실내 부압 제어만으로는 기울기 제어각도가 제한된다. Kim et al. (2017)에 의하면 부압에 의해서는 0.25°의 기울기 보정이 가능하였다. 따라서 격실 안에 모래로 차있는 격실에 정압을 부여하여 격실 내 상부판과 모래지반상부와의 공간을 확보하면서 기울기를 제어하였다. 또한 반대편에 부압을 작용시켜 기울기가 빠르게 보정되도록 하였다. Case 3의 경우도 경사각 5°에 대한 기울기 제어가 가능함을 확인하였다.

Fig. 6

Variations in Pressures of Internal Cells and Inclined Angle of Case 3

3.2.2 부압1격실 및 정압2격실에 적용한 기울기 제어 : Case 4

시공완료 후 조건에 따라 사전에 격실 2 및 격실 3에 모래가 차도록 부압을 발생시켜둔 상태로 부압만으로는 기울기 제어가 안되기 때문에 격실 2 및 격실 3에 정압을 발생시키고 반대편 격실 1에는 부압을 부여하였다. Fig. 7 결과에 의하면 Case 3보다는 Case 4에서 기울기 보정시간이 단축되었는데, Case 3에서는 정압부여 격실이 1개 인데 비하여 Case 4에서는 정압부여 격실이 2개이기 때문으로 사료된다. Case 4에서도 기울기 0.25°로 달성 가능함을 확인하였다.

Fig. 7

Variations in Pressures of Internal Cells and Inclined Angle for Case 4

3.3 실험케이스별 모형석션버켓 기초의 최종 경사각과 도달시간

Table 2는 실험 중 경사각을 정리하였다. 시공 중 및 운용 중에 대한 4개의 실험들에서 설정된 초기 기울기가 5° 인 경우에 최종기울기가 0.25° 이하로의 기울기 보정이 가능함을 확인하였다. 또한, 방위각과 격실배치에 상관없이 임의각도로 기울어져도 격실에 부압과 정압을 부여하면 기울기 제어가 가능함을 확인 하였다. 운용중인 경우는 부압만으로 기울기 제어가 곤란함을 이전 실험연구에서 확인하였는바 이번 연구에서는 격실에 정압을 부여함으로서 기울기 제어가 가능함을 확인하였다.

Table 2

Final Results of Tilting Control

4. 결 론

단일형 석션버켓 기초를 사용하는 해상풍력 발전기의 하부기초에 대하여 3개의 내부격실을 적용한 형식으로 임의 방향의 기울기 제어가 가능함을 확인하는 모형실험을 수행하였다. 각 격실에는 부압용 및 정압용 펌프를 각기 연결하였다. 또한 각 펌프에 비례제어밸브를 추가하여 압력을 제어하였다. 모래지반에서 원형(prototype) 구조물의 1:100 크기로 된 모형석션버켓을 이용한 4개의 실험결과로 부터 다음과 같은 결론을 얻었다.

  • 1. 내부격실 내 여유 공간이 있는 시공단계 중을 모사한 단일형 석션버켓 모형실험에서 초기 설정한 5°의 기울기 제어가 가능하였다. 단일형 석션버켓 기초에 3개의 내부격실을 둠으로서 격실내부압력변화로 부터 기울기 제어가 가능한 것을 확인하였다.
  • 2. 격실 내 상판이 지표면에 맞닿은 조건이 되는 경우로 가정한 운용단계실험에서 정압을 부여하여 내부에 공간을 확보하면서 이웃격실에 부압을 부여하면 기 설정된 5°의 기울기 제어가 가능함을 확인하였다. 3개 격실 모두에 여유 공간이 없는 경우도 기울기 제어가 가능할 것으로 사료되나 내부격실 모두에 정압을 부여하면 풍력발전기전체가 상승하게 되어 이에 대해서는 세심한 기울기 제어가 필요할 것으로 사료된다.
  • 3. 이전 연구에서 펌프압력을 제어하기 어려웠던 것에 비하여 본 연구에서는 비례제어밸브를 사용하여 압력을 기존실험에서보다 낮게 제어하여 격실내부의 압력이 이웃격실로 새어나가는 것을 방지 할 수 있었으며 이를 통하여 2단계 경로제어가 가능하였다. 다만, 동일한 압력제어가 매 실험마다 구현되지 않는 문제가 있었으며, 이를 극복하기 위해서는 모형축척을 보다 크게 할 필요가 있다고 사료된다.
  • 4. 해상풍력 발전기 기초에 단일형 석션버켓 기초가 적용되는 경우 시공단계에서 펌프속도를 제어하는 장치가 각 펌프별로 필요할 것으로 판단된다. 또한 발생된 압력을 알기 위해서는 설치단계별 격실 내 압력을 측정하는 것도 중요하다. 운용 시에는 일정깊이에서 유사한 압력만 제어하면 가능하기 때문에 상대적으로 간단한 제어방식을 사용하는 것도 가능할 것으로 사료된다. 다만, 실험결과와 같이 기울기 보정각이 큰 경우에는 격실 내 정압력도 부여해야 하는 문제가 있기 때문에 격실 내 공간확보를 위한 부양높이를 기울기 제어가 가능한 범위내로 제한할 필요가 있다.
  • 5. 단일형 석션버켓기초는 해상풍력단지 건설시 및 운용시 수직도의 유지가 중요하며, 이 경우 동일한 알고리즘을 가지는 수직도제어방법의 개발이 필요하다고 사료된다. 따라서 이를 자동화하기 위한 알고리즘의 개발이 선행되어야 할 것으로 판단된다. 본 연구에서는 기 개발된 알고리즘이 구현되는지를 실험적으로 규명하였다. 본 연구에서는 2단계 경로를 가지는 방법을 제안하였으나 정밀한 기울기 제어가 가능한 경우에 단일경로로 제어하는 방법도 가능할 것으로 사료된다.
  • 6. 본 연구에서는 격실매입깊이에 따른 상한 및 하한 압력을 결정하고 이에 맞는 압력을 부여하는 실험까지는 수행하지 못하였으며 향 후 보다 정밀한 자세제어기법 개발을 위해서는 상하한 압력도표를 적용한 알고리즘의 개발이 필요하다고 사료된다.
Fig. 4. Meshed quarter aluminum model with HAZ regions and support steel plates.

Benchmark study on slamming response of flat-stiffened plates considering fluid-structure interaction

유체-구조 상호작용을 고려한 평판 보강판의 슬래밍 응답에 대한 벤치마크 연구

Dac DungTruongabBeom-SeonJangaCarl-ErikJansoncJonas W.RingsbergcYasuhiraYamadadKotaTakamotofYasumiKawamuraeHan-BaekJua
aResearch Institute of Marine Systems Engineering, Department of Naval Architecture and Ocean Engineering, Seoul National University, Seoul, South Korea
bDepartment of Engineering Mechanics, Nha Trang University, Nha Trang, Viet Nam
cDivision of Marine Technology, Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, Sweden
dNational Maritime Research Institute, National Institute of Maritime, Port and Aviation Technology, Tokyo, Japan
eDepartment of Systems Design for Ocean-Space, Yokohama National University, Kanagawa, Japan
fDepartment of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan

ABSTRACT

이 논문은 해양구조물의 평보강판의 슬래밍 반응에 대한 벤치마크 연구를 제시합니다. 목표는 유체-구조 상호작용(FSI) 시뮬레이션 방법론, 모델링 기술 및 슬래밍 압력 예측에 대한 기존 연구원의 경험을 비교하는 것이었습니다.

수치 FSI 시뮬레이션을 위해 가장 일반적인 상용 소프트웨어 패키지를 사용하는 3개의 연구 그룹(예: LS-Dyna ALE, LS-Dyna ICFD, ANSYS CFX 및 Star-CCM+/ABAQUS)이 이 연구에 참여했습니다.

공개 문헌에서 입수할 수 있는 경량 선박과 같은 바닥 구조의 평평한 강화 알루미늄 판에 대한 습식 낙하 시험 데이터는 FSI 모델링의 검증에 활용되었습니다. 형상 모델 및 재료 속성을 포함한 실험 조건의 요약은 시뮬레이션 전에 참가자에게 배포되었습니다.

충돌 속도와 강판의 강성이 슬래밍 응답에 미치는 영향을 조사하기 위해 해양 설비에 사용되는 실제 치수를 갖는 평판 보강 강판에 대한 매개변수 연구를 수행했습니다. 보강판에 작용하는 전체 수직력에 대한 FE 시뮬레이션 결과와 이러한 힘에 대한 구조적 반응을 참가자로부터 획득하여 분석 및 비교하였다.

앞서 언급한 상용 FSI 소프트웨어 패키지를 사용하여 슬래밍 부하에 대한 신뢰할 수 있고 정확한 예측을 평가했습니다. 또한 FSI 시뮬레이션에서 관찰된 동일한 영구 처짐을 초래하는 등가 정적 슬래밍 압력을 보고하고 분류 표준 DNV에서 제안한 해석 모델 및 슬래밍 압력 계산을 위한 기존 실험 데이터와 비교했습니다.

연구 결과는 등가 하중 모델이 물 충돌 속도와 플레이트 강성에 의존한다는 것을 보여주었습니다. 즉, 등가정압계수는 충돌속도가 증가함에 따라 감소하고 충돌구조가 더 단단해지면 증가한다.

This paper presents a benchmark study on the slamming responses of offshore structures’ flat-stiffened plates. The objective was to compare the fluid-structure interaction (FSI) simulation methodologies, modeling techniques, and established researchers’ experiences in predicting slamming pressure. Three research groups employing the most common commercial software packages for numerical FSI simulations (i.e. LS-Dyna ALE, LS-Dyna ICFD, ANSYS CFX, and Star-CCM+/ABAQUS) participated in this study. Wet drop test data on flat-stiffened aluminum plates of light-ship-like bottom structures available in the open literature was utilized for validation of the FSI modeling. A summary of the experimental conditions including the geometry model and material properties, was distributed to the participants prior to their simulations. A parametric study on flat-stiffened steel plates having actual scantlings used in marine installations was performed to investigate the effect of impact velocity and plate rigidity on slamming response. The FE simulation results for the total vertical forces acting on the stiffened plates and their structural responses to those forces, as obtained from the participants, were analyzed and compared. The reliable and accurate predictions of slamming loads using the aforementioned commercial FSI software packages were evaluated. Additionally, equivalent static slamming pressures resulting in the same permanent deflections, as observed from the FSI simulations, were reported and compared with analytical models proposed by the Classification Standards DNV and existing experimental data for calculation of the slamming pressure. The study results showed that the equivalent load model depends on the water impact velocity and plate rigidity; that is, the equivalent static pressure coefficient decreases with an increase in impact velocity, and increases when impacting structures become stiffer.

Fig. 4. Meshed quarter aluminum model with HAZ regions and support steel plates.
Fig. 4. Meshed quarter aluminum model with HAZ regions and support steel plates.
Fig. 6. (a) Boundary conditions of water hitting case and (b) water jets at end of the simulation.
Fig. 6. (a) Boundary conditions of water hitting case and (b) water jets at end of the simulation.
Fig. 7. Comparison of prediction and test results for deflection time history of (a) D1 and (b) D2 for Vi = 2.3 m/s.
Fig. 7. Comparison of prediction and test results for deflection time history of (a) D1 and (b) D2 for Vi = 2.3 m/s.
Fig. 8. Comparison of prediction and test results for maximum deflection with different impact velocities.
Fig. 8. Comparison of prediction and test results for maximum deflection with different impact velocities.
Fig. 16. Boundary conditions applied to present FSI simulations (Sym. denotes symmetric, and Cons. denotes constrained)
Fig. 16. Boundary conditions applied to present FSI simulations (Sym. denotes symmetric, and Cons. denotes constrained)
Fig. 24. Distribution of deflections at moment of maximum deflection in: (a) LS-Dyna ALE, (b) Star-CCM+/ABAQUS, (c) ANSYS CFD, and (d) LSDyna ICFD (unit: m).

Keywords

Benchmark studyEquivalent static pressureFlat-stiffened plateFluid-structure interactionPermanent deflectionSlamming pressure coefficient

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Liquid-solid co-printing of multi-material 3D fluidic devices via material jetting

재료 분사를 통한 다중 재료 3D 유체 장치의 액체-고체 공동 인쇄

Liquid-solid co-printing of multi-material 3D fluidic devices via material jetting

BrandonHayes,Travis Hainsworth, Robert MacCurdy
University of Colorado Boulder, Department of Mechanical Engineering, Boulder, 80309, CO, USA

Abstract

다중 재료 재료 분사 적층 제조 공정은 3차원(3D) 부품을 레이어별로 구축하기 위해 다양한 모델 및 지지 재료의 미세 액적을 증착합니다.

최근의 노력은 액체가 마이크로/밀리 채널에서 쉽게 퍼지할 수 있는 지지 재료로 작용할 수 있고 구조에 영구적으로 남아 있는 작동 유체로 작용할 수 있음을 보여주었지만 인쇄 프로세스 및 메커니즘에 대한 자세한 이해가 부족합니다.

액체 인쇄의 제한된 광범위한 적용. 이 연구에서 광경화성 및 광경화성 액체 방울이 동시에 증착되는 액체-고체 공동 인쇄라고 하는 “한 번에 모두 가능한” 다중 재료 인쇄 프로세스가 광범위하게 특성화됩니다. 액체-고체 공동 인쇄의 메커니즘은 실험적인 고속 이미징 및 CFD(전산 유체 역학) 연구를 통해 설명됩니다.

이 연구는 액체의 표면 장력이 액체 표면에서 광중합하여 재료의 단단한 층을 형성하는 분사된 광중합체 미세 방울을 지지할 수 있음을 보여줍니다.

마이크로/밀리 유체 소자의 액체-고체 공동 인쇄를 위한 설계 규칙은 믹서, 액적 발생기, 고도로 분기되는 구조 및 통합된 단방향 플랩 밸브와 같은 평면, 3D 및 복합 재료 마이크로/메조 유체 구조에 대한 사례 연구뿐만 아니라 제시됩니다.

우리는 액체-고체 공동 인쇄 과정을 마이크로/메조플루이딕 회로, 전기화학 트랜지스터, 칩 장치 및 로봇을 포함한 응용 프로그램을 사용하여 3D, 통합된 복합 재료 유체 회로 및 유압 구조의 단순하고 빠른 제작을 가능하게 하는 적층 제조의 핵심 새로운 기능으로 구상합니다.

Multi-material material jetting additive manufacturing processes deposit micro-scale droplets of different model and support materials to build three-dimensional (3D) parts layer by layer. Recent efforts have demonstrated that liquids can act as support materials, which can be easily purged from micro/milli-channels, and as working fluids, which permanently remain in a structure, yet the lack of a detailed understanding of the print process and mechanism has limited widespread applications of liquid printing. In this study, an “all in one go” multi-material print process, herein termed liquid–solid co-printing in which non photo-curable and photo-curable liquid droplets are simultaneous deposited, is extensively characterized. The mechanism of liquid–solid co-printing is explained via experimental high speed imaging and computational fluid dynamic (CFD) studies. This work shows that a liquid’s surface tension can support jetted photopolymer micro-droplets which photo-polymerize on the liquid surface to form a solid layer of material. Design rules for liquid–solid co-printing of micro/milli-fluidic devices are presented as well as case studies of planar, 3D, and multi-material micro/mesofluidic structures such as mixers, droplet generators, highly branching structures, and an integrated one-way flap valve. We envision the liquid–solid co-printing process as a key new capability in additive manufacturing to enable simple and rapid fabrication of 3D, integrated print-in-place multi-material fluidic circuits and hydraulic structures with applications including micro/mesofluidic circuits, electrochemical transistors, lab-on-a-chip devices, and robotics.

Liquid-solid co-printing of multi-material 3D fluidic devices via material jetting
Liquid-solid co-printing of multi-material 3D fluidic devices via material jetting

Keywords

Additive manufacturing; Mesofluidics; Modeling and simulation; Multi-material; Material jetting

Fig. 5. The predicted shapes of initial breach (a) Rectangular (b) V-notch. Fig. 6. Dam breaching stages.

Investigating the peak outflow through a spatial embankment dam breach

공간적 제방댐 붕괴를 통한 최대 유출량 조사

Mahmoud T.GhonimMagdy H.MowafyMohamed N.SalemAshrafJatwaryFaculty of Engineering, Zagazig University, Zagazig 44519, Egypt

Abstract

Investigating the breach outflow hydrograph is an essential task to conduct mitigation plans and flood warnings. In the present study, the spatial dam breach is simulated by using a three-dimensional computational fluid dynamics model, FLOW-3D. The model parameters were adjusted by making a comparison with a previous experimental model. The different parameters (initial breach shape, dimensions, location, and dam slopes) are studied to investigate their effects on dam breaching. The results indicate that these parameters have a significant impact. The maximum erosion rate and peak outflow for the rectangular shape are higher than those for the V-notch by 8.85% and 5%, respectively. Increasing breach width or decreasing depth by 5% leads to increasing maximum erosion rate by 11% and 15%, respectively. Increasing the downstream slope angle by 4° leads to an increase in both peak outflow and maximum erosion rate by 2.0% and 6.0%, respectively.

유출 유출 수문곡선을 조사하는 것은 완화 계획 및 홍수 경보를 수행하는 데 필수적인 작업입니다. 본 연구에서는 3차원 전산유체역학 모델인 FLOW-3D를 사용하여 공간 댐 붕괴를 시뮬레이션합니다. 이전 실험 모델과 비교하여 모델 매개변수를 조정했습니다.

다양한 매개변수(초기 붕괴 형태, 치수, 위치 및 댐 경사)가 댐 붕괴에 미치는 영향을 조사하기 위해 연구됩니다. 결과는 이러한 매개변수가 상당한 영향을 미친다는 것을 나타냅니다. 직사각형 형태의 최대 침식율과 최대 유출량은 V-notch보다 각각 8.85%, 5% 높게 나타났습니다.

위반 폭을 늘리거나 깊이를 5% 줄이면 최대 침식률이 각각 11% 및 15% 증가합니다. 하류 경사각을 4° 증가시키면 최대 유출량과 최대 침식률이 각각 2.0% 및 6.0% 증가합니다.

Keywords

Spatial dam breach; FLOW-3D; Overtopping erosion; Computational fluid dynamics (CFD)

1. Introduction

There are many purposes for dam construction, such as protection from flood disasters, water storage, and power generationEmbankment failures may have a catastrophic impact on lives and infrastructure in the downstream regions. One of the most common causes of embankment dam failure is overtopping. Once the overtopping of the dam begins, the breach formation will start in the dam body then end with the dam failure. This failure occurs within a very short time, which threatens to be very dangerous. Therefore, understanding and modeling the embankment breaching processes is essential for conducting mitigation plans, flood warnings, and forecasting flood damage.

The analysis of the dam breaching process is implemented by different techniques: comparative methods, empirical models with dimensional and dimensionless solutions, physical-based models, and parametric models. These models were described in detail [1]Parametric modeling is commonly used to simulate breach growth as a time-dependent linear process and calculate outflow discharge from the breach using hydraulics principles [2]. Alhasan et al. [3] presented a simple one-dimensional mathematical model and a computer code to simulate the dam breaching process. These models were validated by small dams breaching during the floods in 2002 in the Czech Republic. Fread [4] developed an erosion model (BREACH) based on hydraulics principles, sediment transport, and soil mechanics to estimate breach size, time of formation, and outflow discharge. Říha et al. [5] investigated the dam break process for a cascade of small dams using a simple parametric model for piping and overtopping erosion, as well as a 2D shallow-water flow model for the flood in downstream areas. Goodarzi et al. [6] implemented mathematical and statistical methods to assess the effect of inflows and wind speeds on the dam’s overtopping failure.

Dam breaching studies can be divided into two main modes of erosion. The first mode is called “planar dam breach” where the flow overtops the whole dam width. While the second mode is called “spatial dam breach” where the flow overtops through the initial pilot channel (i.e., a channel created in the dam body). Therefore, the erosion will be in both vertical and horizontal directions [7].

The erosion process through the embankment dams occurs due to the shear stress applied by water flows. The dam breaching evolution can be divided into three stages [8][9], but Y. Yang et al. [10] divided the breach development into five stages: Stage I, the seepage erosion; Stage II, the initial breach formation; Stage III, the head erosion; Stage IV, the breach expansion; and Stage V, the re-equilibrium of the river channel through the breach. Many experimental tests have been carried out on non-cohesive embankment dams with an initial breach to examine the effect of upstream inflow discharges on the longitudinal profile evolution and the time to inflection point [11].

Zhang et al. [12] studied the effect of changing downstream slope angle, sediment grain size, and dam crest length on erosion rates. They noticed that increasing dam crest length and decreasing downstream slope angle lead to decreasing sediment transport rate. While the increase in sediment grain size leads to an increased sediment transport rate at the initial stages. Höeg et al. [13] presented a series of field tests to investigate the stability of embankment dams made of various materials. Overtopping and piping were among the failure tests carried out for the dams composed of homogeneous rock-fill, clay, or gravel with a height of up to 6.0 m. Hakimzadeh et al. [14] constructed 40 homogeneous cohesive and non-cohesive embankment dams to study the effect of changing sediment diameter and dam height on the breaching process. They also used genetic programming (GP) to estimate the breach outflow. Refaiy et al. [15] studied different scenarios for the downstream drain geometry, such as length, height, and angle, to minimize the effect of piping phenomena and therefore increase dam safety.

Zhu et al. [16] examined the effect of headcut erosion on dam breach growth, especially in the case of cohesive dams. They found that the breach growth in non-cohesive embankments is slower than cohesive embankments due to the little effect of headcut. Schmocker and Hager [7] proposed a relationship for estimating peak outflow from the dam breach process.(1)QpQin-1=1.7exp-20hc23d5013H0

where: Qp = peak outflow discharge.

Qin = inflow discharge.

hc = critical flow depth.

d50 = mean sediment diameter.

Ho = initial dam height.

Yu et al. [17] carried out an experimental study for homogeneous non-cohesive embankment dams in a 180° bending rectangular flume to determine the effect of overtopping flows on breaching formation. They found that the main factors influencing breach formation are water level, river discharge, and embankment material diameter.

Wu et al. [18] carried out a series of experiments to investigate the effect of breaching geometry on both non-cohesive and cohesive embankment dams in a U-bend flume due to overtopping flows. In the case of non-cohesive embankments, the non-symmetrical lateral expansion was noticed during the breach formation. This expansion was described by a coefficient ranging from 2.7 to 3.3.

The numerical models of the dam breach can be categorized according to different parameters, such as flow dimensions (1D, 2D, or 3D), flow governing equations, and solution methods. The 1D models are mainly used to predict the outflow hydrograph from the dam breach. Saberi et al. [19] applied the 1D Saint-Venant equation, which is solved by the finite difference method to investigate the outflow hydrograph during dam overtopping failure. Because of the ability to study dam profile evolution and breach formation, 2D models are more applicable than 1D models. Guan et al. [20] and Wu et al. [21] employed both 2D shallow water equations (SWEs) and sediment erosion equations, which are solved by the finite volume method to study the effect of the dam’s geometry parameters on outflow hydrograph and dam profile evolution. Wang et al. [22] also proposed a second-order hybrid-type of total variation diminishing (TVD) finite-difference to estimate the breach outflow by solving the 2D (SWEs). The accuracy of (SWEs) for both vertical flow contraction and surface roughness has been assessed [23]. They noted that the accuracy of (SWEs) is acceptable for milder slopes, but in the case of steeper slopes, modelers should be more careful. Generally, the accuracy of 2D models is still low, especially with velocity distribution over the flow depth, lateral momentum exchange, density-driven flows, and bottom friction [24]. Therefore, 3D models are preferred. Larocque et al. [25] and Yang et al. [26] started to use three-dimensional (3D) models that depend on the Reynolds-averaged Navier-Stokes (RANS) equations.

Previous experimental studies concluded that there is no clear relationship between the peak outflow from the dam breach and the initial breach characteristics. Some of these studies depend on the sharp-crested weir fixed at the end of the flume to determine the peak outflow from the breach, which leads to a decrease in the accuracy of outflow calculations at the microscale. The main goals of this study are to carry out a numerical simulation for a spatial dam breach due to overtopping flows by using (FLOW-3D) software to find an empirical equation for the peak outflow discharge from the breach and determine the worst-case that leads to accelerating the dam breaching process.

2. Numerical simulation

The current study for spatial dam breach is simulated by using (FLOW-3D) software [27], which is a powerful computational fluid dynamics (CFD) program.

2.1. Geometric presentations

A stereolithographic (STL) file is prepared for each change in the initial breach geometry and dimensions. The CAD program is useful for creating solid objects and converting them to STL format, as shown in Fig. 1.

2.2. Governing equations

The governing equations for water flow are three-dimensional Reynolds Averaged Navier-Stokes equations (RANS).

The continuity equation:(2)∂ui∂xi=0

The momentum equation:(3)∂ui∂t+1VFuj∂ui∂xj=1ρ∂∂xj-pδij+ν∂ui∂xj+∂uj∂xi-ρu`iu`j¯

where u is time-averaged velocity,ν is kinematic viscosity, VF is fractional volume open to flow, p is averaged pressure and -u`iu`j¯ are components of Reynold’s stress. The Volume of Fluid (VOF) technique is used to simulate the free surface profile. Hirt et al. [28] presented the VOF algorithm, which employs the function (F) to express the occupancy of each grid cell with fluid. The value of (F) varies from zero to unity. Zero value refers to no fluid in the grid cell, while the unity value refers to the grid cell being fully occupied with fluid. The free surface is formed in the grid cells having (F) values between zero and unity.(4)∂F∂t+1VF∂∂xFAxu+∂∂yFAyv+∂∂zFAzw=0

where (u, v, w) are the velocity components in (x, y, z) coordinates, respectively, and (AxAyAz) are the area fractions.

2.3. Boundary and initial conditions

To improve the accuracy of the results, the boundary conditions should be carefully determined. In this study, two mesh blocks are used to minimize the time consumed in the simulation. The boundary conditions for mesh block 1 are as follows: The inlet and sides boundaries are defined as a wall boundary condition (wall boundary condition is usually used for bound fluid by solid regions. In the case of viscous flows, no-slip means that the tangential velocity is equal to the wall velocity and the normal velocity is zero), the outlet is defined as a symmetry boundary condition (symmetry boundary condition is usually used to reduce computational effort during CFD simulation. This condition allows the flow to be transferred from one mesh block to another. No inputs are required for this boundary condition except that its location should be defined accurately), the bottom boundary is defined as a uniform flow rate boundary condition, and the top boundary is defined as a specific pressure boundary condition with assigned atmospheric pressure. The boundary conditions for mesh block 2 are as follows: The inlet is defined as a symmetry boundary condition, the outlet is defined as a free flow boundary condition, the bottom and sides boundaries are defined as a wall boundary condition, and the top boundary is defined as a specific pressure boundary condition with assigned atmospheric pressure as shown in Fig. 2. The initial conditions required to be set for the fluid (i.e., water) inside of the domain include configuration, temperature, velocities, and pressure distribution. The configuration of water depends on the dimensions and shape of the dam reservoir. While the other conditions have been assigned as follows: temperature is normal water temperature (25 °c) and pressure distribution is hydrostatic with no initial velocity.

2.4. Numerical method

FLOW-3D uses the finite volume method (FVM) to solve the governing equation (Reynolds-averaged Navier-Stokes) over the computational domain. A finite-volume method is an Eulerian approach for representing and evaluating partial differential equations in algebraic equations form [29]. At discrete points on the mesh geometry, values are determined. Finite volume expresses a small volume surrounding each node point on a mesh. In this method, the divergence theorem is used to convert volume integrals with a divergence term to surface integrals. After that, these terms are evaluated as fluxes at each finite volume’s surfaces.

2.5. Turbulent models

Turbulence is the chaotic, unstable motion of fluids that occurs when there are insufficient stabilizing viscous forces. In FLOW-3D, there are six turbulence models available: the Prandtl mixing length model, the one-equation turbulent energy model, the two-equation (k – ε) model, the Renormalization-Group (RNG) model, the two-equation (k – ω) models, and a large eddy simulation (LES) model. For simulating flow motion, the RNG model is adopted to simulate the motion behavior better than the k – ε and k – ω.

models [30]. The RNG model consists of two main equations for the turbulent kinetic energy KT and its dissipation.εT(5)∂kT∂t+1VFuAx∂kT∂x+vAy∂kT∂y+wAz∂kT∂z=PT+GT+DiffKT-εT(6)∂εT∂t+1VFuAx∂εT∂x+vAy∂εT∂y+wAz∂εT∂z=C1.εTKTPT+c3.GT+Diffε-c2εT2kT

where KT is the turbulent kinetic energy, PT is the turbulent kinetic energy production, GT is the buoyancy turbulence energy, εT is the turbulent energy dissipation rate, DiffKT and Diffε are terms of diffusion, c1, c2 and c3 are dimensionless parameters, in which c1 and c3 have a constant value of 1.42 and 0.2, respectively, c2 is computed from the turbulent kinetic energy (KT) and turbulent production (PT) terms.

2.6. Sediment scour model

The sediment scour model available in FLOW-3D can calculate all the sediment transport processes including Entrainment transport, Bedload transport, Suspended transport, and Deposition. The erosion process starts once the water flows remove the grains from the packed bed and carry them into suspension. It happens when the applied shear stress by water flows exceeds critical shear stress. This process is represented by entrainment transport in the numerical model. After entrained, the grains carried by water flow are represented by suspended load transport. After that, some suspended grains resort to settling because of the combined effect of gravity, buoyancy, and friction. This process is described through a deposition. Finally, the grains sliding motions are represented by bedload transport in the model. For the entrainment process, the shear stress applied by the fluid motion on the packed bed surface is calculated using the standard wall function as shown in Eq.7.(7)ks,i=Cs,i∗d50

where ks,i is the Nikuradse roughness and Cs,i is a user-defined coefficient. The critical bed shear stress is defined by a dimensionless parameter called the critical shields number as expressed in Eq.8.(8)θcr,i=τcr,i‖g‖diρi-ρf

where θcr,i is the critical shields number, τcr,i is the critical bed shear stress, g is the absolute value of gravity acceleration, di is the diameter of the sediment grain, ρi is the density of the sediment species (i) and ρf is the density of the fluid. The value of the critical shields number is determined according to the Soulsby-Whitehouse equation.(9)θcr,i=0.31+1.2d∗,i+0.0551-exp-0.02d∗,i

where d∗,i is the dimensionless diameter of the sediment, given by Eq.10.(10)d∗,i=diρfρi-ρf‖g‖μf213

where μf is the fluid dynamic viscosity. For the sloping bed interface, the value of the critical shields number is modified according to Eq.11.(11)θ`cr,i=θcr,icosψsinβ+cos2βtan2φi-sin2ψsin2βtanφi

where θ`cr,i is the modified critical shields number, φi is the angle of repose for the sediment, β is the angle of bed slope and ψ is the angle between the flow and the upslope direction. The effects of the rolling, hopping, and sliding motions of grains along the packed bed surface are taken by the bedload transport process. The volumetric bedload transport rate (qb,i) per width of the bed is expressed in Eq.12.(12)qb,i=Φi‖g‖ρi-ρfρfdi312

where Φi is the dimensionless bedload transport rate is calculated by using Meyer Peter and Müller equation.(13)Φi=βMPM,iθi-θ`cr,i1.5cb,i

where βMPM,i is the Meyer Peter and Müller user-defined coefficient and cb,i is the volume fraction of species i in the bed material. The suspended load transport is calculated as shown in Eq.14.(14)∂Cs,i∂t+∇∙Cs,ius,i=∇∙∇DCs,i

where Cs,i is the suspended sediment mass concentration, D is the diffusivity, and us,i is the grain velocity of species i. Entrainment and deposition are two opposing processes that take place at the same time. The lifting and settling velocities for both entrainment and deposition processes are calculated according to Eq.15 and Eq.16, respectively.(15)ulifting,i=αid∗,i0.3θi-θ`cr,igdiρiρf-1(16)usettling,i=υfdi10.362+1.049d∗,i3-10.36

where αi is the entrainment coefficient of species i and υf is the kinematic viscosity of the fluid.

2.7. Grid type

Using simple rectangular orthogonal elements in planes and hexahedral in volumes in the (FLOW-3D) program makes the mesh generation process easier, decreases the required memory, and improves numerical accuracy. Two mesh blocks were used in a joined form with a size ratio of 2:1. The first mesh block is coarser, which contains the reservoir water, and the second mesh block is finer, which contains the dam. For achieving accuracy and efficiency in results, the mesh size is determined by using a grid convergence test. The optimum uniform cell size for the first mesh block is 0.012 m and for the second mesh block is 0.006 m.

2.8. Time step

The maximum time step size is determined by using a Courant number, which controls the distance that the flow will travel during the simulation time step. In this study, the Courant number was taken equal to 0.25 to prevent the flow from traveling through more than one cell in the time step. Based on the Courant number, a maximum time step value of 0.00075 s was determined.

2.9. Numerical model validation

The numerical model accuracy was achieved by comparing the numerical model results with previous experimental results. The experimental study of Schmocker and Hager [7] was based on 31 tests with changes in six parameters (d50, Ho, Bo, Lk, XD, and Qin). All experimental tests were conducted in a straight open glass-sided flume. The horizontal flume has a rectangular cross-section with a width of 0.4 m and a height of 0.7 m. The flume was provided with a flow straightener and an intake with a length of 0.66 m. All tested dams were inserted at various distances (XD) from the intake. Test No.1 from this experimental program was chosen to validate the numerical model. The different parameters used in test No.1 are as follows:

(1) uniform sediment with a mean diameter (d50 = 0.31 mm), (2) Ho = 0.2 m, (3) Bo = 0.2 m, (4) Lk = 0.1 m,

(5) XD = 1.0 m, (6) Qin = 6.0 lit/s, (7) Su and Sd = 2:1, (8) mass density (ρs = 2650 kg/m3(9) Homogenous and non-cohesive embankment dam. As shown in Fig. 2, the simulation is contained within a rectangular grid with dimensions: 3.56 m in the x-direction (where 0.66 m is used as inlet, 0.9 m as dam base width, and 1.0 m as outlet), in y-direction 0.2 m (dam length), and in the z-direction 0.3 m, which represents the dam height (0.2 m) with a free distance (0.1 m) above the dam. There are two main reasons that this experimental program is preferred for the validation process. The first reason is that this program deals with homogenous, non-cohesive soil, which is available in FLOW-3D. The second reason is that this program deals with small-scale models which saves time for numerical simulation. Finally, some important assumptions were considered during the validation process. The flow is assumed to be incompressible, viscous, turbulent, and three-dimensional.

By comparing dam profiles at different time instants for the experimental test with the current numerical model, it appears that the numerical model gives good agreement as shown in Fig. 3 and Fig. 4, with an average error percentage of 9% between the experimental results and the numerical model.

3. Analysis and discussions

The current model is used to study the effects of different parameters such as (initial breach shapes, dimensions, locations, upstream and downstream dam slopes) on the peak outflow discharge, QP, time of peak outflow, tP, and rate of erosion, E.

This study consists of a group of scenarios. The first scenario is changing the shapes of the initial breach according to Singh [1], the most predicted shapes are rectangular and V-notch as shown in Fig. 5. The second scenario is changing the initial breach dimensions (i.e., width and depth). While the third scenario is changing the location of the initial breach. Eventually, the last scenario is changing the upstream and downstream dam slopes.

All scenarios of this study were carried out under the same conditions such as inflow discharge value (Qin=1.0lit/s), dimensions of the tested dam, where dam height (Ho=0.20m), crest width.

(Lk=0.1m), dam length (Bo=0.20m), and homogenous & non-cohesive soil with a mean diameter (d50=0.31mm).

3.1. Dam breaching process evolution

The dam breaching process is a very complex process due to the quick changes in hydrodynamic conditions during dam failure. The dam breaching process starts once water flows reach the downstream face of the dam. During the initial stage of dam breaching, the erosion process is relatively quiet due to low velocities of flow. As water flows continuously, erosion rates increase, especially in two main zones: the crest and the downstream face. As soon as the dam crest is totally eroded, the water levels in the dam reservoir decrease rapidly, accompanied by excessive erosion in the dam body. The erosion process continues until the water levels in the dam reservoir equal the remaining height of the dam.

According to Zhou et al. [11], the breaching process consists of three main stages. The first stage starts with beginning overtopping flow, then ends when the erosion point directed upstream and reached the inflection point at the inflection time (ti). The second stage starts from the end of the stage1 until the occurrence of peak outflow discharge at the peak outflow time (tP). The third stage starts from the end of the stage2 until the value of outflow discharge becomes the same as the value of inflow discharge at the final time (tf). The outflow discharge from the dam breach increases rapidly during stage1 and stage2 because of the large dam storage capacity (i.e., the dam reservoir is totally full of water) and excessive erosion. While at stage3, the outflow values start to decrease slowly because most of the dam’s storage capacity was run out. The end of stage3 indicates that the dam storage capacity was totally run out, so the outflow equalized with the inflow discharge as shown in Fig. 6 and Fig. 7.

3.2. The effect of initial breach shape

To identify the effect of the initial breach shape on the evolution of the dam breaching process. Three tests were carried out with different cross-section areas for each shape. The initial breach is created at the center of the dam crest. Each test had an ID to make the process of arranging data easier. The rectangular shape had an ID (Rec5h & 5b), which means that its depth and width are equal to 5% of the dam height, and the V-notch shape had an ID (V-noch5h & 1:1) which means that its depth is equal to 5% of the dam height and its side slope is equal to 1:1. The comparison between rectangular and V-notch shapes is done by calculating the ratio between maximum dam height at different times (ZMax) to the initial dam height (Ho), rate of erosion, and hydrograph of outflow discharge for each test. The rectangular shape achieves maximum erosion rate and minimum inflection time, in addition to a rapid decrease in the dam reservoir levels. Therefore, the dam breaching is faster in the case of a rectangular shape than in a V-notch shape, which has the same cross-section area as shown in Fig. 8.

Also, by comparing the hydrograph for each test, the peak outflow discharge value in the case of a rectangular shape is higher than the V-notch shape by 5% and the time of peak outflow for the rectangular shape is shorter than the V-notch shape by 9% as shown in Fig. 9.

3.3. The effect of initial breach dimensions

The results of the comparison between the different initial breach shapes indicate that the worst initial breach shape is rectangular, so the second scenario from this study concentrated on studying the effect of a change in the initial rectangular breach dimensions. Groups of tests were carried out with different depths and widths for the rectangular initial breach. The first group had a depth of 5% from the dam height and with three different widths of 5,10, and 15% from the dam height, the second group had a depth of 10% with three different widths of 5,10, and 15%, the third group had a depth of 15% with three different widths of 5,10, and 15% and the final group had a width of 15% with three different heights of 5, 10, and 15% for a rectangular breach shape. The comparison was made as in the previous section to determine the worst case that leads to the quick dam failure as shown in Fig. 10.

The results show that the (Rec 5 h&15b) test achieves a maximum erosion rate for a shorter period of time and a minimum ratio for (Zmax / Ho) as shown in Fig. 10, which leads to accelerating the dam failure process. The dam breaching process is faster with the minimum initial breach depth and maximum initial breach width. In the case of a minimum initial breach depth, the retained head of water in the dam reservoir is high and the crest width at the bottom of the initial breach (L`K) is small, so the erosion point reaches the inflection point rapidly. While in the case of the maximum initial breach width, the erosion perimeter is large.

3.4. The effect of initial breach location

The results of the comparison between the different initial rectangular breach dimensions indicate that the worst initial breach dimension is (Rec 5 h&15b), so the third scenario from this study concentrated on studying the effect of a change in the initial breach location. Three locations were checked to determine the worst case for the dam failure process. The first location is at the center of the dam crest, which was named “Center”, the second location is at mid-distance between the dam center and dam edge, which was named “Mid”, and the third location is at the dam edge, which was named “Edge” as shown in Fig. 11. According to this scenario, the results indicate that the time of peak outflow discharge (tP) is the same in the three cases, but the maximum value of the peak outflow discharge occurs at the center location. The difference in the peak outflow values between the three cases is relatively small as shown in Fig. 12.

The rates of erosion were also studied for the three cases. The results show that the maximum erosion rate occurs at the center location as shown in Fig. 13. By making a comparison between the three cases for the dam storage volume. The results show that the center location had the minimum values for the dam storage volume, which means that a large amount of water has passed to the downstream area as shown in Fig. 14. According to these results, the center location leads to increased erosion rate and accelerated dam failure process compared with the two other cases. Because the erosion occurs on both sides, but in the case of edge location, the erosion occurs on one side.

3.5. The effect of upstream and downstream dam slopes

The results of the comparison between the different initial rectangular breach locations indicate that the worst initial breach location is the center location, so the fourth scenario from this study concentrated on studying the effect of a change in the upstream (Su) and downstream (Sd) dam slopes. Three slopes were checked individually for both upstream and downstream slopes to determine the worst case for the dam failure process. The first slope value is (2H:1V), the second slope value is (2.5H:1V), and the third slope value is (3H:1V). According to this scenario, the results show that the decreasing downstream slope angle leads to increasing time of peak outflow discharge (tP) and decreasing value of peak outflow discharge. The difference in the peak outflow values between the three cases for the downstream slope is 2%, as shown in Fig. 15, but changing the upstream slope has a negligible impact on the peak outflow discharge and its time as shown in Fig. 16.

The rates of erosion were also studied in the three cases for both upstream and downstream slopes. The results show that the maximum erosion rate increases by 6.0% with an increasing downstream slope angle by 4°, as shown in Fig. 17. The results also indicate that the erosion rates aren’t affected by increasing or decreasing the upstream slope angle, as shown in Fig. 18. According to these results, increasing the downstream slope angle leads to increased erosion rate and accelerated dam failure process compared with the upstream slope angle. Because of increasing shear stress applied by water flows in case of increasing downstream slope.

According to all previous scenarios, the dimensionless peak outflow discharge QPQin is presented for a fixed dam height (Ho) and inflow discharge (Qin). Fig. 19 illustrates the relationship between QP∗=QPQin and.

Lr=ho2/3∗bo2/3Ho. The deduced relationship achieves R2=0.96.(17)QP∗=2.2807exp-2.804∗Lr

4. Conclusions

A spatial dam breaching process was simulated by using FLOW-3D Software. The validation process was performed by making a comparison between the simulated results of dam profiles and the dam profiles obtained by Schmocker and Hager [7] in their experimental study. And also, the peak outflow value recorded an error percentage of 12% between the numerical model and the experimental study. This model was used to study the effect of initial breach shape, dimensions, location, and dam slopes on peak outflow discharge, time of peak outflow, and the erosion process. By using the parameters obtained from the validation process, the results of this study can be summarized in eight points as follows.1.

The rectangular initial breach shape leads to an accelerating dam failure process compared with the V-notch.2.

The value of peak outflow discharge in the case of a rectangular initial breach is higher than the V-notch shape by 5%.3.

The time of peak outflow discharge for a rectangular initial breach is shorter than the V-notch shape by 9%.4.

The minimum depth and maximum width for the initial breach achieve maximum erosion rates (increasing breach width, b0, or decreasing breach depth, h0, by 5% from the dam height leads to an increase in the maximum rate of erosion by 11% and 15%, respectively), so the dam failure is rapid.5.

The center location of the initial breach leads to an accelerating dam failure compared with the edge location.6.

The initial breach location has a negligible effect on the peak outflow discharge value and its time.7.

Increasing the downstream slope angle by 4° leads to an increase in both peak outflow discharge and maximum rate of erosion by 2.0% and 6.0%, respectively.8.

The upstream slope has a negligible effect on the dam breaching process.

References

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Figure 2: Temperature contours and melt pool border lines at different times for the 50 % duty cycle case: (a) - (c) Δtcycle = 400 μs, (d) – (f) Δtcycle = 1000 μs and (g) – (i) Δtcycle = 3000 μs.

MULTIPHYSICS SIMULATION OF THEMRAL AND FLUID DYNAMICS PHENOMENA DURING THE PULSED LASER POWDER BED FUSION PROCESS OF 316-L STEEL

M. Bayat* , V. K. Nadimpalli, J. H. Hattel
1Department of Mechanical Engineering, Technical University of Denmark (DTU), Produktionstorvet
425, Kgs. 2800, Lyngby, Denmark

ABSTRACT

L-PBF(Laser Powder Bed Fusion)는 다양한 산업 분야에서 많은 관심을 받았으며, 주로 기존 제조 기술을 사용하여 만들 수 없었던 복잡한 토폴로지 최적화 구성 요소를 구현하는 잘 알려진 능력 덕분입니다. . 펄스 L-PBF(PL-PBF)에서 레이저의 시간적 프로파일은 주기 지속 시간과 듀티 주기 중 하나 또는 둘 다를 수정하여 변조할 수 있습니다. 따라서 레이저의 시간적 프로파일은 향후 적용을 위해 이 프로세스를 더 잘 제어할 수 있는 길을 열어주는 새로운 프로세스 매개변수로 간주될 수 있습니다. 따라서 이 작업에서 우리는 레이저의 시간적 프로파일을 변경하는 것이 PL-PBF 공정에서 용융 풀 조건과 트랙의 최종 모양 및 형상에 어떻게 영향을 미칠 수 있는지 조사하는 것을 목표로 합니다. 이와 관련하여 본 논문에서는 CFD(Computational Fluid Dynamics) 소프트웨어 패키지인 Flow-3D를 기반으로 하는 316-L 스테인리스강 PL-PBF 공정의 다중물리 수치 모델을 개발하고 이 모델을 사용하여 열과 유체를 시뮬레이션합니다. 다양한 펄스 모드에서 공정 과정 중 용융 풀 내부에서 발생하는 유동 조건. 따라서 고정된 레이저 듀티 사이클(50%)이 있는 레이저 주기 지속 시간이 용융 풀의 모양과 크기 및 최종 트랙 형태에 미치는 영향을 연구하기 위해 매개변수 연구가 수행됩니다. 더 긴 주기 기간에서 더 많은 재료가 더 큰 용융 풀 내에서 변위됨에 따라 용융 풀의 후류에 더 눈에 띄는 혹이 형성되며, 동시에 더 심각한 반동 압력을 받습니다. 또한 시뮬레이션에서 50% 듀티 사이클에서 1000μs에서 형성된 보다 대칭적인 용융 풀과 비교하여 400μs 사이클 주기에서 더 긴 용융 풀이 형성된다는 것이 관찰되었습니다. 풀 볼륨은 1000μs의 경우 더 큽니다. 매개변수 연구는 연속 트랙과 파손된 트랙 PL-PBF 사이의 경계를 설명하며, 여기서 연속 트랙은 항상 소량의 용융 재료를 유지함으로써 유지됩니다.

English Abstract

Laser Powder Bed Fusion (L-PBF) has attracted a lot of attention from various industrial sectors and mainly thanks to its well-proven well-known capacity of realizing complex topology-optimized components that have so far been impossible to make using conventional manufacturing techniques. In Pulsed L-PBF (PL-PBF), the laser’s temporal profile can be modulated via modifying either or both the cycle duration and the duty cycle. Thus, the laser’s temporal profile could be considered as a new process parameter that paves the way for a better control of this process for future applications. Therefore, in this work we aim to investigate how changing the laser’s temporal profile can affect the melt pool conditions and the final shape and geometry of a track in the PL-PBF process. In this respect, in this paper a multiphysics numerical model of the PL-PBF process of 316-L stainless steel is developed based on the computational fluid dynamics (CFD) software package Flow-3D and the model is used to simulate the heat and fluid flow conditions occurring inside the melt pool during the course of the process at different pulsing modes. Thus, a parametric study is carried out to study the influence of the laser’s cycle duration with a fixed laser duty cycle (50 %) on the shape and size of the melt pool and the final track morphology. It is noticed that at longer cycle periods, more noticeable humps form at the wake of the melt pool as more material is displaced within bigger melt pools, which are at the same time subjected to more significant recoil pressures. It is also observed in the simulations that at 50 % duty cycle, longer melt pools form at 400 μs cycle period compared to the more symmetrical melt pools formed at 1000 μs, primarily because of shorter laser off-times in the former, even though melt pool volume is bigger for the 1000 μs case. The parameteric study illustrates the boundary between a continuous track and a broken track PL-PBF wherein the continuous track is retained by always maintaining a small volume of molten material.

Figure 1: Front and side views of the computational domain. Note that the region along z and from -100 μm to +50 μm is void.
Figure 1: Front and side views of the computational domain. Note that the region along z and from -100 μm to +50 μm is void.
Figure 2: Temperature contours and melt pool border lines at different times for the 50 % duty cycle case: (a) - (c) Δtcycle = 400 μs, (d) – (f) Δtcycle = 1000 μs and (g) – (i) Δtcycle = 3000 μs.
Figure 2: Temperature contours and melt pool border lines at different times for the 50 % duty cycle case: (a) – (c) Δtcycle = 400 μs, (d) – (f) Δtcycle = 1000 μs and (g) – (i) Δtcycle = 3000 μs.
Figure 3: Plot of melt pool volume versus time for four cases including continuous wave laser as well as 50 % duty cycle at 400 μs, 1000 μs and 3000 μs.
Figure 3: Plot of melt pool volume versus time for four cases including continuous wave laser as well as 50 % duty cycle at 400 μs, 1000 μs and 3000 μs.

CONCLUSIONS

In this work a CFD model of the modulated PL-PBF process of stainless steel 316-L is developed in the commercial software package Flow-3D. The model involves physics such as solidification, melting, evaporation, convection, laser-material interaction, capillarity, Marangoni effect and the recoil pressure effect. In the current study, a parametric study is carried out to understand how the change in the cycle period duration affects the melt pool’s thermo-fluid conditions during the modulated PL-PBF process. It is observed that at the pulse mode with 50 % duty cycle and 400 μs cycle period, an overlapped chain of humps form at the wake of the melt pool and at a spatial frequency of occurrence of about 78 μm. Furthermore and as expected, it is noted that the melt pool volume, the size of the hump as well as the crater size at the end of the track, increase with increase in the cycle period duration, as more material is re-deposited at the back of the melt pool and that itself is caused by more pronounced recoil pressures. Moreover, it is noticed that due to the short off-time period of the laser in the 400 μs cycle period case, there is always an amount of liquid metal left from the previous cycle, at the time the new cycle starts. This is found to be the main reason why longer and elongated melt pools form at 400 μs cycle period, compared to the bigger, shorter and more symmetrical-like melt pools forming at the 1000 μs case. In this study PL-PBF single tracks including the broken track and the continuous track examples were studied to illustrate the boundary of this transition at a given laser scan parameter setting. At higher scan speeds, it is expected that the Plateau–Rayleigh instability will compete with the pulsing behavior to change the transition boundary between a broken and continuous track, which is suggested as future work from this study.

REFERENCES

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zones, Acta Mater. 108 (2016) 36–45. https://doi.org/10.1016/j.actamat.2016.02.014.
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Effect of roughness on separation zone dimensions.

Experimental and numerical study of flow at a 90 degree lateral turnout with enhanced roughness coefficient and invert level changes

조도 계수 및 역전 수준 변화가 개선된 90도 측면 분출구에서의 유동에 대한 실험적 및 수치적 연구

Maryam BagheriSeyed M. Ali ZomorodianMasih ZolghadrH. Md. AzamathullaC. Venkata Siva Rama Prasad

Abstract

측면 분기기(흡입구)의 상류 측에서 흐름 분리는 분기기 입구에서 와류를 일으키는 중요한 문제입니다. 이는 흐름의 유효 폭, 출력 용량 및 효율성을 감소시킵니다. 따라서 분리지대의 크기를 파악하고 크기를 줄이기 위한 방안을 제시하는 것이 필수적이다. 본 연구에서는 분리 구역의 치수를 줄이기 위한 방법으로 7가지 유형의 거칠기 요소를 분기구 입구에 설치하고 4가지 다른 배출(총 84번의 실험을 수행)과 함께 3개의 서로 다른 베드 반전 레벨을 조사했습니다. 또한 3D CFD(Computational Fluid Dynamics) 모델을 사용하여 분리 영역의 흐름 패턴과 치수를 평가했습니다. 결과는 거칠기 계수를 향상시키면 분리 영역 치수를 최대 38%까지 줄일 수 있는 반면, 드롭 구현 효과는 사용된 거칠기 계수를 기반으로 이 영역을 다르게 축소할 수 있음을 보여주었습니다. 두 가지 방법을 결합하면 분리 영역 치수를 최대 63%까지 줄일 수 있습니다.

Flow separation at the upstream side of lateral turnouts (intakes) is a critical issue causing eddy currents at the turnout entrance. It reduces the effective width of flow, turnout capacity and efficiency. Therefore, it is essential to identify the dimensions of the separation zone and propose remedies to reduce its dimensions. Installation of 7 types of roughening elements at the turnout entrance and 3 different bed invert levels, with 4 different discharges (making a total of 84 experiments) were examined in this study as a method to reduce the dimensions of the separation zone. Additionally, a 3-D Computational Fluid Dynamic (CFD) model was utilized to evaluate the flow pattern and dimensions of the separation zone. Results showed that enhancing the roughness coefficient can reduce the separation zone dimensions up to 38% while the drop implementation effect can scale down this area differently based on the roughness coefficient used. Combining both methods can reduce the separation zone dimensions up to 63%.

HIGHLIGHTS

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  • Flow separation at the upstream side of lateral turnouts (intakes) is a critical issue causing eddy currents at the turnout entrance.
  • Installation of 7 types of roughening elements at the turnout entrance and 3 different bed level inverts were investigated.
  • Additionally, a 3-D Computational Fluid Dynamic (CFD) model was utilized to evaluate the flow.
  • Combining both methods can reduce the separation zone dimensions by up to 63%.
Experimental and numerical study of flow at a 90 degree lateral turnout with enhanced roughness coefficient and invert level changes
Experimental and numerical study of flow at a 90 degree lateral turnout with enhanced roughness coefficient and invert level changes

Keywords

discharge ratioflow separation zoneintakethree dimensional simulation

INTRODUCTION

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Turnouts or intakes are amongst the oldest and most widely used hydraulic structures in irrigation networks. Turnouts are also used in water distribution, transmission networks, power generation facilities, and waste water treatment plants etc. The flows that enter a turnout have a strong momentum in the direction of the main waterway and that is why flow separation occurs inside the turnout. The horizontal vortex formed in the separation area is a suitable place for accumulation and deposition of sediments. The separation zone is a vulnerable area for sedimentation and for reduction of effective flow due to a contracted flow region in the lateral channel. Sedimentaion in the entrance of the intake can gradually be transfered into the lateral channel and decrease the capacity of the higher order channels over time (Jalili et al. 2011). On the other hand, the existence of coarse-grained materials causes erosion and destruction of the waterway side walls and bottom. In addition, sedimentation creates conditions for vegetation to take root and damage the waterway cover, which causes water to leak from its perimeter. Therefore, it is important to investigate the pattern of the flow separation area in turnouts and provide solutions to reduce the dimensions of this area.

The three-dimensional flow structure at turnouts is quite complex. In an experimental study by Neary & Odgaard (1993) in a 90-degree water turnout it was found that the secondary currents and separation zone varies from the bed to the water surface. They also found that at a 90-degree water turnout, the bed roughness and discharge ratio play a critical role in flow structure. They asserted that an explanation of sediment behavior at a diversion entrance requires a comprehensive understanding of 3D flow patterns around the lateral-channel entrance. In addition, they suggested that there is a strong similarity between flow in a channel bend and a diversion channel, and that this similarity can rationalize the use of bend flow models for estimation of 3D flow structures in diversion channels.

Some of the distinctive characteristics of dividing flow in a turnout include a zone of separation immediately near the entrance of the lateral turnout (separation zone), a contracted flow region in the branch channel (contracted flow), and a stagnation point near the downstream corner of the junction (stagnation zone). In the region downstream of the junction, along the continuous far wall, separation due to flow expansion may occur (Ramamurthy et al. 2007), that is, a separation zone. This can both reduce the turnout efficiency and the effective width of flow while increasing the sediment deposition in the turnout entrance (Jalili et al. 2011). Installation of submerged vanes in the turnout entrance is a method which is already applied to reduce the size of flow separation zones. The separation zone draws sediments and floating materials into themselves. This reduces effective cross-section area and reduces transmission capacity. These results have also been obtained in past studies, including by Ramamurthy et al. (2007) and in Jalili et al. (2011). Submerged vanes (Iowa vanes) are designed in order to modify the near-bed flow pattern and bed-sediment motion in the transverse direction of the river. The vanes are installed vertically on the channel bed, at an angle of attack which is usually oriented at 10–25 degrees to the local primary flow direction. Vane height is typically 0.2–0.5 times the local water depth during design flow conditions and vane length is 2–3 times its height (Odgaard & Wang 1991). They are vortex-generating devices that generate secondary circulation, thereby redistributing sediment within the channel cross section. Several factors affect the flow separation zone such as the ratio of lateral turnout discharge to main channel discharge, angle of lateral channel with respect to the main channel flow direction and size of applied submerged vanes. Nakato et al. (1990) found that sediment management using submerged vanes in the turnout entrance to Station 3 of the Council Bluffs plant, located on the Missouri River, is applicable and efficient. The results show submerged vanes are an appropriate solution for reduction of sediment deposition in a turnout entrance. The flow was treated as 3D and tests results were obtained for the flow characteristics of dividing flows in a 90-degree sharp-edged, junction. The main and lateral channel were rectangular with the same dimensions (Ramamurthy et al., 2007).

Keshavarzi & Habibi (2005) carried out experiments on intake with angles of 45, 67, 79 and 90 degrees in different discharge ratios and reported the optimum angle for inlet flow with the lowest flow separation area to be about 55 degrees. The predicted flow characteristics were validated using experimental data. The results indicated that the width and length of the separation zone increases with the increase in the discharge ratio Qr (ratio of outflow per unit width in the turnout to inflow per unit width in the main channel).

Abbasi et al. (2004) performed experiments to investigate the dimensions of the flow separation zone at a lateral turnout entrance. They demonstrated that the length and width of the separation zone decreases with the increasing ratio of lateral turn-out discharge. They also found that with a reducing angle of lateral turnout, the length of the separation zone scales up and width of separation zone reduces. Then they compared their observations with results of Kasthuri & Pundarikanthan (1987) who conducted some experiments in an open-channel junction formed by channels of equal width and an angle of lateral 90 degree turnout, which showed the dimensions of the separation zone in their experiments to be smaller than in previous studies. Kasthuri & Pundarikanthan (1987) studied vortex and flow separation dimensions at the entrance of a 90 degree channel. Results showed that increasing the diversion discharge ratio can reduce the length and width of the vortex area. They also showed that the length and width of the vortex area remain constant at diversion ratios greater than 0.7. Karami Moghaddam & Keshavarzi (2007) analyzed the flow characteristics in turnouts with angles of 55 and 90 degrees. They reported that the dimensions of the separation zone decrease by increasing the discharge ratio and reducing the turnout angle with respect to the main channel. Studies about flow separation zone can be found in Jalili et al. (2011)Nikbin & Borghei (2011)Seyedian et al. (2008).

Jamshidi et al. (2016) measured the dimensions of a flow separation zone in the presence of submerged vanes with five arrangements (parallel, stagger, compound, piney and butterflies). Results showed that the ratio of the width to the length of the separation zone (shape index) was between 0.2 and 0.28 for all arrangements.

Karami et al. (2017) developed a 3D computational fluid dynamic (CFD) code which was calibrated by measured data. They used the model to evaluate flow pattern, diversion ratio of discharge, strength of the secondary flow, and dimensions of the vortex inside the channel in various dikes and submerged vane installation scenarios. Results showed that the diversion ratio of discharge in the diversion channel is dependent on the width of the flow separation area in the main channel. A dike, perpendicular to the flow, doubles the ratio of diverted discharge and reduces the suspended sediment load compared with the base-line situation by creating outer arch conditions. In addition, increasing the longitudinal distance between vanes increases the velocity gradient between the vanes and leads to a more severe erosion of the bed near the vanes.Figure 1VIEW LARGEDOWNLOAD SLIDE

Laboratory channel dimensions.

Al-Zubaidy & Hilo (2021) used the Navier–Stokes equation to study the flow of incompressible fluids. Using the CFD software ANSYS Fluent 19.2, 3D flow patterns were simulated at a diversion channel. Their results showed good agreement using the comparison between the experimental and numerical results when the k-omega turbulence viscous model was employed. Simulation of the flow pattern was then done at the lateral channel junction using a variety of geometry designs. These improvements included changing the intake’s inclination angle and chamfering and rounding the inner corner of the intake mouth instead of the sharp edge. Flow parameters at the diversion including velocity streamlines, bed shear stress, and separation zone dimensions were computed in their study. The findings demonstrated that changing the 90° lateral intake geometry can improve the flow pattern and bed shear stress at the intake junction. Consequently, sedimentation and erosion problems are reduced. According to the conclusions of their study, a branching angle of 30° to 45° is the best configuration for increasing branching channel discharge, lowering branching channel sediment concentration.

The review of the literature shows that most of the studies deal with turnout angle, discharge ratio and implementation of vanes as techniques to reduce the area of the separation zone. This study examines the effect of roughness coefficient and drop implementation at the entrance of a 90-degree lateral turnout on the dimensions of the separation zone. As far as the authors are aware, these two variables have never been studied as a remedy to decrease the separation zone dimensions whilst enhancing turnout efficiency. Additionally, a three-dimensional numerical model is applied to simulate the flow pattern around the turnout. The numerical results are verified against experimental data.

METHOD

Experimental setup

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The experiments were conducted in a 90 degree dividing flow laboratory channel. The main channel is 15 m long, 0.5 m wide and 0.4 m high and the branch channel is 3 m long, 0.35 m wide and 0.4 m high, as shown in Figure 1. The tests were carried out at 9.65 m from the beginning of the flume and were far enough from the inlet, so we were sure that the flow was fully developed. According to Kirkgöz & Ardiçlioğlu (1997) the length of the developing region would be approximantly 65 and 72 times the flow depth. In this study, the depth is 9 cm, which makes this condition.

Both the main and lateral channel had a slope of 0.0003 with side walls of concrete. A 100 hp pump discharged the water into a stilling basin at the entrance of the main flume. The discharge was measured using an ultrasonic discharge meter around the discharge pipe. Eighty-four experiments in total were carried out at range of 0.1<Fr<0.4 (Froude numbers in main channel and upstream of turnout). The depth of water in the main channel in the experiments was 9 cm, in which case the effect of surface tension can be considered; according to research by Zolghadr & Shafai Bejestan (2020) and Zolghadr et al. (2021), when the water depth is more than 6 cm, the effect of surface tension is reduced and can be ignored given that the separation phenomenon occurs in the boundary layer, the height of the roughness creates disturbances in growth and development of the boundary layer and, as a result, separation growth is also faced with disruption and its dimensions grow less compared to smooth surfaces. Similar conditions occur in case of drop implementation. A disturbance occurs in the growth of the boundary layer and as a result the separation zone dimensions decrease. In order to investigate the effect of roughness coefficient and drop implementation on the separation zone dimensions, four different discharges (16, 18, 21, 23 l/s) in subcritical conditions, seven Manning (Strickler) roughness coefficients (0.009, 0.011, 0.017, 0.023, 0.028, 0.030, 0.032) as shown in Figure 2 and three invert elevation differences between the main channel and lateral turnout invert (0, 5 and 10 cm) at the entrance of the turnout were considered. The Manning roughness coefficient values were selected based on available and feasible values for real conditions, so that 0.009 is equivalent to galvanized sheet roughness and selected for the baseline tests. 0.011 is for concrete with neat surface, 0.017 and 0.023 are for unfinished and gunite concrete respectively. 0.030 and 0.032 values are for concrete on irregular excavated rock (Chow 1959). The roughness coefficients were created by gluing sediment particles on a thin galvanized sheet which was installed at the upstream side of the lateral turnout. The values of roughness coefficients were calculated based on the Manning-Strickler formula. For this purpose, some uniformly graded sediment samples were prepared and the Manning roughness coefficient of each sample was determined with respect to the median size (D50) value pasted into the Manning-Strickler formula. Some KMnO4 was sifted in the main channel upstream to visualize and measure the dimensions of the separation zone. Consequently, when KMnO4 approached the lateral turnout a photo of the separation zone was taken from a top view. All the experiments were recorded and several photos were taken during the experiment after stablishment of steady flow conditions. The photos were then imported to AutoCAD to measure the separation zone dimensions. Because all the shooting was done with a high-definition camera and it was possible to zoom in, the results are very accurate.Figure 2VIEW LARGEDOWNLOAD SLIDE

Roughness plates.

The velocity values were also recorded by a one-dimensional velocity meter at 15 cm distance from the turnout entrance and in transverse direction (perpendicular to the flow direction).

The water level was also measured by depth gauges with a accuracy of 0.1 mm, and velocity in one direction with a single-dimensional KENEK LP 1100 with an accuracy of ±0.02 m/s (0–1 m/s), ± 0.04 m/s (1–2 m/s), ± 0.08 m/s (2–4 m/s), ±0.10 m/s (4–5 m/s).

Numerical simulation

ListenA FLOW-3D numerical model was utilized as a solver of the Navier-Stokes equation to simulate the three-dimensional flow field at the entrance of the turnout. The governing equations included continuity momentum equations. The continuity equation, regardless of the density of the fluid in the form of Cartesian coordinates x, y, and z, is as follows:

formula

(1)where uv, and w represent the velocity components in the x, y, and z directions, respectively; AxAy, and Az are the surface flow fractions in the xy, and z directions, respectively; VF denotes flow volume fraction; r is the density of the fluid; t is time; and Rsor refers to the source of the mass. Equations (2)–(4) show momentum equations in xy and z dimensions respectively :

formula

(2)

formula

(3)

formula

(4)where GxGy, and Gz are the accelerations caused by gravity in the xy, and z directions, respectively; and fxfy, and fz are the accelerations caused by viscosity in the xy, and z directions, respectively.

The turbulence models used in this study were the renormalized group (RNG) models. Evaluation of the concordance of the mentioned models with experimental studies showed that the RNG model provides more accurate results.

Two blocks of mesh were used to simulate the main channels and lateral turnout. The meshes were denser in the vicinity of the entrance of the turnout in order to increase the accuracy of computations. Boundary conditions for the main mesh block included inflow for the channel entrance (volumetric flow rate), outflow for the channel exit, ‘wall’ for the bed and the right boundary and ‘symmetry’ for the top (free surface) and left boundaries (turnout). The side wall roughness coefficient was given to the software as the Manning number in surface roughness of any component. Considering the restrictions in the available processor, a main mesh block with appropriate mesh size was defined to simulate the main flow field in the channel, while the nested mesh-block technique was utilized to create a very dense solution field near the roughness plate in order to provide accurate results around the plates and near the entrance of the lateral turnout. This technique reduced the number of required mesh elements by up to 60% in comparison with the method in which the mesh size of the main solution field was decreased to the required extent.

The numerical outputs are verified against experimental data. The hydraulic characteristics of the experiment are shown in Table 1.Table 1

Hydraulic conditions of the flow

Q(L/s)FrY1 (m)Q2/Q1
16 0.449 0.09 0.22 
18 0.335 0.09 0.61 
21 0.242 0.09 0.71 
23 0.180 0.09 1.04 

RESULTS AND DISCUSSION

Experimental results

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During the experiments, the dimensions of the separation zone were recorded with an HD camera. Some photos were imported to AutoCad software. Then, the separation zones dimensions were measured and compared in different scenarios.

At the beginning, the flow pattern in the separation zone for four different hydraulic conditions was studied for seven different Manning roughness coefficients from 0.009 to 0.032. To compare the obtained results, roughness of 0.009 was considered as the base line. The percentage of reduction in separation zone area in different roughness coefficients is shown in Figure 3. According to this figure, by increasing the roughness of the turnout side wall, the separation zone area ratio reduces (ratio of separation zone area to turnout area). In other words, in any desired Froud number, the highest dimensions of the separation zone area are related to the lowest roughness coefficients. In Figure 3, ‘A’ is the area of the separation zone and ‘Ai’ represents the total area of the turnout.Figure 3VIEW LARGEDOWNLOAD SLIDE

Effect of roughness on separation zone dimensions.Figure 4VIEW LARGEDOWNLOAD SLIDE

Effect of roughness on separation zone dimensions.

It should be mentioned that the separation zone dimensions change with depth, so that the area is larger at the surface than near the bed. This study measured the dimensions of this area at the surface. Figure 4 show exactly where the roughness elements were located.Figure 5VIEW LARGEDOWNLOAD SLIDE

Comparison of separation zone for n=0.023 and n=0.032.

Figure 5 shows images of the separation zone at n=0.023 and n=0.032 as examples, and show that the separation area at n=0.032 is smaller than that of n=0.023.

The difference between the effect of the two 0.032 and 0.030 roughnesses is minor. In other words, the dimensions of the separation zone decreased by increasing roughness up to 0.030 and then remained with negligable changes.

In the next step, the effect of intake invert relative to the main stream (drop) on the dimensions of the separation zone was investigated. To do this, three different invert levels were considered: (1) without drop; (2) a 5 cm drop between the main canal and intake canal; and (3) a 10 cm drop between the main canal and intake canal. The without drop mode was considered as the control state. Figure 6 shows the effect of drop implementation on separation zone dimensions. Tables 2 and 3 show the reduced percentage of separation zone areas in 5 and 10 cm drop compared to no drop conditions as the base line. It was found that the best results were obtained when a 10 cm drop was implemented.Table 2

Decrease percentage of separation zone area in 5 cm drop

Frn=0.011n=0.017n=0.023n=0.028n=0.030n=0.032
0.08 10.56 11.06 25.27 33.03 35.57 36.5 
0.121 7.66 11.14 11.88 15.93 34.59 36.25 
0.353 1.38 2.63 8.17 14.39 31.20 31.29 
0.362 11.54 19.56 25.73 37.89 38.31 

Table 3

Decrease percentage of separation zone area in 10 cm drop

Frn=0.011n=0.017n=0.023n=0.028n=0.030n=0.032
0.047 4.30 8.75 23.47 31.22 34.96 35.13 
0.119 11.01 13.16 15.02 21.48 39.45 40.68 
0.348 3.89 5.71 9.82 16.09 29 30.96 
0.354 2.84 10.44 18.42 25.45 35.68 35.76 

Figure 6VIEW LARGEDOWNLOAD SLIDE

Effect of drop implementation on separation zone dimensions.

The combined effect of drop and roughness is shown in Figure 7. According to this figure, by installing a drop structure at the entrance of the intake, the dimensions of the separation zone scales down in any desired roughness coefficient. Results indicated that by increasing the roughness coefficient or drop implementation individually, the separation zone area decreases up to 38 and 25% respectively. However, employing both techniques simultaneously can reduce the separation zone area up to 63% (Table 4). The reason for the reduction of the dimensions of the separation zone area by drop implementation can be attributed to the increase of discharge ratio. This reduces the dimensions of the separation zone area.Table 4

Reduction in percentage of combined effect of roughness and 10 cm drop

Qin=0.011n=0.017n=0.023n=0.028n=0.030n=0.032
16 32.3 35.07 37.2 45.7 58.01 59.1 
18 44.5 34.15 36.18 48.13 54.2 56.18 
21 43.18 32.33 42.30 37.79 57.16 63.2 
23 40.56 34.5 34.09 46.25 50.12 57.2 

Figure 7VIEW LARGEDOWNLOAD SLIDE

Combined effect of roughness and drop on separation zone dimensions.

This method increases the discharge ratio (ratio of turnout to main channel discharge). The results are compatible with the literature. Some other researchers reported that increasing the discharge ratio can scale down the separation zone dimensions (Karami Moghaddam & Keshavarzi 2007Ramamurthy et al. 2007). However, these researchers employed other methods to enhance the discharge ratio. Drop implementation is simple and applicable in practice, since there is normally an elevation difference between the main and lateral canal in irrigation networks to ensure gravity flow occurance.

Table 4 depicts the decrease in percentage of the separation zone compared to base line conditions in different arrangements of the combined tests.Figure 8VIEW LARGEDOWNLOAD SLIDE

Velocity profiles for various roughness coefficients along turnout width.

A comparison between the proposed methods introduced in this paper and traditional methods such as installation of submerged vanes, and changing the inlet geometry (angle, radius) was performed. Figure 8 shows the comparison of the results. The comparison shows that the new techniques can be highly influential and still practical. In this research, with no change in structural geometry (enhancement of roughness coefficient) or minor changes with respect to drop implementation, the dimensions of the separation zone are decreased noticeably. The velocity values were also recorded by a one-dimensional velocity meter at 15 cm distance from the turnout entrance and in a transverse direction (perpendicular to the flow direction). The results are shown in Figure 9.Figure 9VIEW LARGEDOWNLOAD SLIDE

Effect of roughness on separation zone dimensions in numerical study.

Numerical results

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This study examined the flow patterns around the entrance of a diversion channel due to various wall roughnesses in the diversion channel. Results indicated that increasing the discharge ratio in the main channel and diversion channel reduces the area of the separation zone in the diversion channel.Figure 10VIEW LARGEDOWNLOAD SLIDE

Comparision of the vortex area (software output) for three roughnesses (0.009, 0.023 and 0.032).A laboratory and numerical error rate of 0.2605 was calculated from the following formula,

formula

where Uexp is the experimental result, Unum is the numerical result, and N is the number of data.

Figure 9 shows the effect of roughness on separation zone dimensions in numerical study. Figure 10 compares the vortex area (software output) for three roughnesses, 0.009, 0.023 and 0.032 and Figure 11 shows the flow lines (tecplot output) that indicate the effect of roughness on flow in the separation zone. Numerical analysis shows that by increasing the roughness coefficient, the dimensions of the separation zone area decrease, as shown in Figure 10 where the separation zone area at n=0.032 is less than the separation zone area at n=0.009.Figure 11VIEW LARGEDOWNLOAD SLIDE

Comparison of vortex area in 3D mode (tecplot output) with two roughnesses (a) 0.009 and (b) 0.032.Figure 12VIEW LARGEDOWNLOAD SLIDE

Velocity vector for flow condition Q1/422 l/s, near surface.

The velocities intensified moving midway toward the turnout showing that the effective area is scaled down. The velocity values were almost equal to zero near the side walls as expected. As shown in Figure 12 the approach vortex area velocity decreases. Experimental and numerical measured velocity at x=0.15 m of the diversion channel compared in Figure 13 shows that away from the separation zone area, the velocity increases. All longitudinal velocity contours near the vortex area are distinctly different between different roughnesses. The separation zone is larger at less roughness both in length and width.Figure 13VIEW LARGEDOWNLOAD SLIDE

Exprimental and numerical measured velocity.

CONCLUSION

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This study introduces practical and feasible methods for enhancing turnout efficiency by reducing the separation zone dimensions. Increasing the roughness coefficient and implementation of inlet drop were considered as remedies for reduction of separation zone dimensions. A data set has been compiled that fully describes the complex, 3D flow conditions present in a 90 degree turnout channel for selected flow conditions. The aim of this numerical model was to compare the results of a laboratory model in the area of the separation zone and velocity. Results showed that enhancing roughness coefficient reduce the separation zone dimensions up to 38% while the drop implementation effect can scale down this area differently based on roughness coefficient used. Combining both methods can reduce the separation zone dimensions up to 63%. Further research is proposed to investigate the effect of roughness and drop implementation on sedimentation pattern at lateral turnouts. The dimensions of the separation zone decreases with the increase of the non-dimensional parameter, due to the reduction ratio of turnout discharge increasing in all the experiments.

This method increases the discharge ratio (ratio of turnout to main channel discharge). The results are compatible with the literature. Other researchers have reported that intensifying the discharge ratio can scale down the separation zone dimensions (Karami Moghaddam & Keshavarzi 2007Ramamurthy et al. 2007). However, they employed other methods to enhance the discharge ratio. Employing both techniques simultaneously can decrease the separation zone dimensions up to 63%. A comparison between the new methods introduced in this paper and traditional methods such as installation of submerged vanes, and changing the inlet geometry (angle, radius) was performed. The comparison shows that the new techniques can be highly influential and still practical. The numerical and laboratory models are in good agreement and show that the method used in this study has been effective in reducing the separation area. This method is simple, economical and can prevent sediment deposition in the intake canal. Results show that CFD prediction of the fluid through the separation zone at the canal intake can be predicted reasonably well and the RNG model offers the best results in terms of predictability.

DATA AVAILABILITY STATEMENT

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

REFERENCES

Abbasi A., Ghodsian M., Habibi M. & Salehi Neishabouri S. A. 2004 Experimental investigation on dimensions of flow separation zone at lateral intakeentrance. Research & Construction; Pajouhesh va Sazandegi 62, 38–44. (In Persian).Google Scholar Al-Zubaidy R. & Hilo A. 2021 Numerical investigation of flow behavior at the lateral intake using Computational Fluid Dynamics (CFD). Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2021.11.172.Google Scholar Chow V. T. 1959 Open Channel Hydraulics. McGraw-Hill, New York.Jalili H., Hosseinzadeh Dalir A. & Farsadizadeh D. 2011 Effect of intake geometry on the sediment transport and lateral flow pattern. Iranian Water Research Journal 5 (9), 1–10. (In Persian).Google Scholar Jamshidi A., Farsadizadeh D. & Hosseinzadeh Dalir A. 2016 Variations of flow separation zone at lateral intake entrance using submerged vanes. Journal of Civil Engineering Urban 6 (3), 54–63. Journal homepage. Available from: www.ojceu.ir/main.Google Scholar Karami Moghaddam K. & Keshavarzi A. 2007 Investigation of flow structure in lateral intakes of 55° and 90° with rounded entrance edge. In: 03 National Congress on Civil Engineering University of Tabriz. Available from: https://civilica.com/doc/16317. (In Persian).Google Scholar Karami H., Farzin S., Sadrabadi M. T. & Moazeni H. 2017 Simulation of flow pattern at rectangular lateral intake with different dike and submerged vane scenarios. Journal of Water Science and Engineering 10 (3), 246–255. https://doi.org/10.1016/j.wse.2017.10.001.Google ScholarCrossref  Kasthuri B. & Pundarikanthan N. V. 1987 Discussion on separation zone at open- channel junction. Journal of Hydraulic Engineering 113 (4), 543–548.Google ScholarCrossref  Keshavarzi A. & Habibi L. 2005 Optimizing water intake angle by flow separation analysis. Journal of Irrigation and Drain 54, 543–552. https://doi.org/10.1002/ird.207.Google ScholarCrossref  Kirkgöz M. S. & Ardiçlioğlu M. 1997 Velocity profiles of developing and developed open channel flow. Journal of Hydraulic Engineering 1099–1105. 10.1061/(ASCE)0733-9429(1997)123:12(1099).Google Scholar Nakato T., Kennedy J. F. & Bauerly D. 1990 Pumpstation intake-shoaling control with submerge vanes. Journal of Hydraulic Engineering. https://doi.org/10.1061/(ASCE)0733-9429(1990)116:1(119).Google Scholar Neary V. S. & Odgaard J. A. 1993 Three-dimensional flow structure at open channel diversions. Journal of Hydraulic Engineering. ASCE 119 (11), 1224–1230. https://doi.org/10.1061/(ASCE)0733-9429(1993)119:11(1223).Google ScholarCrossref  Nikbin S. & Borghei S. M. 2011 Experimental investigation of submerged vanes effect on dimensions of flow separation zone at a 90° openchannel junction. In: 06rd National Congress on Civil Engineering University of Semnan. (In Persian). Available from: https://civilica.com/doc/120494.Google Scholar Odgaard J. A. & Wang Y. 1991 Sediment management with submerged vanes, I: theory. Journal of Hydraulic Engineering 117 (3), 267–283.Google ScholarCrossref  Ramamurthy A. S., Junying Q. & Diep V. 2007 Numerical and experimental study of dividing open-channel flows. Journal of Hydraulic Engineering. See: https://doi.org/10.1061/(ASCE)0733-9429(2007)133:10(1135).Google Scholar Seyedian S., Karami Moghaddam K. & Shafai Begestan M. 2008 Determining the optimal radius in lateral intakes of 55° and 90° using variation of flow velocity. In: 07th Iranian Hydraulic Conference. Power & Water University of Technology (PWUT). (In Persian). Available from: https://civilica.com/doc/56251.Google Scholar Zolghadr M. & Shafai Bejestan M. 2020 Six legged concrete (SLC) elements as scour countermeasures at wing wall bridge abutments. International Journal of River Basin Management. doi: 10.1080/15715124.2020.1726357.Google Scholar Zolghadr M., Zomorodian S. M. A., Shabani R. & Azamatulla H.Md. 2021 Migration of sand mining pit in rivers: an experimental, numerical and case study. Measurement. https://doi.org/10.1016/j.measurement.2020.108944.Google Scholar © 2022 The AuthorsThis is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Fluid Thermodynamic Simulation of Ti-6Al-4V Alloy in Laser Wire Deposition

Fluid Thermodynamic Simulation of Ti-6Al-4V Alloy in Laser Wire Deposition

Xiang WangLin-Jie ZhangJie Ning, and Suck-Joo Na
Published Online:8 Apr 2022https://doi.org/10.1089/3dp.2021.0159

Abstract

A 3D numerical model of heat transfer and fluid flow of molten pool in the process of laser wire deposition was presented by computational fluid dynamics technique. The simulation results of the deposition morphology were also compared with the experimental results under the condition of liquid bridge transfer mode. Moreover, they showed a good agreement. Considering the effect of recoil pressure, the morphology of the deposit metal obtained by the simulation was similar to the experiment result. Molten metal at the wire tip was peeled off and flowed into the molten pool, and then spread to both sides of the deposition layer under the recoil pressure. In addition, the results of simulation and high-speed charge-coupled device presented that a wedge transition zone, with a length of ∼6 mm, was formed behind the keyhole in the liquid bridge transfer process, where the height of deposited metal decreased gradually. After solidification, metal in the transition zone retained the original melt morphology, resulting in a decrease in the height of the tail of the deposition layer.

Keywords

LWD, CFD, liquid bridge transfer, fluid dynamics, wedge transition zone

Fluid Thermodynamic Simulation of Ti-6Al-4V Alloy in Laser Wire Deposition
Fluid Thermodynamic Simulation of Ti-6Al-4V Alloy in Laser Wire Deposition
Fluid Thermodynamic Simulation of Ti-6Al-4V Alloy in Laser Wire Deposition
Fluid Thermodynamic Simulation of Ti-6Al-4V Alloy in Laser Wire Deposition

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Figure 6. Circular section of the viscosity and shear-rate clouds.

Simulation and Visual Tester Verification of Solid Propellant Slurry Vacuum Plate Casting

Wu Yue,Li Zhuo,Lu RongFirst published: 26 February 2020 https://doi.org/10.1002/prep.201900411Citations: 3

Abstract

Using an improved Carreau constitutive model, a numerical simulation of the casting process of a type of solid propellant slurry vacuum plate casting was carried out using the Flow3D software. Through the flow process in the orifice flow channel and the combustion chamber, the flow velocity of the slurry passing through the plate flow channel was quantitatively analyzed, and the viscosity, shear rate, and leveling characteristics of the slurry in the combustion chamber were qualitatively analyzed and predicted. The pouring time, pouring quality, and flow state predicted by the numerical simulation were verified using a visual tester consisting of a vacuum plate casting system in which a pouring experiment was carried out. Studies have shown that HTPB three-component propellant slurry is a typical yielding pseudoplastic fluid. When the slurry flows through the flower plate and the airfoil, the fluid shear rate reaches its maximum value and the viscosity of the slurry decreases. The visual pouring platform was built and the experiment was controlled according to the numerically-calculated parameters, ensuring the same casting speed. The comparison between the predicted casting quality and the one obtained in the verification test resulted in an error less than 10 %. Moreover, the error between the simulated casting completion time and the process verification test result was also no more than 10 %. Last, the flow state of the slurry during the simulation was consistent with the one during the experimental test. The overall leveling of the slurry in the combustion chamber was adequate and no relatively large holes and flaws developed during the pouring process.

개선된 Carreau 구성 모델을 사용하여 FLOW-3D 소프트웨어를 사용하여 고체 추진제 슬러리 진공판 유형의 Casting Process에 대한 수치 시뮬레이션을 수행했습니다. 오리피스 유로와 연소실에서의 유동과정을 통해 판 유로를 통과하는 슬러리의 유속을 정량적으로 분석하고, 연소실에서 슬러리의 점도, 전단율, 레벨링 특성을 정성적으로 분석하하고, 예측하였습니다.

타설시간, 타설품질, 수치해석으로 예측된 ​​유동상태는 타설실험을 수행한 진공판주조시스템으로 구성된 비주얼 테스터를 이용하여 검증하였습니다.

연구에 따르면 HTPB 3성분 추진제 슬러리는 전형적인 생성 가소성 유체입니다. 슬러리가 플라워 플레이트와 에어포일을 통과할 때 유체 전단율이 최대값에 도달하고 슬러리의 점도가 감소합니다.

시각적 주입 플랫폼이 구축되었고 동일한 주조 속도를 보장하기 위해 수치적으로 계산된 매개변수에 따라 실험이 제어되었습니다. 예측된 casting 품질과 검증 테스트에서 얻은 품질을 비교한 결과 10 % 미만의 오류가 발생했습니다.

또한 모의 casting 완료시간과 공정검증시험 결과의 오차도 10 % 이하로 나타났습니다.

마지막으로 시뮬레이션 중 슬러리의 흐름 상태는 실험 테스트 시와 일치하였다. 연소실에서 슬러리의 전체 레벨링은 적절했으며 주입 과정에서 상대적으로 큰 구멍과 결함이 발생하지 않았습니다.

Figure 1. The equipment used in the vacuum flower-plate pouring process.
Figure 1. The equipment used in the vacuum flower-plate pouring process.
Figure 2. Calculation model.
Figure 2. Calculation model.
Figure 3. Grid block division unit.
Figure 3. Grid block division unit.
Figure 4. Circular section of the speed cloud.
Figure 4. Circular section of the speed cloud.
Figure 5. Viscosity and shear rate distribution cloud pattern flowing through the plate holes.
Figure 5. Viscosity and shear rate distribution cloud pattern flowing through the plate holes.
Figure 6. Circular section of the viscosity and shear-rate clouds.
Figure 6. Circular section of the viscosity and shear-rate clouds.
Figure 7. Volume fraction cloud chart at different time.
Figure 7. Volume fraction cloud chart at different time.
Figure 8. Experimental program.
Figure 8. Experimental program.
Figure 9. Emulation experimental device.
Figure 9. Emulation experimental device.
Figure 10. Visualization of the flow state of the pulp inside the tester.
Figure 10. Visualization of the flow state of the pulp inside the tester.

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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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Numerical study of the effect of flow velocity and flood roughness components on hydraulic flow performance in composite sections with converging floodplains

Numerical study of the effect of flow velocity and flood roughness components on hydraulic flow performance in composite sections with converging floodplains

Authors

1 Civil Enigneering Department, Lahijan Branch.Islamic Azad University.Lahijan.Iran

2 Department of Civil Engnieering, University of Qom,Qom,Iran

3 Civil Engineering Department, Lahijan Branch,Islamic Azad Univeristy,Lahijan,Iran

Abstract

홍수와 그 위험을 통제해야 할 필요성은 누구에게도 숨겨져 있지 않습니다. 또한 이 현상으로 인해 다양한 경제, 사회 및 환경 문제가 영향을 받습니다. 홍수 제어 방법의 설계 및 최적 관리의 첫 번째 단계는 홍수 중 하천 거동을 올바르게 식별하는 것입니다.

홍수 경로 지정, 하상 및 하천 면적 결정 등과 같은 대부분의 하천 엔지니어링 프로젝트에서 하천 단면의 수리학적 매개변수의 평균값을 계산하는 것으로 충분합니다. 오늘날 유체 환경 연구에서 수치 및 분석 방법의 사용이 성장하고 발전했습니다.

신뢰할 수 있는 결과 생성으로 인해 물리적 모델에 대한 좋은 대안이 될 수 있었습니다. 오늘날 수치 모델의 급속한 발전과 컴퓨터 계산 속도의 증가로 인해 3D 수치 모델의 사용이 선호되며 또한 강의 속도 분포 및 전단 응력을 측정하는 데 시간이 많이 걸리고 비용이 많이 들기 때문에 결과 3D 수치 모델의 가치가 있을 것입니다.

한편, 본 연구에서는 복합단면에 대해 FLOW-3D 모델을 이용한 종합적인 수치연구가 이루어지지 않았음을 보여주고 있어 적절한 연구기반을 제공하고 있습니다.

따라서 본 연구의 혁신은 발산 및 수렴 범람원을 동반하는 비 각형 복합 단면에서 흐름의 상태 및 수리 성능에 대한 거칠기와 같은 매개 변수의 영향에 대한 수치 연구입니다.

수치해석 결과를 검증하기 위해 Younesi(2013) 연구를 이용하였습니다. 이 실험에서는 먼저 고정층이 있는 복합 프리즘 및 비 프리즘 단면의 수리 흐름을 조사한 다음 조건을 유지하면서 프리즘 및 비 프리즘 모드에서 퇴적물 이동 실험을 수행했습니다.

실험은 15미터 길이의 연구 채널에서 수행되었습니다. 이 운하는 초당 250리터의 시스템에서 재순환을 위해 제공될 수 있는 유속과 0.0088 000의 종경사를 가진 폭 400mm의 두 개의 대칭 범람원이 있는 합성 운하입니다. 범람원의 가장자리는 0.18미터와 같고 주요 운하의 너비는 0.4미터와 같습니다(그림 1).

본수로의 바닥과 벽을 거칠게 하기 위해 평균직경 0.65mm의 퇴적물을 사용하였으며, 각 단계에서 범람원의 벽과 바닥은 평균직경 0.65, 1.3, 1.78의 퇴적물로 거칠게 하였습다. (mm). 삼각형 오버플로는 운하 상류에서 운하로의 유입량을 측정하는 데 사용됩니다.

상대깊이 0.15와 0.25, 직경 14mm의 마이크로몰리나 실험과 상대깊이 0.35의 실험에서는 유속을 측정하기 위해 3차원 속도계(ADV)를 사용하였습니다. 수위는 0.1mm의 정확도로 깊이 게이지로 측정 되었습니다.

본 연구에서는 수면 프로파일의 수치적 모델을 검증하기 위해 실험 0.25-2에서 발산대의 시작, 중간 및 끝에서 세 단면의 평균 깊이 속도 분포 및 경계 전단 응력) -11.3-NP 및 0.25-2-5.7-NP 및 또한 각형 복합 단면의 0.25-2-2 P 테스트가 평가되었습니다.

각형 합성 단면의 P.20-2-2-P 테스트와 관련된 RMSE 및 NRMSE 지수 값 및 표 (2) 실험 11.3에서 RMSE 및 NRMSE 지수 값 -2-0.25-NP 및 -0.25. 2-5.7-NP가 제공됩니다. 실험 0.25-2-5.7-NP-11.3-2-0.25, NP 및 P.2.0-2-2-P의 평균 깊이 속도의 검증과 관련된 결과가 표시됩니다. 0.25-2-5.7-NP 실험에서 초, 중, 기말 NRMSE의 양은 각각 5.7, 11.8, 10.3%로 계산되었으며, 이는 초급이 우수, 중급이 양호, 최종 성적. 배치. 보시다시피, RMSE 값은 각각 0.026, 0.037 및 0.026으로 계산됩니다.

실험 11.3-2-0.25, NP에서 초급, 중급 및 최종 수준의 NRMSE 값은 각각 7, 11.2 및 15.4%로 계산되었으며, 이는 초급에서 우수 범주 및 우수 범주에서 중간 및 최종 수준. 가져 가다. 보시다시피, RMSE 값은 각각 0.032, 0.038, 0.04로 계산됩니다. 0.25-2-P 실험에서 NRMSE 값은 1.7%로 계산되어 우수 범주에 속한다. 보시다시피 RMSE 값도 0.004로 계산됩니다. 중간 깊이의 속도 분포와 관련하여 수치 모델은 실험실 결과에 적합하며 접합 영역에 작은 오류만 입력되었다고 말할 수 있습니다. 이는 2차 전지의 이동 결과로 간주될 수 있습니다. 모서리를 향해.
결론: 본 연구에서는 3차원 유동 해석이 가능한 Flow 3D 소프트웨어를 사용하여 각형 및 비각형 단면이 복합된 수로의 유동 패턴을 조사했습니다. 3개의 다른 상대 거칠기(1, 2 및 2.74)와 3개의 상대 깊이(0.15, 0.25 및 0.35) 및 5.7 및 11.3도의 발산 각도에 대해 속도의 세로 성분 변화, 평균 깊이 속도 분포, 경계 범람원에 의해 전달되는 유속뿐만 아니라 전단 응력 분포를 조사했습니다.

결과는 수로를 따라 범람원의 폭이 증가함에 따라 유속량이 감소함을 보여주었다. 또한 조도가 유동패턴에 미치는 영향에 대한 연구는 일반적으로 벽의 거칠기에 따라 모든 구간에서 유속량이 감소하는 것으로 나타났으며, 또한 본관과 범람원의 교차점에서의 유동패턴은 벽의 거칠기 영향을 더 많이 받는 것으로 나타났습니다. 결과는 또한 상대 깊이가 증가하거나 상대 거칠기가 감소함에 따라 주 수로와 범람원 사이의 속도 구배가 감소함을 보여주었습니다.

Intrpduction: The need to control floods and their dangers is not hidden from anyone. In addition, a wide range of economic, social and environmental issues are affected by this phenomenon. The first step in the design and optimal management of flood control methods is the correct identification of river behavior during floods. In most river engineering projects such as flood routing, determining the bed and river area, etc., calculating the average values of hydraulic parameters of the river section is sufficient. Today, the use of numerical and analytical methods in the study of fluid environment have grown and developed. Due to the production of reliable results, they have been able to be a good alternative to physical models. Today, with the rapid development of numerical models and increasing the speed of computer calculations, the use of 3D numerical models is preferred and also due to the fact that measuring the velocity distribution and shear stress in rivers is very time consuming and expensive, the results of 3D numerical models It will be valuable. On the other hand, the present studies show that comprehensive numerical research using FLOW-3D model has not been performed on composite sections, so a suitable ground for research is provided. Therefore, the innovation of the present study is the numerical study of the effects of parameters such as roughness on the status and hydraulic performance of the flow in non-prismatic composite sections, which are accompanied by divergent and convergent floodplains, which have received less attention numerically.

Methodology: Younesi (2013) research has been used to validate the results of numerical simulation. In these experiments, first the hydraulic flow in composite prismatic and non-prismatic sections with fixed bed was examined and then, while maintaining the conditions, sediment transfer experiments were performed in prismatic and non-prismatic mode. The experiments were performed in a research channel 15 meters long. This canal is a composite canal with two symmetrical floodplains with a width of 400 mm with a flow rate that can be provided for recirculation in the system of 250 liters per second and a longitudinal slope of 0.0088 000. The depth of the main canal to the edge of the floodplain is equal to 0.18 meters and the width of the main canal is equal to 0.4 meters (Figure 1). In order to roughen the bed and walls of the main canal, sediments with an average diameter of 0.65 mm have been used and at each stage, the walls and bed of floodplains have been roughened by sediments with an average diameter of 0.65, 1.3 and 1.78 (mm). A triangular overflow is used to measure the inflow to the canal, upstream of the canal. In order to measure the flow velocity in experiments with relative depth of 0.15 and 0.25, a micromolina with a diameter of 14 mm and in experiments with relative depth of 0.35, a three-dimensional speedometer (ADV) was used. The water level was also taken by depth gauges with an accuracy of 0.1 mm.
Result and Diccussion: In the present study, in order to validate the numerical model of water surface profile, average depth velocity distribution and boundary shear stress in the three sections at the beginning, middle and end of the divergence zone) in experiments 0.25-2-11.3-NP and 0.25-2-5.7-NP and Also, the 0.25-2-2 P test of the prismatic composite section has been evaluated. In Table (1) the values of RMSE and NRMSE indices related to the P.20-2-2-P test of the prismatic composite section, and also in Table (2) the values of the RMSE and NRMSE indices in the experiments 11.3-2-0.25-NP and -0.25. 2-5.7-NP is provided. The results related to the validation of the average depth velocity of the experiments 0.25-2-5.7- NP-11.3-2-0.25, NP and P.2.0-2-2-P are shown. In 0.25-2-5.7-NP experiment, the amount of NRMSE in elementary, middle and final grades was calculated to be 5.7, 11.8 and 10.3%, respectively, which is in the excellent grade in the elementary grade and good in the middle and final grades. Placed. As can be seen, the RMSE values are calculated as 0.026, 0.037 and 0.026, respectively. In the experiment 11.3-2-0.25, NP, the NRMSE values in the primary, middle and final levels were calculated as 7, 11.2 and 15.4%, respectively, which are in the excellent category in the primary level and in the good category in the middle and final levels. Take. As can be seen, the RMSE values are calculated as 0.032, 0.038 and 0.04, respectively. In the 0.25-2-P experiment, the NRMSE value was calculated to be 1.7%, which is in the excellent category. As can be seen, the RMSE value is also calculated to be 0.004. Regarding the medium-depth velocity distribution, it can be said that the numerical model has an acceptable compliance with the laboratory results and only a small error has been entered in the junction area, which can be considered as a result of the movement of secondary cells towards the corners.
Conclusion: in this research The flow pattern in waterways with composite prismatic and non-prismatic sections was investigated using Flow 3D software that is capable of three-dimensional flow analysis. For three different relative roughnesses (1, 2 and 2.74) as well as three relative depths (0.15, 0.25 and 0.35) and divergence angles of 5.7 and 11.3 degrees, changes in the longitudinal component of velocity, The average depth velocity distribution, the boundary shear stress distribution as well as the flow rate transmitted by the floodplains were investigated. The results showed that with increasing the width of floodplains along the canal, the amount of velocity decreases. Also, the study of the effect of roughness on the flow pattern showed that in general, with wall roughness, the amount of velocity has decreased in all sections and also the flow pattern at the junction of the main canal and floodplain is more affected by wall roughness. The results also showed that with increasing relative depth or decreasing relative roughness, the velocity gradient between the main channel and floodplains decreases

Keywords

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

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한국건설기술연구원 (2017) 보와 하상유지공의 안전성 확보를 위한 물받이와 바닥보호공의 성능평가
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Figure 13 | Velocity vector for flow condition Q¼22 l/s, Near surface.

Experimental and numerical study of flow at a 90 degree lateral turn-out with enhanced roughness coefficient and invert elevation changes

조도 계수 및 역 고도 변화가 향상된 90도 측면 회전에서 유동의 실험 및 수치 연구

Maryam Bagheria, Seyed M. Ali Zomorodianb, Masih Zolghadrc, H. MD. Azamathulla d,*
and C. Venkata Siva Rama Prasade
a Hydraulic Structures, Department of Water Engineering, Shiraz University, Shiraz, Iran
b Department of Water Engineering, College of Agriculture, Shiraz University, Shiraz, Iran
c Department of Water Sciences Engineering, College of Agriculture, Jahrom University, Jahrom, Iran
d Civil & Environmental Engineering, The University of the West Indies, St. Augustine Campus, Port of Spain, Trinidad
e Department of Civil Engineering, St. Peters Engineering College, Hyderabad, India
*Corresponding author. E-mail: azmatheditor@gmail.com

ABSTRACT

Flow separation at the upstream side of the lateral turnouts (intakes) is a critical issue causing eddy currents at the turn-out entrance. It reduces the effective width of flow, turn-out capacity and efficiency.

Therefore, it is essential to identify the dimensions of the separation zone and propose remedies to reduce its dimensions. Installation of 7 types of roughening elements at the turn-out entrance and 3 different bed level inverts, with 4 different discharges (total of 84 experiments) were examined in this study as a method to reduce the dimensions of
the separation zone.

Additionally, a 3-D Computational Fluid Dynamic (CFD) model was utilized to evaluate the flow pattern and dimensions of the separation zone. Results showed that enhancing the roughness coefficient can reduce the separation zone dimensions up to 38% while the drop implementation effect can scale down this area differently based on the roughness coefficient used. Combining both methods can reduce the separation zone dimensions up to 63%.

측면 분기기(흡입구)의 상류 측에서 흐름 분리는 분기기 입구에서 와류를 일으키는 중요한 문제입니다. 이는 흐름의 유효 폭, 턴아웃 용량 및 효율성을 감소시킵니다. 따라서 분리지대의 크기를 파악하고 크기를 줄이기 위한 방안을 제시하는 것이 필수적이다.

이 연구에서는 분리 구역의 치수를 줄이기 위한 방법으로 4가지 다른 배출(총 84개 실험)과 함께 7가지 유형의 조면화 요소를 출구 입구에 설치하고 3가지 서로 다른 베드 레벨 반전 장치를 조사했습니다.

또한 3D CFD(Computational Fluid Dynamics) 모델을 사용하여 분리 영역의 흐름 패턴과 치수를 평가했습니다. 결과는 거칠기 계수를 향상시키면 분리 영역 치수를 최대 38%까지 줄일 수 있는 반면 드롭 구현 효과는 사용된 거칠기 계수를 기반으로 이 영역을 다르게 축소할 수 있음을 보여주었습니다.

두 가지 방법을 결합하면 분리 영역 치수를 최대 63%까지 줄일 수 있습니다.

Key words

discharge ratio, flow separation zone, intake, three dimensional simulation

Experimental and numerical study of flow at a 90 degree lateral turn-out with enhanced roughness coefficient and invert elevation changes
Experimental and numerical study of flow at a 90 degree lateral turn-out with enhanced roughness coefficient and invert elevation changes
Figure 2 | Roughness plates.
Figure 2 | Roughness plates.
Figure 3 | Effect of roughness on separation zone dimensions
Figure 3 | Effect of roughness on separation zone dimensions
Figure 4 | Effect of roughness on separation zone dimensions.
Figure 4 | Effect of roughness on separation zone dimensions.
Figure 5 | Comparison of separation zone for n¼0.023 and n¼0.032.
Figure 5 | Comparison of separation zone for n¼0.023 and n¼0.032.
Figure 6 | Effect of drop implementation on separation zone dimensions
Figure 6 | Effect of drop implementation on separation zone dimensions
Figure 7 | Combined effect of roughness and drop on separation zone dimensions
Figure 7 | Combined effect of roughness and drop on separation zone dimensions
Figure 8 | Non- dimensional Length of separation zone (Lr) variations against relative unit discharge per width (qr) in present study compared with other methods.
Figure 8 | Non- dimensional Length of separation zone (Lr) variations against relative unit discharge per width (qr) in present study compared with other methods.
Figure 9 | Velocity profiles for various roughness coefficients along turn-out width.
Figure 9 | Velocity profiles for various roughness coefficients along turn-out width.
Figure 10 | Effect of roughness on sepration zone dimensions in numerical study
Figure 10 | Effect of roughness on sepration zone dimensions in numerical study
Figure 11 | Comparision of the vortex area (software output) with three roughness (0.009, 0.023 and 0.032).
Figure 11 | Comparision of the vortex area (software output) with three roughness (0.009, 0.023 and 0.032).
Figure 12 | Comparison of vortex area in 3D mode (tecplot output) with two roughness (a) 0.009 and (b) 0.032
Figure 12 | Comparison of vortex area in 3D mode (tecplot output) with two roughness (a) 0.009 and (b) 0.032
Figure 13 | Velocity vector for flow condition Q¼22 l/s, Near surface.
Figure 13 | Velocity vector for flow condition Q¼22 l/s, Near surface.
Figure 14 | Exprimental and numerical measured velocity.
Figure 14 | Exprimental and numerical measured velocity.

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Figure 3.10: Snapshots of Temperature Profile for Single Track in Keyhole Regime (P = 250W and V = 0.5m/s) at the Preheating Temperature of 100 °C

Multiscale Process Modeling of Residual Deformation and Defect Formation for Laser Powder Bed Fusion Additive Manufacturing

Qian Chen, PhD
University of Pittsburgh, 2021

레이저 분말 베드 퓨전(L-PBF) 적층 제조(AM)는 우수한 기계적 특성으로 그물 모양에 가까운 복잡한 부품을 생산할 수 있습니다. 그러나 빌드 실패 및 다공성과 같은 결함으로 이어지는 원치 않는 잔류 응력 및 왜곡이 L-PBF의 광범위한 적용을 방해하고 있습니다.

L-PBF의 잠재력을 최대한 실현하기 위해 잔류 변형, 용융 풀 및 다공성 형성을 예측하는 다중 규모 모델링 방법론이 개발되었습니다. L-PBF의 잔류 변형 및 응력을 부품 규모에서 예측하기 위해 고유 변형 ​​방법을 기반으로 하는 다중 규모 프로세스 모델링 프레임워크가 제안됩니다.

고유한 변형 벡터는 마이크로 스케일에서 충실도가 높은 상세한 다층 프로세스 시뮬레이션에서 추출됩니다. 균일하지만 이방성인 변형은 잔류 왜곡 및 응력을 예측하기 위해 준 정적 평형 유한 요소 분석(FEA)에서 레이어별로 L-PBF 부품에 적용됩니다.

부품 규모에서의 잔류 변형 및 응력 예측 외에도 분말 규모의 다중물리 모델링을 수행하여 공정 매개변수, 예열 온도 및 스패터링 입자에 의해 유도된 용융 풀 변동 및 결함 형성을 연구합니다. 이러한 요인과 관련된 용융 풀 역학 및 다공성 형성 메커니즘은 시뮬레이션 및 실험을 통해 밝혀졌습니다.

제안된 부품 규모 잔류 응력 및 왜곡 모델을 기반으로 경로 계획 방법은 큰 잔류 변형 및 건물 파손을 방지하기 위해 주어진 형상에 대한 레이저 스캐닝 경로를 조정하기 위해 개발되었습니다.

연속 및 아일랜드 스캐닝 전략을 위한 기울기 기반 경로 계획이 공식화되고 공식화된 컴플라이언스 및 스트레스 최소화 문제에 대한 전체 감도 분석이 수행됩니다. 이 제안된 경로 계획 방법의 타당성과 효율성은 AconityONE L-PBF 시스템을 사용하여 실험적으로 입증되었습니다.

또한 기계 학습을 활용한 데이터 기반 프레임워크를 개발하여 L-PBF에 대한 부품 규모의 열 이력을 예측합니다. 본 연구에서는 실시간 열 이력 예측을 위해 CNN(Convolutional Neural Network)과 RNN(Recurrent Neural Network)을 포함하는 순차적 기계 학습 모델을 제안합니다.

유한 요소 해석과 비교하여 100배의 예측 속도 향상이 달성되어 실제 제작 프로세스보다 빠른 예측이 가능하고 실시간 온도 프로파일을 사용할 수 있습니다.

Laser powder bed fusion (L-PBF) additive manufacturing (AM) is capable of producing complex parts near net shape with good mechanical properties. However, undesired residual stress and distortion that lead to build failure and defects such as porosity are preventing broader applications of L-PBF. To realize the full potential of L-PBF, a multiscale modeling methodology is developed to predict residual deformation, melt pool, and porosity formation. To predict the residual deformation and stress in L-PBF at part-scale, a multiscale process modeling framework based on inherent strain method is proposed.

Inherent strain vectors are extracted from detailed multi-layer process simulation with high fidelity at micro-scale. Uniform but anisotropic strains are then applied to L-PBF part in a layer-by-layer fashion in a quasi-static equilibrium finite element analysis (FEA) to predict residual distortion and stress. Besides residual distortion and stress prediction at part scale, multiphysics modeling at powder scale is performed to study the melt pool variation and defect formation induced by process parameters, preheating temperature and spattering particles. Melt pool dynamics and porosity formation mechanisms associated with these factors are revealed through simulation and experiments.

Based on the proposed part-scale residual stress and distortion model, path planning method is developed to tailor the laser scanning path for a given geometry to prevent large residual deformation and building failures. Gradient based path planning for continuous and island scanning strategy is formulated and full sensitivity analysis for the formulated compliance- and stress-minimization problem is performed.

The feasibility and effectiveness of this proposed path planning method is demonstrated experimentally using the AconityONE L-PBF system. In addition, a data-driven framework utilizing machine learning is developed to predict the thermal history at part-scale for L-PBF.

In this work, a sequential machine learning model including convolutional neural network (CNN) and recurrent neural network (RNN), long shortterm memory unit, is proposed for real-time thermal history prediction. A 100x prediction speed improvement is achieved compared to the finite element analysis which makes the prediction faster than real fabrication process and real-time temperature profile available.

Figure 1.1: Schematic Overview of Metal Laser Powder Bed Fusion Process [2]
Figure 1.1: Schematic Overview of Metal Laser Powder Bed Fusion Process [2]
Figure 1.2: Commercial Powder Bed Fusion Systems
Figure 1.2: Commercial Powder Bed Fusion Systems
Figure 1.3: Commercial Metal Components Fabricated by Powder Bed Fusion Additive Manufacturing: (a) GE Fuel Nozzle; (b) Stryker Hip Biomedical Implant.
Figure 1.3: Commercial Metal Components Fabricated by Powder Bed Fusion Additive Manufacturing: (a) GE Fuel Nozzle; (b) Stryker Hip Biomedical Implant.
Figure 2.1: Proposed Multiscale Process Simulation Framework
Figure 2.1: Proposed Multiscale Process Simulation Framework
Figure 2.2: (a) Experimental Setup for In-situ Thermocouple Measurement in the EOS M290 Build Chamber; (b) Themocouple Locations on the Bottom Side of the Substrate.
Figure 2.2: (a) Experimental Setup for In-situ Thermocouple Measurement in the EOS M290 Build Chamber; (b) Themocouple Locations on the Bottom Side of the Substrate.
Figure 2.3: (a) Finite Element Model for Single Layer Thermal Analysis; (b) Deposition Layer
Figure 2.3: (a) Finite Element Model for Single Layer Thermal Analysis; (b) Deposition Layer
Figure 2.4: Core-skin layer: (a) Surface Morphology; (b) Scanning Strategy; (c) Transient Temperature Distribution and Temperature History at (d) Point 1; (e) Point 2 and (f) Point 3
Figure 2.4: Core-skin layer: (a) Surface Morphology; (b) Scanning Strategy; (c) Transient Temperature Distribution and Temperature History at (d) Point 1; (e) Point 2 and (f) Point 3
Figure 2.5: (a) Scanning Orientation of Each Layer; (b) Finite Element Model for Micro-scale Representative Volume
Figure 2.5: (a) Scanning Orientation of Each Layer; (b) Finite Element Model for Micro-scale Representative Volume
Figure 2.6: Bottom Layer (a) Thermal History; (b) Plastic Strain and (c) Elastic Strain Evolution History
Figure 2.6: Bottom Layer (a) Thermal History; (b) Plastic Strain and (c) Elastic Strain Evolution History
Figure 2.7: Bottom Layer Inherent Strain under Default Process Parameters along Horizontal Scanning Path
Figure 2.7: Bottom Layer Inherent Strain under Default Process Parameters along Horizontal Scanning Path
Figure 2.8: Snapshots of the Element Activation Process
Figure 2.8: Snapshots of the Element Activation Process
Figure 2.9: Double Cantilever Beam Structure Built by the EOS M290 DMLM Process (a) Before and (b) After Cutting off; (c) Faro Laser ScanArm V3 for Distortion Measurement
Figure 2.9: Double Cantilever Beam Structure Built by the EOS M290 DMLM Process (a) Before and (b) After Cutting off; (c) Faro Laser ScanArm V3 for Distortion Measurement
Figure 2.10: Square Canonical Structure Built by the EOS M290 DMLM Process
Figure 2.10: Square Canonical Structure Built by the EOS M290 DMLM Process
Figure 2.11: Finite Element Mesh for the Square Canonical and Snapshots of Element Activation Process
Figure 2.11: Finite Element Mesh for the Square Canonical and Snapshots of Element Activation Process
Figure 2.12: Simulated Distortion Field for the Double Cantilever Beam before Cutting off the Supports: (a) Inherent Strain Method; (b) Simufact Additive 3.1
Figure 2.12: Simulated Distortion Field for the Double Cantilever Beam before Cutting off the Supports: (a) Inherent Strain Method; (b) Simufact Additive 3.1
Figure 3.10: Snapshots of Temperature Profile for Single Track in Keyhole Regime (P = 250W and V = 0.5m/s) at the Preheating Temperature of 100 °C
Figure 3.10: Snapshots of Temperature Profile for Single Track in Keyhole Regime (P = 250W and V = 0.5m/s) at the Preheating Temperature of 100 °C
s) at the Preheating Temperature of 500 °C
s) at the Preheating Temperature of 500 °C
Figure 3.15: Melt Pool Cross Section Comparison Between Simulation and Experiment for Single Track
Figure 3.15: Melt Pool Cross Section Comparison Between Simulation and Experiment for Single Track

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Figure 2 Idea and details of T-shaped weir.

Introducing the T-shaped weir: a new nonlinear weir

Behzad NorooziJalal BazarganAkbar Safarzadeh

Abstract

본 연구에서는 LW(Labyrinth Weir)와 PKW(Piano Key Weir)가 결합된 T자형 웨어(TSW)라는 새로운 비선형 웨어를 도입하여 수압 성능을 비교하였다.

PKW. 입구 키, 출구 키 또는 두 키 모두에서 수직 벽의 존재에 따라 TSW 위어는 각각 A, B 또는 C 유형 웨어로 분류되었습니다. 다른 TSW 사례의 흐름 패턴을 분석하고 배출 계수 곡선을 제공했습니다. 또한 테스트된 둑의 유체역학을 정확하게 연구하기 위해 FLOW-3D 소프트웨어를 사용하여 3D 수치 시뮬레이션을 수행했습니다.

결과는 출구 키(C-TSW 유형)의 상류에 수직 벽을 삽입하는 것이 PKW의 유압 성능에 미미한 영향을 미치는 것으로 나타났습니다. B-TSW의 토출계수는 PKW 대비 최대 16% 증가하였으며, Ht/p 0.45까지 수직벽의 성능향상 효과 증가 B-TSW는 유지되었습니다.

실험적 및 수치적 실험을 통해 가장 높은 방전 용량을 갖는 B-TSW에서 수직벽의 최적 높이비(Pd/P)는 0.4로 결정되었다.

In the present study, a new nonlinear weir called the T-shaped weir (TSW), which is a combination of the labyrinth weir (LW) and the piano key weir (PKW), was introduced, and its hydraulic performance was compared with the PKW. Based on the presence of the vertical walls at the inlet key, outlet key, or both keys, the TSW weirs were classified as type A, B, or C weirs, respectively. The flow pattern of different TSW cases was analyzed, and the discharge coefficient curves were provided. Furthermore, to accurately study the hydrodynamics of the tested weirs, 3D numerical simulations were performed using the FLOW-3D software. The results showed that inserting a vertical wall at the upstream of the outlet keys (C-TSW type) has a negligible effect on the hydraulic performance of the PKW. A maximum increase of 16% occurred in the discharge coefficient of the B-TSW in comparison to the PKW, and up to a head to height ratio (Ht/p) of 0.45, the effect of the vertical wall on increasing the performance of the B-TSW was maintained. Based on the experimental and numerical tests, the optimal height ratio of the vertical wall (Pd/P) in B-TSW with highest discharge capacity was determined to be equal to 0.4.

HIGHLIGHTS

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  • A new nonlinear weir called the T-shaped weir (TSW), which is a combination of the labyrinth weir (LW) and the piano key weir (PKW), is introduced.
  • To investigate the hydrodynamics of the tested weirs in more detail, 3D numerical models are developed on the CFD-software FLOW-3D.
  • By testing different vertical wall sizes, the optimal size of the vertical wall is determined for B-TSW weir.

Keywords

discharge coefficientlabyrinth weirlocal submergencepiano key weirT-shaped weir

Figure 2 Idea and details of T-shaped weir.
Figure 2 Idea and details of T-shaped weir.

Figure 19. Water surface profile at the middle part of the inlet key for H/P = 0.4.
Figure 19. Water surface profile at the middle part of the inlet key for H/P = 0.4.
Figure 21 Transverse water surface profile in the outlet key of tested weirs  for H/P = 0.4.
Figure 21 Transverse water surface profile in the outlet key of tested weirs for H/P = 0.4.

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Investigation ofcavitation in stepped spillway of Siah-Bishe dam by using Flow-3D model

Investigation ofcavitation in stepped spillway of Siah-Bishe dam by using Flow-3D model

Author(s) : Daneshfaraz, R. ;  Zogi, N.

Author Affiliation : Civil Eng. & Hydraulics Dept., Faculty of Engineering, University of Maragheh, Maragheh, Iran.

Author Email : daneshfaraz@yahoo.com

Journal article : International Research Journal of Applied and Basic Sciences 2013 Vol.4 No.11 pp.3382-3388 ref.14

Abstract

캐비테이션은 고속 및 과난류 흐름에서 수리 구조물에 손상을 입히고 구멍을 만드는 현상입니다. 본 연구에서는 Siah-Bishe 배수로의 계단식 급수 공식을 Flow-3D 소프트웨어를 통해 시뮬레이션하고 물리적 모델과 비교합니다.

이 소프트웨어는 자유 표면과 복잡한 형상의 불안정한 3D 흐름 문제를 분석하는 정확한 도구입니다. 유한체적법을 통해 질량, 운동량, 에너지 보존 공식을 풀어 문제를 해결합니다.

본 연구에서는 여수로의 시작, 끝, 끝 부분의 압력 매개변수를 연구하고 일부 부분에서 음압이 관찰됩니다. 이 압력은 캐비테이션을 일으킬 수 있습니다. 본 연구는 Flow-3D로 모델링된 물리적 모델과 유한체적법 간의 대응 결과를 보여준다.

Cavitation is a phenomenon which damages and makes hole in hydraulic structure in high velocity and over-turbulent flows. In this research, stepped fast water formula of Siah-Bishe spillway is stimulated via Flow-3D software and compared with physical model. This software is an accurate tool in analyzing unsteady 3D flow problems with free surface and complex geometry. It solves problems by solving conservation of mass formulas, momentum and energy viafinite volume method. In this study, pressure parameter at the beginning, end and along the spillway is studied and negative pressure is observed in some parts. This pressure can make cavitation. The study shows the results of correspondence between physical model and finite volume method modeled by Flow-3D.

ISSN : 2251-838X

URL : http://irjabs.com/files_site/paperlis…

Record Number : 20133348057

Publisher : Science Explorer Publications

Location of publication : London

Country of publication : UK

Language of text : English

Indexing terms for this abstract:

Keywords

cavitation, computer simulation, dams, pressure, simulation models, spillways, water flow

Figure 3 Simulation PTC pipes enhanced with copper foam and nanoparticles in FLOW-3D software.

다공성 미디어 및 나노유체에 의해 강화된 수집기로 태양광 CCHP 시스템의 최적화

Optimization of Solar CCHP Systems with Collector Enhanced by Porous Media and Nanofluid


Navid Tonekaboni,1Mahdi Feizbahr,2 Nima Tonekaboni,1Guang-Jun Jiang,3,4 and Hong-Xia Chen3,4

Abstract

태양열 집열기의 낮은 효율은 CCHP(Solar Combined Cooling, Heating, and Power) 사이클의 문제점 중 하나로 언급될 수 있습니다. 태양계를 개선하기 위해 나노유체와 다공성 매체가 태양열 집열기에 사용됩니다.

다공성 매질과 나노입자를 사용하는 장점 중 하나는 동일한 조건에서 더 많은 에너지를 흡수할 수 있다는 것입니다. 이 연구에서는 평균 일사량이 1b인 따뜻하고 건조한 지역의 600 m2 건물의 전기, 냉방 및 난방을 생성하기 위해 다공성 매질과 나노유체를 사용하여 태양열 냉난방 복합 발전(SCCHP) 시스템을 최적화했습니다.

본 논문에서는 침전물이 형성되지 않는 lb = 820 w/m2(이란) 정도까지 다공성 물질에서 나노유체의 최적량을 계산하였다. 이 연구에서 태양열 집열기는 구리 다공성 매체(95% 다공성)와 CuO 및 Al2O3 나노 유체로 향상되었습니다.

나노유체의 0.1%-0.6%가 작동 유체로 물에 추가되었습니다. 나노유체의 0.5%가 태양열 집열기 및 SCCHP 시스템에서 가장 높은 에너지 및 엑서지 효율 향상으로 이어지는 것으로 밝혀졌습니다.

본 연구에서 포물선형 집열기(PTC)의 최대 에너지 및 엑서지 효율은 각각 74.19% 및 32.6%입니다. 그림 1은 태양 CCHP의 주기를 정확하게 설명하기 위한 그래픽 초록으로 언급될 수 있습니다.

The low efficiency of solar collectors can be mentioned as one of the problems in solar combined cooling, heating, and power (CCHP) cycles. For improving solar systems, nanofluid and porous media are used in solar collectors. One of the advantages of using porous media and nanoparticles is to absorb more energy under the same conditions. In this research, a solar combined cooling, heating, and power (SCCHP) system has been optimized by porous media and nanofluid for generating electricity, cooling, and heating of a 600 m2 building in a warm and dry region with average solar radiation of Ib = 820 w/m2 in Iran. In this paper, the optimal amount of nanofluid in porous materials has been calculated to the extent that no sediment is formed. In this study, solar collectors were enhanced with copper porous media (95% porosity) and CuO and Al2O3 nanofluids. 0.1%–0.6% of the nanofluids were added to water as working fluids; it is found that 0.5% of the nanofluids lead to the highest energy and exergy efficiency enhancement in solar collectors and SCCHP systems. Maximum energy and exergy efficiency of parabolic thermal collector (PTC) riches in this study are 74.19% and 32.6%, respectively. Figure 1 can be mentioned as a graphical abstract for accurately describing the cycle of solar CCHP.

1. Introduction

Due to the increase in energy consumption, the use of clean energy is one of the important goals of human societies. In the last four decades, the use of cogeneration cycles has increased significantly due to high efficiency. Among clean energy, the use of solar energy has become more popular due to its greater availability [1]. Low efficiency of energy production, transmission, and distribution system makes a new system to generate simultaneously electricity, heating, and cooling as an essential solution to be widely used. The low efficiency of the electricity generation, transmission, and distribution system makes the CCHP system a basic solution to eliminate waste of energy. CCHP system consists of a prime mover (PM), a power generator, a heat recovery system (produce extra heating/cooling/power), and thermal energy storage (TES) [2]. Solar combined cooling, heating, and power (SCCHP) has been started three decades ago. SCCHP is a system that receives its propulsive force from solar energy; in this cycle, solar collectors play the role of propulsive for generating power in this system [3].

Increasing the rate of energy consumption in the whole world because of the low efficiency of energy production, transmission, and distribution system causes a new cogeneration system to generate electricity, heating, and cooling energy as an essential solution to be widely used. Building energy utilization fundamentally includes power required for lighting, home electrical appliances, warming and cooling of building inside, and boiling water. Domestic usage contributes to an average of 35% of the world’s total energy consumption [4].

Due to the availability of solar energy in all areas, solar collectors can be used to obtain the propulsive power required for the CCHP cycle. Solar energy is the main source of energy in renewable applications. For selecting a suitable area to use solar collectors, annual sunshine hours, the number of sunny days, minus temperature and frosty days, and the windy status of the region are essentially considered [5]. Iran, with an average of more than 300 sunny days, is one of the suitable countries to use solar energy. Due to the fact that most of the solar radiation is in the southern regions of Iran, also the concentration of cities is low in these areas, and transmission lines are far apart, one of the best options is to use CCHP cycles based on solar collectors [6]. One of the major problems of solar collectors is their low efficiency [7]. Low efficiency increases the area of collectors, which increases the initial cost of solar systems and of course increases the initial payback period. To increase the efficiency of solar collectors and improve their performance, porous materials and nanofluids are used to increase their workability.

There are two ways to increase the efficiency of solar collectors and mechanical and fluid improvement. In the first method, using porous materials or helical filaments inside the collector pipes causes turbulence of the flow and increases heat transfer. In the second method, using nanofluids or salt and other materials increases the heat transfer of water. The use of porous materials has grown up immensely over the past twenty years. Porous materials, especially copper porous foam, are widely used in solar collectors. Due to the high contact surface area, porous media are appropriate candidates for solar collectors [8]. A number of researchers investigated Solar System performance in accordance with energy and exergy analyses. Zhai et al. [9] reviewed the performance of a small solar-powered system in which the energy efficiency was 44.7% and the electrical efficiency was 16.9%.

Abbasi et al. [10] proposed an innovative multiobjective optimization to optimize the design of a cogeneration system. Results showed the CCHP system based on an internal diesel combustion engine was the applicable alternative at all regions with different climates. The diesel engine can supply the electrical requirement of 31.0% and heating demand of 3.8% for building.

Jiang et al. [11] combined the experiment and simulation together to analyze the performance of a cogeneration system. Moreover, some research focused on CCHP systems using solar energy. It integrated sustainable and renewable technologies in the CCHP, like PV, Stirling engine, and parabolic trough collector (PTC) [21215].

Wang et al. [16] optimized a cogeneration solar cooling system with a Rankine cycle and ejector to reach the maximum total system efficiency of 55.9%. Jing et al. analyzed a big-scale building with the SCCHP system and auxiliary heaters to produced electrical, cooling, and heating power. The maximum energy efficiency reported in their work is 46.6% [17]. Various optimization methods have been used to improve the cogeneration system, minimum system size, and performance, such as genetic algorithm [1819].

Hirasawa et al. [20] investigated the effect of using porous media to reduce thermal waste in solar systems. They used the high-porosity metal foam on top of the flat plate solar collector and observed that thermal waste decreased by 7% due to natural heat transfer. Many researchers study the efficiency improvement of the solar collector by changing the collector’s shapes or working fluids. However, the most effective method is the use of nanofluids in the solar collector as working fluid [21]. In the experimental study done by Jouybari et al. [22], the efficiency enhancement up to 8.1% was achieved by adding nanofluid in a flat plate collector. In this research, by adding porous materials to the solar collector, collector efficiency increased up to 92% in a low flow regime. Subramani et al. [23] analyzed the thermal performance of the parabolic solar collector with Al2O3 nanofluid. They conducted their experiments with Reynolds number range 2401 to 7202 and mass flow rate 0.0083 to 0.05 kg/s. The maximum efficiency improvement in this experiment was 56% at 0.05 kg/s mass flow rate.

Shojaeizadeh et al. [24] investigated the analysis of the second law of thermodynamic on the flat plate solar collector using Al2O3/water nanofluid. Their research showed that energy efficiency rose up to 1.9% and the exergy efficiency increased by a maximum of 0.72% compared to pure water. Tiwari et al. [25] researched on the thermal performance of solar flat plate collectors for working fluid water with different nanofluids. The result showed that using 1.5% (optimum) particle volume fraction of Al2O3 nanofluid as an absorbing medium causes the thermal efficiency to enhance up to 31.64%.

The effect of porous media and nanofluids on solar collectors has already been investigated in the literature but the SCCHP system with a collector embedded by both porous media and nanofluid for enhancing the ratio of nanoparticle in nanofluid for preventing sedimentation was not discussed. In this research, the amount of energy and exergy of the solar CCHP cycles with parabolic solar collectors in both base and improved modes with a porous material (copper foam with 95% porosity) and nanofluid with different ratios of nanoparticles was calculated. In the first step, it is planned to design a CCHP system based on the required load, and, in the next step, it will analyze the energy and exergy of the system in a basic and optimize mode. In the optimize mode, enhanced solar collectors with porous material and nanofluid in different ratios (0.1%–0.7%) were used to optimize the ratio of nanofluids to prevent sedimentation.

2. Cycle Description

CCHP is one of the methods to enhance energy efficiency and reduce energy loss and costs. The SCCHP system used a solar collector as a prime mover of the cogeneration system and assisted the boiler to generate vapor for the turbine. Hot water flows from the expander to the absorption chiller in summer or to the radiator or fan coil in winter. Finally, before the hot water wants to flow back to the storage tank, it flows inside a heat exchanger for generating domestic hot water [26].

For designing of solar cogeneration system and its analysis, it is necessary to calculate the electrical, heating (heating load is the load required for the production of warm water and space heating), and cooling load required for the case study considered in a residential building with an area of 600 m2 in the warm region of Iran (Zahedan). In Table 1, the average of the required loads is shown for the different months of a year (average of electrical, heating, and cooling load calculated with CARRIER software).Table 1 The average amount of electric charges, heating load, and cooling load used in the different months of the year in the city of Zahedan for a residential building with 600 m2.

According to Table 1, the maximum magnitude of heating, cooling, and electrical loads is used to calculate the cogeneration system. The maximum electric load is 96 kW, the maximum amount of heating load is 62 kW, and the maximum cooling load is 118 kW. Since the calculated loads are average, all loads increased up to 10% for the confidence coefficient. With the obtained values, the solar collector area and other cogeneration system components are calculated. The cogeneration cycle is capable of producing 105 kW electric power, 140 kW cooling capacity, and 100 kW heating power.

2.1. System Analysis Equations

An analysis is done by considering the following assumptions:(1)The system operates under steady-state conditions(2)The system is designed for the warm region of Iran (Zahedan) with average solar radiation Ib = 820 w/m2(3)The pressure drops in heat exchangers, separators, storage tanks, and pipes are ignored(4)The pressure drop is negligible in all processes and no expectable chemical reactions occurred in the processes(5)Potential, kinetic, and chemical exergy are not considered due to their insignificance(6)Pumps have been discontinued due to insignificance throughout the process(7)All components are assumed adiabatic

Schematic shape of the cogeneration cycle is shown in Figure 1 and all data are given in Table 2.

Figure 1 Schematic shape of the cogeneration cycle.Table 2 Temperature and humidity of different points of system.

Based on the first law of thermodynamic, energy analysis is based on the following steps.

First of all, the estimated solar radiation energy on collector has been calculated:where α is the heat transfer enhancement coefficient based on porous materials added to the collector’s pipes. The coefficient α is increased by the porosity percentage, the type of porous material (in this case, copper with a porosity percentage of 95), and the flow of fluid to the collector equation.

Collector efficiency is going to be calculated by the following equation [9]:

Total energy received by the collector is given by [9]

Also, the auxiliary boiler heat load is [2]

Energy consumed from vapor to expander is calculated by [2]

The power output form by the screw expander [9]:

The efficiency of the expander is 80% in this case [11].

In this step, cooling and heating loads were calculated and then, the required heating load to reach sanitary hot water will be calculated as follows:

First step: calculating the cooling load with the following equation [9]:

Second step: calculating heating loads [9]:

Then, calculating the required loud for sanitary hot water will be [9]

According to the above-mentioned equations, efficiency is [9]

In the third step, calculated exergy analysis as follows.

First, the received exergy collector from the sun is calculated [9]:

In the previous equation, f is the constant of air dilution.

The received exergy from the collector is [9]

In the case of using natural gas in an auxiliary heater, the gas exergy is calculated from the following equation [12]:

Delivering exergy from vapor to expander is calculated with the following equation [9]:

In the fourth step, the exergy in cooling and heating is calculated by the following equation:

Cooling exergy in summer is calculated [9]:

Heating exergy in winter is calculated [9]:

In the last step based on thermodynamic second law, exergy efficiency has been calculated from the following equation and the above-mentioned calculated loads [9]:

3. Porous Media

The porous medium that filled the test section is copper foam with a porosity of 95%. The foams are determined in Figure 2 and also detailed thermophysical parameters and dimensions are shown in Table 3.

Figure 2 Copper foam with a porosity of 95%.Table 3 Thermophysical parameters and dimensions of copper foam.

In solar collectors, copper porous materials are suitable for use at low temperatures and have an easier and faster manufacturing process than ceramic porous materials. Due to the high coefficient conductivity of copper, the use of copper metallic foam to increase heat transfer is certainly more efficient in solar collectors.

Porous media and nanofluid in solar collector’s pipes were simulated in FLOW-3D software using the finite-difference method [27]. Nanoparticles Al2O3 and CUO are mostly used in solar collector enhancement. In this research, different concentrations of nanofluid are added to the parabolic solar collectors with porous materials (copper foam with porosity of 95%) to achieve maximum heat transfer in the porous materials before sedimentation. After analyzing PTC pipes with the nanofluid flow in FLOW-3D software, for energy and exergy efficiency analysis, Carrier software results were used as EES software input. Simulation PTC with porous media inside collector pipe and nanofluids sedimentation is shown in Figure 3.

Figure 3 Simulation PTC pipes enhanced with copper foam and nanoparticles in FLOW-3D software.

3.1. Nano Fluid

In this research, copper and silver nanofluids (Al2O3, CuO) have been added with percentages of 0.1%–0.7% as the working fluids. The nanoparticle properties are given in Table 4. Also, system constant parameters are presented in Table 4, which are available as default input in the EES software.Table 4 Properties of the nanoparticles [9].

System constant parameters for input in the software are shown in Table 5.Table 5 System constant parameters.

The thermal properties of the nanofluid can be obtained from equations (18)–(21). The basic fluid properties are indicated by the index (bf) and the properties of the nanoparticle silver with the index (np).

The density of the mixture is shown in the following equation [28]:where ρ is density and ϕ is the nanoparticles volume fraction.

The specific heat capacity is calculated from the following equation [29]:

The thermal conductivity of the nanofluid is calculated from the following equation [29]:

The parameter β is the ratio of the nanolayer thickness to the original particle radius and, usually, this parameter is taken equal to 0.1 for the calculated thermal conductivity of the nanofluids.

The mixture viscosity is calculated as follows [30]:

In all equations, instead of water properties, working fluids with nanofluid are used. All of the above equations and parameters are entered in the EES software for calculating the energy and exergy of solar collectors and the SCCHP cycle. All calculation repeats for both nanofluids with different concentrations of nanofluid in the solar collector’s pipe.

4. Results and Discussion

In the present study, relations were written according to Wang et al. [16] and the system analysis was performed to ensure the correctness of the code. The energy and exergy charts are plotted based on the main values of the paper and are shown in Figures 4 and 5. The error rate in this simulation is 1.07%.

Figure 4 Verification charts of energy analysis results.

Figure 5 Verification charts of exergy analysis results.

We may also investigate the application of machine learning paradigms [3141] and various hybrid, advanced optimization approaches that are enhanced in terms of exploration and intensification [4255], and intelligent model studies [5661] as well, for example, methods such as particle swarm optimizer (PSO) [6062], differential search (DS) [63], ant colony optimizer (ACO) [616465], Harris hawks optimizer (HHO) [66], grey wolf optimizer (GWO) [5367], differential evolution (DE) [6869], and other fusion and boosted systems [4146485054557071].

At the first step, the collector is modified with porous copper foam material. 14 cases have been considered for the analysis of the SCCHP system (Table 6). It should be noted that the adding of porous media causes an additional pressure drop inside the collector [922263072]. All fourteen cases use copper foam with a porosity of 95 percent. To simulate the effect of porous materials and nanofluids, the first solar PTC pipes have been simulated in the FLOW-3D software and then porous media (copper foam with porosity of 95%) and fluid flow with nanoparticles (AL2O3 and CUO) are generated in the software. After analyzing PTC pipes in FLOW-3D software, for analyzing energy and exergy efficiency, software outputs were used as EES software input for optimization ratio of sedimentation and calculating energy and exergy analyses.Table 6 Collectors with different percentages of nanofluids and porous media.

In this research, an enhanced solar collector with both porous media and Nanofluid is investigated. In the present study, 0.1–0.5% CuO and Al2O3 concentration were added to the collector fully filled by porous media to achieve maximum energy and exergy efficiencies of solar CCHP systems. All steps of the investigation are shown in Table 6.

Energy and exergy analyses of parabolic solar collectors and SCCHP systems are shown in Figures 6 and 7.

Figure 6 Energy and exergy efficiencies of the PTC with porous media and nanofluid.

Figure 7 Energy and exergy efficiency of the SCCHP.

Results show that the highest energy and exergy efficiencies are 74.19% and 32.6%, respectively, that is achieved in Step 12 (parabolic collectors with filled porous media and 0.5% Al2O3). In the second step, the maximum energy efficiency of SCCHP systems with fourteen steps of simulation are shown in Figure 7.

In the second step, where 0.1, −0.6% of the nanofluids were added, it is found that 0.5% leads to the highest energy and exergy efficiency enhancement in solar collectors and SCCHP systems. Using concentrations more than 0.5% leads to sediment in the solar collector’s pipe and a decrease of porosity in the pipe [73]. According to Figure 7, maximum energy and exergy efficiencies of SCCHP are achieved in Step 12. In this step energy efficiency is 54.49% and exergy efficiency is 18.29%. In steps 13 and 14, with increasing concentration of CUO and Al2O3 nanofluid solution in porous materials, decreasing of energy and exergy efficiency of PTC and SCCHP system at the same time happened. This decrease in efficiency is due to the formation of sediment in the porous material. Calculations and simulations have shown that porous materials more than 0.5% nanofluids inside the collector pipe cause sediment and disturb the porosity of porous materials and pressure drop and reduce the coefficient of performance of the cogeneration system. Most experience showed that CUO and AL2O3 nanofluids with less than 0.6% percent solution are used in the investigation on the solar collectors at low temperatures and discharges [74]. One of the important points of this research is that the best ratio of nanofluids in the solar collector with a low temperature is 0.5% (AL2O3 and CUO); with this replacement, the cost of solar collectors and SCCHP cycle is reduced.

5. Conclusion and Future Directions

In the present study, ways for increasing the efficiency of solar collectors in order to enhance the efficiency of the SCCHP cycle are examined. The research is aimed at adding both porous materials and nanofluids for estimating the best ratio of nanofluid for enhanced solar collector and protecting sedimentation in porous media. By adding porous materials (copper foam with porosity of 95%) and 0.5% nanofluids together, high efficiency in solar parabolic collectors can be achieved. The novelty in this research is the addition of both nanofluids and porous materials and calculating the best ratio for preventing sedimentation and pressure drop in solar collector’s pipe. In this study, it was observed that, by adding 0.5% of AL2O3 nanofluid in working fluids, the energy efficiency of PTC rises to 74.19% and exergy efficiency is grown up to 32.6%. In SCCHP cycle, energy efficiency is 54.49% and exergy efficiency is 18.29%.

In this research, parabolic solar collectors fully filled by porous media (copper foam with a porosity of 95) are investigated. In the next step, parabolic solar collectors in the SCCHP cycle were simultaneously filled by porous media and different percentages of Al2O3 and CuO nanofluid. At this step, values of 0.1% to 0.6% of each nanofluid were added to the working fluid, and the efficiency of the energy and exergy of the collectors and the SCCHP cycle were determined. In this case, nanofluid and the porous media were used together in the solar collector and maximum efficiency achieved. 0.5% of both nanofluids were used to achieve the biggest efficiency enhancement.

In the present study, as expected, the highest efficiency is for the parabolic solar collector fully filled by porous material (copper foam with a porosity of 95%) and 0.5% Al2O3. Results of the present study are as follows:(1)The average enhancement of collectors’ efficiency using porous media and nanofluids is 28%.(2)Solutions with 0.1 to 0.5% of nanofluids (CuO and Al2O3) are used to prevent collectors from sediment occurrence in porous media.(3)Collector of solar cogeneration cycles that is enhanced by both porous media and nanofluid has higher efficiency, and the stability of output temperature is more as well.(4)By using 0.6% of the nanofluids in the enhanced parabolic solar collectors with copper porous materials, sedimentation occurs and makes a high-pressure drop in the solar collector’s pipe which causes decrease in energy efficiency.(5)Average enhancement of SCCHP cycle efficiency is enhanced by both porous media and nanofluid 13%.

Nomenclature

:Solar radiation
a:Heat transfer augmentation coefficient
A:Solar collector area
Bf:Basic fluid
:Specific heat capacity of the nanofluid
F:Constant of air dilution
:Thermal conductivity of the nanofluid
:Thermal conductivity of the basic fluid
:Viscosity of the nanofluid
:Viscosity of the basic fluid
:Collector efficiency
:Collector energy receives
:Auxiliary boiler heat
:Expander energy
:Gas energy
:Screw expander work
:Cooling load, in kilowatts
:Heating load, in kilowatts
:Solar radiation energy on collector, in Joule
:Sanitary hot water load
Np:Nanoparticle
:Energy efficiency
:Heat exchanger efficiency
:Sun exergy
:Collector exergy
:Natural gas exergy
:Expander exergy
:Cooling exergy
:Heating exergy
:Exergy efficiency
:Steam mass flow rate
:Hot water mass flow rate
:Specific heat capacity of water
:Power output form by the screw expander
Tam:Average ambient temperature
:Density of the mixture.

Greek symbols

ρ:Density
ϕ:Nanoparticles volume fraction
β:Ratio of the nanolayer thickness.

Abbreviations

CCHP:Combined cooling, heating, and power
EES:Engineering equation solver.

Data Availability

For this study, data were generated by CARRIER software for the average electrical, heating, and cooling load of a residential building with 600 m2 in the city of Zahedan, Iran.

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 1. Typical road and rail tunnel sections.

터널의 화재 위험을 평가하는 컴퓨터 모델(FASIT)

A Computer Model to Assess Fire Hazards in Tunnels (FASlT)

David A. Charters, W. Alan Gray, Andrew C. McIntosh
Charters is now with NHS Estates in Leeds (previously with AEA Consultancy
Services), and Gray and Mclntosh are with the University of Leeds, England.

Abstract

터널에서 화재 성장 움직임을 시뮬레이션하는 컴퓨터 모델이 설명되고 터널 시스템에 대한 간략한 개요가 표시됩니다. 질량 흐름, 속도, 연기 농도 및 열 전달을 예측하는 방법과 위험 출력 매개 변수 목록이 표시됩니다. 실험에 대한 모델의 유효성 검사와 향후 작업에 대한 가능한 방향도 제시됩니다.

Introduction

최근 도로 및 철도 터널의 화재 안전에 대해 운송 업계와 여행자들 사이에서 많은 우려가 제기되고 있습니다.

1,2,3 터널에서 연소 생성물은 한 방향 또는 두 방향을 제외한 모든 방향으로 제한되어 매우 빠른 연기 이동과 생명에 대한 빠른 위협을 초래할 수 있습니다.

이 분야의 많은 초기 작업은 Thomas에 의해 수행되었습니다. 4,5 AEA Consultancy Services와 University of Leeds의 연료 및 에너지부는 현재 터널의 구멍으로 인한 위험을 예측하는 컴퓨터 모델을 개발 중입니다.

이 모델은 터널 내 설비의 위험과 화재 위험 수준, 화재 방지 시스템의 이점을 평가하는 데 도움이 됩니다.

유사한 ‘구역’ 화재 모델에서 Considine et al. 7은 유해 물질 운송을 포함하는 피트에 대한 모델을 개발했으며 Miclea 등은 터널 환기에 대한 화재의 영향을 평가하고 비상 환기를 논의하는 터널 환기 모델을 개발했으며 Laage 등은 터널 환기 모델을 개발했습니다.

9는 특히 광산 네트워크의 화재에 대한 모델을 개발했습니다. 다른 터널 화재 모델에서 Kumar et al.10 및 Jones et al.11은 터널 화재의 유체 흐름을 예측하기 위해 전산 유체 역학(CFD) 또는 ‘장’ 모델을 사용합니다.

AEA/Leeds University에서 개발 중인 코드는 터널의 화재 위험을 예측하기 위한 더 큰 모델의 일부가 되도록 의도되었습니다.

이 코드는 FASIT(Fire growth And Smoke movement In Tunnels) 모델이라고 합니다.12 FASIT는 구조가 모듈식이므로 화염, 연기, 부력 흐름, 열 전달 등에 대한 개선된 모델을 많은 수의 재작성 없이 통합할 수 있습니다.

Figure 1. Typical road and rail tunnel sections.
Figure 1. Typical road and rail tunnel sections.
Figure 2. Tunnel zone/layer schematic.
Figure 2. Tunnel zone/layer schematic.
Figure 3. Schematic of plume mass flows°
Figure 3. Schematic of plume mass flows°

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Fig. 2 Schematic diagram of the experimental Rijke tube

RIJKE 튜브 내부의 열음향 장에 대한 새로운 조사

A novel investigation of the thermoacoustic field inside a Rijke tube

B. EntezamW. Van Moorhem and J. MajdalaniPublished Online:22 Aug 2012 https://doi.org/10.2514/6.1998-2582

Abstract

이 논문에서는 Rijke 튜브 내부의 시간 종속 유동장의 실험 연구 및 계산 시뮬레이션에서 진행한 결과를 제시하고 해석합니다. 기존의 추측과 스케일링 분석을 기반으로 한 이론적 논의가 진행됩니다. 주요 결과에는 열 구동 진동에서 중요한 역할을 하는 것으로 보이는 유사성 매개변수가 포함됩니다. 이 매개변수는 열 섭동을 속도, 압력 및 특성 길이의 제곱과 관련시킵니다. 열 진동을 압력 및 속도 진동의 결합된 효과에 기인하는 간단한 이론은 계산, 실험 및 스케일링 고려 사항을 통해 논의됩니다. 이전의 분석 이론은 열 진동을 속도 또는 압력 진동에 연결했기 때문에 현재 분석 모델은 기존 추측에 동의하고 조정합니다. Rayleigh 기준에 따라 열원은 Rijke-tube 하단에서 1/4의 임계 거리에 위치해야 공명이 발생합니다. 이 관찰은 결합이 최대화되는 임계점이 음향 속도와 압력의 곱인 음향 강도가 가장 큰 공간 위치에 해당하기 때문에 제안된 해석을 확인합니다. 수치 시뮬레이션은 Rijke 튜브 내부의 압력 진동이 열 입력이 증가함에 따라 기하급수적으로 증가한다는 것을 보여줍니다. 충분히 작은 열 입력으로 음향 싱크가 소스를 초과하고 음향 감쇠가 발생합니다. 열 입력이 임계 임계값 이상으로 증가하면 음향 싱크가 불충분해져서 ​​내부 에너지 축적으로 인해 빠른 음향 증폭이 발생합니다.

In this paper, results proceeding from experimental studies and computational simulations of the time-dependent flowfield inside a Rijke tube are presented and interpreted. A theoretical discussion based on existing speculations and scaling analyses is carried out. The main results include a similarity parameter that appears to play an important role in the heat driven oscillations. This parameter relates heat perturbations to velocity, pressure, and the square of a characteristic length. A simple theory that attributes heat oscillations to the combined effects of pressure and velocity oscillations is discussed via computational, experimental, and scaling considerations. Since previous analytical theories link heat oscillations to either velocity or pressure oscillations, the current analytical model agrees with and reconciles between existing speculations. In compliance with the Rayleigh criterion, it is found that the heat source must be positioned at a critical distance of 1/4 from the Rijke-tube lower end for resonance to occur. This observation confirms our proposed interpretation since the critical point where coupling is maximized corresponds to a spatial location where the acoustic intensity, product of both acoustic velocities and pressures, is largest. Numerical simulations show that pressure oscillations inside the Rijke tube grow exponentially with increasing heat input With a sufficiently small heat input, the acoustic sinks exceed the sources and acoustic damping takes place. When the heat input is augmented beyond a critical threshold, acoustic sinks become insufficient causing rapid acoustic amplification by virtue of internal energy accumulation.

Fig. 2 Schematic diagram of the experimental Rijke tube
Fig. 2 Schematic diagram of the experimental Rijke tube
A novel investigation of the thermoacoustic field inside a Rijke tube
A novel investigation of the thermoacoustic field inside a Rijke tube

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Mesh conditions: a) mesh block; b) computational cells c) boundary conditions applied in simulation

FLOW-3D를 이용한 Λ자 단차가 있는 계단식 배수로의 에너지 소산 조건 연구

A Study of the Conditions of Energy Dissipation in Stepped Spillways with Λ-shaped step Using FLOW-3D

Authors:

Abbas Mansoori at Islamic Azad University

Abbas Mansoori

Shadi Erfanian

Abstract and Figures

본 연구에서는 특정 유형의 계단식 배수로에서 에너지 소산을 조사했습니다. 목적은 여수로 하류에서 최고 수준의 에너지 소산을 달성하는 것이었습니다.

큰 러프니스로 계단에 대한 특정 유형의 기하학을 제공하여 수행되었습니다. 여기에서 계단은 흐름에 대한 큰 거칠기로 인식되었습니다.

이 단계에서 최대 흐름 에너지가 최소화될 수 있도록 모양과 수를 설계했습니다. 따라서 하류의 구조에서 가장 높은 에너지 소산률을 얻을 수 있다고 말할 수 있습니다. 또한, 이에 따라 프로젝트에서 저유조를 설계하고 건설함으로써 부과되는 막대한 비용을 최소화할 수 있었습니다.

이 연구에서는 FLOW-3D를 사용하여 에너지 소산율을 분석하고 구했습니다. 최대 에너지 소산을 달성할 수 있는 계단의 최상의 기하학은 관련 문헌을 검토하고 FLOW-3D에서 제안된 모델을 발명하여 결정되었습니다.

제안된 방법을 평가하기 위해 앞서 언급한 방법들과 함께 시행착오를 통해 메쉬망 크기를 분석하고 그 결과를 다른 연구들과 비교하였습니다. 즉, 스무드 스텝에 비해 에너지 소산율이 25도 각도에서 Λ자 스텝으로 가장 최적의 상태를 얻었습니다.

In the present study, energy dissipation was investigated in a specific type of stepped spillways. The purpose was to achieve the highest level of energy dissipation in downstream of the spillway. It was performed by providing a specific type of geometry for step as a great roughness. Here, steps were recognized as great roughness against flow. Their shape and number were designed in such a way that the maximum flow energy can be minimized in this stage, i.e. over steps before reaching to downstream. Accordingly, it can be stated that the highest energy dissipation rate will be obtained in the structure at downstream. Moreover, thereby, heavy costs imposed by designing and constructing stilling basin on project can be minimized. In this study, FLOW-3D was employed to analyse and obtain energy dissipation rate. The best geometry of the steps, through which the maximum energy dissipation can be achieved, was determined by reviewing related literature and inventing the proposed model in FLOW-3D. To evaluate the proposed method, analyses were performed using trial and error in mesh networks sizes as well as the mentioned methods and the results were compared to other studies. In other words, the most optimal state was obtained with Λ-shaped step at angel of 25 degree with respect to energy dissipation rate compare to smooth step.

Figure 2. Three-dimensional design of the spillway using SolidWorks 2012
Figure 2. Three-dimensional design of the spillway using SolidWorks 2012
The results obtained from energy dissipation computation
Geometrical characteristics of the í µíº²-shaped stepped spillway To investigate flow filed and hydraulic conditions, boundary and initial conditions should be applied to each of the models in FLOW-3D. 
Mesh conditions: a) mesh block; b) computational cells; c) boundary conditions applied in simulation 
Figure 6. a) 3D Numerical modelling of flow over Spillway; b) 3D experimental modelling of flow over Spillway (with the discharge of  )
Figure 6. a) 3D Numerical modelling of flow over Spillway; b) 3D experimental modelling of flow over Spillway (with the discharge of  )
Figure 7. 2D model of flow depth for each angle of the-shaped steps
Figure 7. 2D model of flow depth for each angle of the-shaped steps

References

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Forming characteristics and control method of weld bead for GMAW on curved surface

곡면에 GMAW용 용접 비드의 형성 특성 및 제어 방법

Forming characteristics and control method of weld bead for GMAW on curved surface

The International Journal of Advanced Manufacturing Technology (2021)Cite this article

Abstract

곡면에서 GMAW 기반 적층 가공의 용접 성형 특성은 중력의 영향을 크게 받습니다. 성형면의 경사각이 크면 혹 비드(hump bead)와 같은 심각한 결함이 발생합니다.

본 논문에서는 양생면에서 용접 비드 형성의 형성 특성과 제어 방법을 연구하기 위해 용접 용융 풀 유동 역학의 전산 모델을 수립하고 제안된 모델을 검증하기 위해 증착 실험을 수행하였습니다.

결과는 용접 비드 경사각(α)이 증가함에 따라 역류의 속도가 증가하고 상향 용접의 경우 α > 60°일 때 불규칙한 험프 결함이 나타나는 것으로 나타났습니다.

상부 과잉 액체의 하향 압착력과 하부 상향 유동의 반동력과 표면장력 사이의 상호작용은 용접 혹 형성의 주요 요인이었다. 하향 용접의 경우 양호한 형태를 얻을 수 있었으며, 용접 비드 경사각이 증가함에 따라 용접 높이는 감소하고 용접 폭은 증가하였습니다.

하향 및 상향 용접을 위한 곡면의 용융 거동 및 성형 특성을 기반으로 험프 결함을 제어하기 위해 위브 용접을 통한 증착 방법을 제안하였습니다.

성형 궤적의 변화로 인해 용접 방향의 중력 성분이 크게 감소하여 용융 풀 흐름의 안정성이 향상되었으며 복잡한 표면에서 안정적이고 일관된 용접 비드를 얻는 데 유리했습니다.

하향 용접과 상향 용접 사이의 단일 비드의 치수 편차는 7% 이내였으며 하향 및 상향 혼합 혼합 비드 중첩 증착에서 비드의 변동 편차는 0.45로 GMAW 기반 적층 제조 공정에서 허용될 수 있었습니다.

이러한 발견은 GMAW를 기반으로 하는 곡선 적층 적층 제조의 용접 비드 형성 제어에 기여했습니다.

The weld forming characteristics of GMAW-based additive manufacturing on curved surface are dramatically influenced by gravity. Large inclined angle of the forming surface would lead to severe defects such as hump bead. In this paper, a computational model of welding molten pool flow dynamics was established to research the forming characteristic and control method of weld bead forming on cured surface, and deposition experiments were conducted to verify the proposed model. Results indicated that the velocity of backward flows increased with the increase of weld bead tilt angle (α) and irregular hump defects appeared when α > 60° for upward welding. The interaction between the downward squeezing force of the excess liquid at the top and the recoil force of the upward flow at the bottom and the surface tension were primary factors for welding hump formation. For downward welding, a good morphology shape could be obtained, and the weld height decreased and the weld width increased with the increase of weld bead tilt angle. Based on the molten behaviors and forming characteristics on curved surface for downward and upward welding, the method of deposition with weave welding was proposed to control hump defects. Gravity component in the welding direction was significantly reduced due to the change of forming trajectory, which improved the stability of the molten pool flow and was beneficial to obtain stable and consistent weld bead on complex surface. The dimensional deviations of the single bead between downward and upward welding were within 7% and the fluctuation deviation of the bead in multi-bead overlapping deposition with mixing downward and upward welding was 0.45, which could be acceptable in GMAW-based additive manufacturing process. These findings contributed to the weld bead forming control of curve layered additive manufacturing based on GMAW.

Keywords

  • Molten pool behaviors
  • GMAW-based WAAM
  • Deposition with weave welding
  • Welding on curved surface
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Figure 1 Location map of barrier lakes, Sichuan-Tibet region, China

Barrier Lake의 홍수 침수 진행 및 평가지역 생태 시공간 반응 사례 연구 (쓰촨-티베트 지역)

Flood Inundation Evolution of Barrier Lake and Evaluation of Regional Ecological Spatiotemporal Response — A Case Study of Sichuan-Tibet Region

Abstract

중국 쓰촨-티베트 지역은 댐 호수의 발생과 붕괴를 동반한 지진 재해가 빈번한 지역이었습니다. 댐 호수의 붕괴는 하류 직원의 생명과 재산 안전을 심각하게 위협합니다.

동시에 국내외 학자들은 주변의 댐 호수에 대해 우려하고 있으며 호수에 대한 생태 연구는 거의 없으며 댐 호수가 생태에 미치는 영향은 우리 호수 건설 프로젝트에서 매우 중요한 계몽 의의를 가지고 있습니다.

이 기사의 목적은 방벽호의 댐 붕괴 위험을 과학적으로 예측하고 생태 환경에 대한 영향을 조사하며 통제 조치를 제시하는 것입니다. 본 논문은 쓰촨-티베트 지역의 Diexihaizi, Tangjiashan 댐호, Hongshihe 댐의 4대 댐 호수 사건을 기반으로 원격 감지 이미지에서 수역을 추출하고 HEC-RAS 모델을 사용하여 위험이 있는지 여부를 결정합니다.

댐 파손 여부 및 댐의 경로 예측; InVEST 모델을 이용하여 1990년부터 2020년까지 가장 작은 행정 구역(군/구)이 위치한 서식지를 평가 및 분석하고, 홍수 침수 결과를 기반으로 평가합니다. 결과는 공학적 처리 후 안정적인 댐 호수(Diexi Haizi)가 서식지 품질 지수에 안정화 효과가 있음을 보여줍니다.

댐 호수의 형성은 인근 토지 이용 유형과 지역 경관 생태 패턴을 변화 시켰습니다. 서식지 품질 지수는 사이 호수 주변 1km 지역에서 약간 감소하지만 3km 지역과 5km 지역에서 서식지 품질이 향상됩니다. 인공 홍수 방류 및 장벽 호수의 공학적 보강이 필요합니다.

이 논문에서 인간의 통제가 강한 지역은 다른 지역의 서식지 질 지수보다 더 잘 회복될 것입니다.

The Sichuan-Tibet region of China has always been an area with frequent earthquake disasters, accompanied by the occurrence and collapse of dammed lakes. The collapse of dammed lakes seriously threatens the lives and property safety of downstream personnel.

At the same time, domestic and foreign scholars are concerned about the surrounding dammed lake there are few ecological studies on the lake, and the impact of the dammed lake on the ecology has very important enlightenment significance for our lake construction project. It is the purpose of this article to scientifically predict the risk of dam break in a barrier lake, explore its impact on the ecological environment and put forward control measures.

Based on the four major dammed lake events of Diexihaizi, Tangjiashan dammed lake, and Hongshihe dammed lake in the Sichuan-Tibet area, this paper extracts water bodies from remote sensing images and uses the HEC-RAS model to determine whether there is a risk of the dam break and whether Forecast the route of the dam; and use the InVEST model to evaluate and analyze the habitat of the smallest administrative district (county/district) where it is located from 1990 to 2020 and make an evaluation based on the results of flood inundation.

The results show that the stable dammed lake (Diexi Haizi) after engineering treatment has a stabilizing effect on the habitat quality index. The formation of the dammed lake has changed the nearby land-use types and the regional landscape ecological pattern.

The habitat quality index will decrease slightly in the 1 km area around Sai Lake, but the habitat quality will increase in the 3 km area and the 5 km area. Artificial flood discharge and engineering reinforcement of barrier lakes are necessary. In this paper, the areas with strong human control will recover better than other regions’ habitat quality index.

Fengshan Jiang (  florachaing@mail.ynu.edu.cn )
Yunnan University https://orcid.org/0000-0001-6231-6180
Xiaoai Dai
Chengdu University of Technology https://orcid.org/0000-0003-1342-6417
Zhiqiang Xie
Yunnan University
Tong Xu
Yunnan University
Siqiao Yin
Yunnan University
Ge Qu
Chengdu University of Technology
Shouquan Yang
Yunnan University
Yangbin Zhang
Yunnan University
Zhibing Yang
Yunnan University
Jiarui Xu
Yunnan University
Zhiqun Hou
Kunming institute of surveying and mapping

Keywords

dammed lake, regional ecology, flood simulation, habitat quality

Figure 1 Location map of barrier lakes, Sichuan-Tibet region, China
Figure 1 Location map of barrier lakes, Sichuan-Tibet region, China
Figure 8 Habitat quality changes in Maoxian County
Figure 8 Habitat quality changes in Maoxian County
Figure 9 Habitat quality changes in Beichuan County
Figure 9 Habitat quality changes in Beichuan County
Figure 10 Habitat quality change map of Qingchuan County
Figure 10 Habitat quality change map of Qingchuan County

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CFD Simulations of Conical Central Baffle Flumes | Journal of Irrigation and Drainage Engineering | Vol 148, No 2

원추형 중앙 배플 수로의 CFD 시뮬레이션

CFD Simulations of Conical Central Baffle Flumes

Abstract

Ankur KapoorAniruddha D. Ghare; and Avinash M. Badar

원추형 중앙 배플 수로는 개방 채널에서 임시 유량 측정을 위한 효과적인 솔루션을 제공합니다. 

원추형 중앙 배플 수로는 원뿔 모양의 장애물 또는 열린 수로의 중심에서 수직으로 향하는 중앙 배플로 구성됩니다. 본 연구에서, 원추형 중앙 배플 수로를 사용하여 개방 채널에서 유량 측정을 위해 이전에 개발된 배출 예측 모델은 더 넓은 적용 범위를 커버하기 위해 직사각형 및 사다리꼴 채널에서 사용하기 위해 실험적으로 재 보정되었습니다. 

제안된 보정 방정식은 FLOW-3D를 사용한 전산유체역학(CFD) 시뮬레이션 결과를 사용하여 확장된 범위의 흐름 및 기하학적 매개변수에 대해 검증되었습니다. 

시뮬레이션 연구는 두 단계로 수행됩니다. 첫 번째 단계는 시뮬레이션의 수면 프로파일과 동일한 배출 및 흐름 조건에 대한 실험 흐름을 비교하여 설정한 정의된 시뮬레이션 문제의 검증입니다. 

두 번째 단계는 무차원 방전 및 측면 경사(중1= 0중1=0, 0.50, 1.00 및 1.50). 80% 미만의 수중에서 방전 예측의 오류는 평균값이 거의 3%로 항상 10% 미만인 것으로 나타났습니다. 

CFD 분석 결과에 따르면 보정된 배출 예측 모델의 사용은 수중 한계 80%까지 권장되었으며, 그 이상에서는 오차가 10% 이상인 것으로 나타났습니다.

Conical central baffle flumes present an effective solution for temporary flow measurements in open channels. A conical central baffle flume consists of a cone-shaped obstruction, or a central baffle, oriented vertically at the center of an open channel. In the present study, a previously developed discharge prediction model for flow measurements in open channels using the conical central baffle flumes has been experimentally recalibrated for use in rectangular and trapezoidal channels to cover a wider application range. The proposed calibration equation has been validated for an extended range of flow and geometrical parameters using the results of computational fluid dynamics (CFD) simulations using Flow-3D. The simulation studies are carried out in two steps. The first step is the validation of the defined simulation problem set up by comparing the water surface profiles of the simulation and experiment flows for the same discharge and flow conditions. The second step is the validation of the proposed discharge prediction model for the extended range (0–0.50) of the dimensionless discharge and side slopes (m1=0m1=0, 0.50, 1.00, and 1.50). It is found that for submergence less than 80%, the error in discharge prediction is always less than 10% with a mean value of nearly 3%. Based on the results of the CFD analysis, the use of the calibrated discharge prediction model has been recommended up to a submergence limit of 80%, beyond which the errors are found to be greater than 10%.

ASCE Library CFD Simulations of Conical Central Baffle Flumes | Journal of Irrigation and Drainage Engineering | Vol 148, No 2
ASCE Library CFD Simulations of Conical Central Baffle Flumes | Journal of Irrigation and Drainage Engineering | Vol 148, No 2
CFD Simulations of Conical Central Baffle Flumes | Journal of Irrigation and Drainage Engineering | Vol 148, No 2
CFD Simulations of Conical Central Baffle Flumes | Journal of Irrigation and Drainage Engineering | Vol 148, No 2
CFD Simulations of Conical Central Baffle Flumes | Journal of Irrigation and Drainage Engineering | Vol 148, No 2
CFD Simulations of Conical Central Baffle Flumes | Journal of Irrigation and Drainage Engineering | Vol 148, No 2
Channel Flow Measurement Using Portable Conical Central Baffle | Journal of Irrigation and Drainage Engineering | Vol 145, No 11
Channel Flow Measurement Using Portable Conical Central Baffle | Journal of Irrigation and Drainage Engineering | Vol 145, No 11
Figure 2. (a) Scanning electron microscopy images of Ti6Al4V powder particles and (b) simulated powder bed using discrete element modelling

Laser Powder Bed에서 Laser Drilling에 의한 Keyhole 형성 Ti6Al4V 생체 의학 합금의 융합: 메조스코픽 전산유체역학 시뮬레이션 대 경험적 검증을 사용한 수학적 모델링

Keyhole Formation by Laser Drilling in Laser Powder Bed Fusion of Ti6Al4V Biomedical Alloy: Mesoscopic Computational Fluid Dynamics Simulation versus Mathematical Modelling Using Empirical Validation

Asif Ur Rehman 1,2,3,*
,† , Muhammad Arif Mahmood 4,*
,† , Fatih Pitir 1
, Metin Uymaz Salamci 2,3
,
Andrei C. Popescu 4 and Ion N. Mihailescu 4

Abstract

LPBF(Laser Powder Bed fusion) 공정에서 작동 조건은 열 분포를 기반으로 레이저 유도 키홀 영역을 결정하는 데 필수적입니다. 얕은 구멍과 깊은 구멍으로 분류되는 이러한 영역은 LPBF 프로세스에서 확률과 결함 형성 강도를 제어합니다.

LPBF 프로세스의 핵심 구멍을 연구하고 제어하기 위해 수학적 및 CFD(전산 유체 역학) 모델이 제공됩니다. CFD의 경우 이산 요소 모델링 기법을 사용한 유체 체적 방법이 사용되었으며, 분말 베드 보이드 및 표면에 의한 레이저 빔 흡수를 포함하여 수학적 모델이 개발되었습니다.

동적 용융 풀 거동을 자세히 살펴봅니다. 실험적, CFD 시뮬레이션 및 분석적 컴퓨팅 결과 간에 정량적 비교가 수행되어 좋은 일치를 얻습니다.

LPBF에서 레이저 조사 영역 주변의 온도는 높은 내열성과 분말 입자 사이의 공기로 인해 분말층 주변에 비해 급격히 상승하여 레이저 횡방향 열파의 이동이 느려집니다. LPBF에서 키홀은 에너지 밀도에 의해 제어되는 얕고 깊은 키홀 모드로 분류될 수 있습니다. 에너지 밀도를 높이면 얕은 키홀 구멍 모드가 깊은 키홀 구멍 모드로 바뀝니다.

깊은 키홀 구멍의 에너지 밀도는 다중 반사와 키홀 구멍 내의 2차 반사 빔의 집중으로 인해 더 높아져 재료가 빠르게 기화됩니다.

깊은 키홀 구멍 모드에서는 온도 분포가 높기 때문에 액체 재료가 기화 온도에 가까우므로 얕은 키홀 구멍보다 구멍이 형성될 확률이 훨씬 높습니다. 온도가 급격히 상승하면 재료 밀도가 급격히 떨어지므로 비열과 융해 잠열로 인해 유체 부피가 증가합니다.

그 대가로 표면 장력을 낮추고 용융 풀 균일성에 영향을 미칩니다.

In the laser powder bed fusion (LPBF) process, the operating conditions are essential in determining laser-induced keyhole regimes based on the thermal distribution. These regimes, classified into shallow and deep keyholes, control the probability and defects formation intensity in the LPBF process. To study and control the keyhole in the LPBF process, mathematical and computational fluid dynamics (CFD) models are presented. For CFD, the volume of fluid method with the discrete element modeling technique was used, while a mathematical model was developed by including the laser beam absorption by the powder bed voids and surface. The dynamic melt pool behavior is explored in detail. Quantitative comparisons are made among experimental, CFD simulation and analytical computing results leading to a good correspondence. In LPBF, the temperature around the laser irradiation zone rises rapidly compared to the surroundings in the powder layer due to the high thermal resistance and the air between the powder particles, resulting in a slow travel of laser transverse heat waves. In LPBF, the keyhole can be classified into shallow and deep keyhole mode, controlled by the energy density. Increasing the energy density, the shallow keyhole mode transforms into the deep keyhole mode. The energy density in a deep keyhole is higher due to the multiple reflections and concentrations of secondary reflected beams within the keyhole, causing the material to vaporize quickly. Due to an elevated temperature distribution in deep keyhole mode, the probability of pores forming is much higher than in a shallow keyhole as the liquid material is close to the vaporization temperature. When the temperature increases rapidly, the material density drops quickly, thus, raising the fluid volume due to the specific heat and fusion latent heat. In return, this lowers the surface tension and affects the melt pool uniformity.

Keywords: laser powder bed fusion; computational fluid dynamics; analytical modelling; shallow
and deep keyhole modes; experimental correlation

Figure 1. Powder bed schematic with voids.
Figure 1. Powder bed schematic with voids.
Figure 2. (a) Scanning electron microscopy images of Ti6Al4V powder particles and (b) simulated powder bed using discrete element modelling
Figure 2. (a) Scanning electron microscopy images of Ti6Al4V powder particles and (b) simulated powder bed using discrete element modelling
Figure 3. Temperature field contour formation at various time intervals (a) 0.695 ms, (b) 0.795 ms, (c) 0.995 ms and (d) 1.3 ms.
Figure 3. Temperature field contour formation at various time intervals (a) 0.695 ms, (b) 0.795 ms, (c) 0.995 ms and (d) 1.3 ms.
Figure 4. Detailed view of shallow depth melt mode with temperature field at 0.695 ms
Figure 4. Detailed view of shallow depth melt mode with temperature field at 0.695 ms
Figure 5. Melt flow stream traces formation at various time intervals (a) 0.695 ms, (b) 0.795 ms, (c) 0.995 ms and (d) 1.3 ms
Figure 5. Melt flow stream traces formation at various time intervals (a) 0.695 ms, (b) 0.795 ms, (c) 0.995 ms and (d) 1.3 ms
Figure 6. Density evolution of the melt pool at various time intervals (a) 0.695 ms, (b) 0.795 ms, (c) 0.995 ms and (d) 1.3 ms.
Figure 6. Density evolution of the melt pool at various time intervals (a) 0.695 ms, (b) 0.795 ms, (c) 0.995 ms and (d) 1.3 ms.
Figure 7. Un-melted and melted regions at different time intervals (a) 0.695 ms, (b) 0.795 ms, (c) 0.995 ms and (d) 1.3 ms
Figure 7. Un-melted and melted regions at different time intervals (a) 0.695 ms, (b) 0.795 ms, (c) 0.995 ms and (d) 1.3 ms
Figure 8. Transformation from shallow depth melt flow to deep keyhole formation when laser power increased from (a) 170 W to (b) 200 W
Figure 8. Transformation from shallow depth melt flow to deep keyhole formation when laser power increased from (a) 170 W to (b) 200 W
Figure 9. Stream traces and laser beam multiple reflections in deep keyhole melt flow mode
Figure 9. Stream traces and laser beam multiple reflections in deep keyhole melt flow mode
Figure 10. A comparison between analytical and CFD simulation results for peak thermal distribution value in the deep keyhole formation
Figure 10. A comparison between analytical and CFD simulation results for peak thermal distribution value in the deep keyhole formation
Figure 11. A comparison among experiments [49], CFD and analytical simulations for deep keyhole top width and bottom width
Figure 11. A comparison among experiments [49], CFD and analytical simulations for deep keyhole top width and bottom width

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Experimental and Numerical Investigation of Hydrodynamic Performance of a Sloping Floating Breakwater with and Without Chain-Net

Chain-Net이 있거나 없는 경사 부유식 방파제의 유체역학적 성능에 대한 실험 및 수치적 조사

Experimental and Numerical Investigation of Hydrodynamic Performance of a Sloping Floating Breakwater with and Without Chain-Net

Keywords

  • Sloping floating breakwater
  • Chain net
  • Anchorage system
  • Hydrodynamic performance

Abstract

두 개의 부유체 사이에 간격이 있는 경사진 부유식 방파제(FB)에 대한 새로운 연구가 제안되었습니다. 구조물의 기울기는 파동 에너지 소산을 유발할 수 있습니다. 경사진 구조물의 문제는 파도가 넘친다는 것입니다. 이 문제를 해결하기 위해 두 플로터 사이의 간격을 고려합니다. 

오버 토핑이 발생하면 마루를 통과하는 물이 두 플로터 사이의 틈으로 쏟아지며 결과적으로 파도 에너지가 감쇠됩니다. 체인 네트가 모델에 추가되고 전송 계수에 대한 영향이 연구됩니다. 또한, 구조물의 유체역학적 성능에 대한 자유도의 영향을 조사하기 위해 말뚝으로 고정된(1 자유도) 계류 라인으로 고정된(3도의 자유도) 두 가지 고정 시스템에서 자유 모델을 연구했습니다.

게다가, 실험은 5개의 다른 파도 주기와 4개의 다른 파도 높이를 가진 규칙파에서 수행됩니다. 실험 결과, 경사형 부유식 방파제가 직사각형 상자형보다 최대 15% 성능이 우수한 것으로 나타났다. 말뚝에 의해 고정된 FB에 대한 투과계수는 단파에서 케이블에 의해 고정된 FB보다 최대값으로 약 14% 낮고 장파에서 약 4-10% 더 높다. 흘수가 증가함에 따라 전송 계수는 감소하지만 건현은 허용 비율의 초과를 제한하기 위한 최소 요구 사항을 충족해야 합니다. 

체인 그물이 있는 모델은 없는 모델에 비해 전달 계수가 최대 14% 감소하여 더 나은 성능을 나타냅니다. 실험 결과, 경사형 부유식 방파제가 직사각형 상자형보다 최대 15% 성능이 우수한 것으로 나타났다. 말뚝에 의해 고정된 FB에 대한 투과계수는 단파에서 케이블에 의해 고정된 FB보다 최대값으로 약 14% 낮고 장파에서 약 4-10% 더 높다. 흘수가 증가함에 따라 전송 계수는 감소하지만 건현은 허용 비율의 초과를 제한하기 위한 최소 요구 사항을 충족해야 합니다. 

체인 그물이 있는 모델은 없는 모델에 비해 전달 계수가 최대 14% 감소하여 더 나은 성능을 나타냅니다. 실험 결과, 경사형 부유식 방파제가 직사각형 상자형보다 최대 15% 성능이 우수한 것으로 나타났다. 말뚝에 의해 고정된 FB에 대한 투과계수는 단파에서 케이블에 의해 고정된 FB보다 최대값으로 약 14% 낮고 장파에서 약 4-10% 더 높다. 흘수가 증가함에 따라 전송 계수는 감소하지만 건현은 허용 비율의 초과를 제한하기 위한 최소 요구 사항을 충족해야 합니다.

체인 그물이 있는 모델은 없는 모델에 비해 전달 계수가 최대 14% 감소하여 더 나은 성능을 나타냅니다. 말뚝에 의해 고정된 FB에 대한 투과계수는 단파에서 케이블에 의해 고정된 FB보다 최대값으로 약 14% 낮고 장파에서 약 4-10% 더 높다. 흘수가 증가함에 따라 전송 계수는 감소하지만 건현은 허용 비율의 초과를 제한하기 위한 최소 요구 사항을 충족해야 합니다. 

체인 그물이 있는 모델은 없는 모델에 비해 전달 계수가 최대 14% 감소하여 더 나은 성능을 나타냅니다. 말뚝에 의해 고정된 FB에 대한 투과계수는 단파에서 케이블에 의해 고정된 FB보다 최대값으로 약 14% 낮고 장파에서 약 4-10% 더 높다. 

흘수가 증가함에 따라 전송 계수는 감소하지만 건현은 허용 비율의 초과를 제한하기 위한 최소 요구 사항을 충족해야 합니다. 체인 그물이 있는 모델은 없는 모델에 비해 전달 계수가 최대 14% 감소하여 더 나은 성능을 나타냅니다.

A novel study of sloping floating breakwater (FB) that has a gap between two floaters is proposed. The slope of a structure can cause wave energy dissipation. A problem with sloping structures is wave overtopping. To solve this problem, a gap is considered between the two floaters. If overtopping occurs, water passing the crest will pour into the gap between the two floaters, as a result wave energy will be attenuated. A chain net is added to the model and its effect on the transmission coefficient is studied. Furthermore, in order to investigate the effects of the degree of freedom on the hydrodynamic performance of the structure, the model is studied in the two anchorage systems which are anchored by pile (1 degree of freedom) and anchored by mooring lines (3 degree of freedom). Moreover, the experiments are performed under regular waves with five different wave periods and four different wave heights. The results of the experiments show a sloping floating breakwater that has a better performance than that of rectangular box type by 15% as maximum value. The transmission coefficients for the FB anchored by pile are lower about 14% as maximum value than that of the FB anchored by cable in shorter waves and are higher about 4–10% in longer waves. With increasing the draft, the transmission coefficient decreases but the freeboard should meet the minimum requirements to restrict overtopping in the allowable rate. The model with a chain net exhibits a better performance as compared with the model without it by a maximum 14% reduction in the transmission coefficients.

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Figure 1 | Original Compound Broad Crested Weir Model (PVC cast).

복합 광대보의 방류계수 예측을 위한 실험적 해석과 CFD 해석의 비교연구

Comparative study of experimental and CFD analysis for predicting discharge coefficient of compound broad crested weir

ABSTRACT

Present study highlights the behavior of weir crest head and width parameter on the discharge coefficient of compound broad crested (CBC) weir. Computational fluid dynamics model (CFD) is validated with laboratory experimental investigations.

In the discharge analysis through broad crested weirs, the upstream head over the weir crest (h) is crucial, where the result is mainly dependent upon the weir crest length (L) in transverse direction to flow, water depth from channel bed. Currently, minimal investigations are known for CFD validations on compound broad crested weirs.

The hydraulic research for measuring discharge numerically is carried out using FLOW 3D software. The model applies renormalized group (RNG) using volume of fluid (VOF) method for improved accuracy in free surface simulations. Structured hexagonal meshes of cubic elements define discretized meshing.

The comparative analysis of the numerical simulations and experimental observations confirm the performance of CBC weir for precise measurement of a wide range of discharges. Series of CFD model studies and experimental validation have led to constant range of discharg coefficients for various head over weir crest. The correlation coefficient of discharge predictions is 0.999 with mean error of 0.28%.

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넓은 볏이 있는 둑을 통한 유출 분석에서 둑 마루의 상류 수두(h)가 중요합니다. 여기서 결과는 주로 흐름에 대한 횡 방향의 둑 마루 길이(L), 수로 바닥에서 수심에 따라 달라집니다. . 현재 복합 넓은 볏 둑에 대한 CFD 검증에 대해 최소한의 조사가 알려져 있습니다.

수압 연구는 FLOW 3D 소프트웨어를 사용하여 수치적으로 측정합니다. 이 모델은 자유 표면 시뮬레이션의 정확도 향상을 위해 VOF(유체 체적) 방법을 사용하여 RNG(재정규화 그룹)를 적용합니다. 정육면체 요소의 구조화된 육각형 메쉬는 이산화된 메쉬를 정의합니다.

수치 시뮬레이션과 실험적 관찰의 비교 분석을 통해 광범위한 배출의 정확한 측정을 위한 CBC 둑의 성능을 확인했습니다. 일련의 CFD 모델 연구와 실험적 검증을 통해 다양한 head over weir crest에 대한 일정한 범위의 방전 계수가 나타났습니다. 방전 예측의 상관 계수는 0.999이고 평균 오차는 0.28%입니다.

Figure 1 | Original Compound Broad Crested Weir Model (PVC cast).
Figure 1 | Original Compound Broad Crested Weir Model (PVC cast).
Figure 4 | CFD Simulation for max discharge (y2 ¼ 13.557 cm, Qmax ¼ 10 lps) and min discharge (y2 ¼ 6.56 cm, Qmin ¼ 2 lps).
Figure 4 | CFD Simulation for max discharge (y2 ¼ 13.557 cm, Qmax ¼ 10 lps) and min discharge (y2 ¼ 6.56 cm, Qmin ¼ 2 lps).
Figure 5 | (a, b) Velocity profiles corresponding to max discharge (10 lps) and min discharge (2 lps).
Figure 5 | (a, b) Velocity profiles corresponding to max discharge (10 lps) and min discharge (2 lps).
Table 8 | Range of Froude number, Reynold number and Weber number
Table 8 | Range of Froude number, Reynold number and Weber number

Key words

compound weir, flow 3D, flow measurement, numerical technique, open channel

HIGHLIGHTS

• The Head-Discharge relation is established for discharge measurement using compound broad crested weir, experimentally and numerically.
• Assessment of head over weir crest for different step widths of proposed weir on discharge coefficient is executed.
• Experimental and CFD results of weir performance demonstrate good agreement between the theoretical discharges by traditional rectangular weir formulae keeping Cd constant.

CONCLUSION

  1. The head discharge relationship established for compound rectangular broad crested weir for various discharge ranges was validated by CFD technique. A three dimensional simulation software FLOW 3D was used for this purpose.
  2. Original theoretical compound weir model depicts the relative average error between discharge predictions with Flow 3D simulation as 4.96% which is found less than the predictions made by graphical interpolation technique which is 5.33%.
  3. The standard deviation in Cd parameter for CFD simulation model is less i.e. 0.0146 as compared to experimental output of 0.0502.
  4. The correlation coefficient for physical and CFD studies for modified compound weir model is high, around 0.999 with
    error in discharge predictions being 0.28% as compared to the accuracy limits of about +3–5% stated in literature so far.
  5. Discharge coefficient by experimental and CFD approach is maintained constant and equal to design input value of 0.6.
    Thus, the proposed CBC weir can be operated for various discharge ranges by maintaining constant discharge coefficients.
    Good agreement between the theoretical, experimental and CFD simulation results for obtaining discharge through compound broad crested weir ascertains the fact that CFD model can be used as an effective tool towards modeling flow through compound broad crested weir.

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Heat and Mass Transfer in a Cryogenic Tank in Case of Active-Pressurization

능동 가압의 경우 극저온 탱크의 열 및 물질 전달

Heat and Mass Transfer in a Cryogenic Tank in Case of Active-Pressurization

하이라이트

헤닝 슈플러 옌스 게르스트만DLR 독일 항공 우주 센터, 우주 시스템 연구소, 28359 Bremen, Germany

상변화 및 공액 열전달을 포함하는 압축성 2상 솔버 개발.

분석 솔루션으로 솔버를 성공적으로 검증.

극저온 탱크의 압력 및 온도 변화에 대한 정확한 시뮬레이션.

자유 표면에서의 물질 전달 분석.

Abstract

압력 요구 사항을 예측하는 것은 극저온 추진 시스템의 주요 과제 중 하나입니다. 이러한 맥락에서 증발 및 응축 현상을 고려한 탱크 여압을 시뮬레이션하기 위한 수치 모델을 개발하여 적용하였습니다. 

새로운 솔버는 PISO(splitting of operator) 알고리즘이 있는 압력 암시적 방법을 기반으로 하는 OpenFOAM의 약한 압축성 다상 솔버와 기울기 기반 위상 변화 모델을 결합합니다. 날카로운 인터페이스를 유지하기 위해 인터페이스에 인접한 셀에 질량 소스 용어가 적용됩니다. 

첫째, 모델은 1차원 상 변화 문제와 중력이 없는 상태에서 과열된 액체에서 증기 기포의 성장이라는 두 가지 분석 솔루션에 대해 검증되었습니다. 

두 번째 단계에서는 검증된 모델을 극저온 가압 실험에 적용했습니다. 측정된 압력 거동은 수치 모델이 양호한 근사값으로 확인될 수 있습니다. 

수치 모델을 사용하면 물리적 거동에 대한 추가 통찰력을 얻을 수 있습니다. 응축 및 증발 효과는 가압 중 및 가압 후의 압력 발생에 상당한 영향을 미칩니다. 기액 계면에서 일어나는 상변화로 인한 질량유동은 계면의 위치와 시간에 따라 달라진다. 벽에서 직접적으로 증발이 지배적이며 액체 표면의 중앙 영역에서 응결이 발생합니다. 

응축 및 증발 효과는 가압 중 및 가압 후의 압력 발생에 상당한 영향을 미칩니다. 기액 계면에서 일어나는 상변화로 인한 질량유동은 계면의 위치와 시간에 따라 달라진다. 벽에서 직접적으로 증발이 지배적이며 액체 표면의 중앙 영역에서 응결이 발생합니다. 

응축 및 증발 효과는 가압 중 및 가압 후의 압력 발생에 상당한 영향을 미칩니다. 기액 계면에서 일어나는 상변화로 인한 질량유동은 계면의 위치와 시간에 따라 달라진다. 벽에서 직접적으로 증발이 지배적이며 액체 표면의 중앙 영역에서 응결이 발생합니다.

Predicting the pressurant requirements is one of the key challenges for cryogenic propulsion systems. In this context, a numerical model to simulate the tank pressurization that considers evaporation and condensation phenomena was developed and applied. The novel solver combines the a gradient-based phase change model with a weakly compressible multiphase solver of OpenFOAM based on the pressure implicit method with splitting of operator (PISO) algorithm. To maintain a sharp interface the mass source terms are applied to the cells adjacent to the interface. First, the model is validated against two analytical solutions: the one-dimensional phase change problem and secondly, the growth of a vapor bubble in a superheated liquid in the absence of gravity. In a second step, the validated model was applied to a cryogenic pressurization experiment. The measured pressure behavior could be confirmed with the numerical model being in a good approximation. With the numerical model further insights into the physical behavior could be achieved. The condensation and evaporation effects have a significant impact on the pressure development during and after the pressurization. The mass flows due to phase change occurring at the vapor-liquid interface depend on interface location and time. Directly at the wall, evaporation becomes dominant while condensation occurs at the center area of the liquid surface.

  1. Fig. 1. Calculation of the gradient at the interface: On the left side the interface…
  2. Fig. 2. Mass source term distribution: First the sharp mass source term ρ0, which is…
  3. Fig. 3. a) Layout of the Stefan-Problem: a vapor is located between a liquid and a…
  4. Fig. 4. Bubble in a superheated liquid: The left side depicts the calculated and…
  5. Fig. 5. Modified drawing of the dewar (as documented in [5] [6]; dimensions in mm) and…
  6. Fig. 6. Schematic presentation of the pressure evoluation in the dewar: Initial…
  7. Fig. 7. Simulation of the pressurization phase: The diagram shows the pressure…
  8. Fig. 8. Turbulent thermal diffusivity in pressurization and relaxation phase
  9. Fig. 9. Comparison of the pressure evolution in the relaxation phase of the solver with…
  10. Fig. 10. On the left side the temperature evolution in the bulk of the gas phase is shown
  11. Fig. 11. Heat Flux profile over the interface caused by evaporation with details of the…
  12. Fig. 12. Temperatures field with velocity vectors at 420 seconds after the start of the…
  13. Fig. 13. Heat transfer to the liquid from the wall and the freesurface with and without…

Hide figures

키워드

Pressurization, Phase Change, CFD, Propellant Management, 가압, 상 변화, 추진제 관리

Figure 1- The experimental model [17]

와류형 우수 저류지의 수치 모델링에 대한 난류 슈미트 수의 영향 조사

Investigation of the Turbulent Schmidt Number Effects On Numerical Modelling Of Vortex-Type Stormwater Retention Ponds

S. M. Yamini1; H. Shamloo2; S. H. Ghafari3
1M.Eng., Dep. of Civil Engineering K.N. Toosi University of Technology, Valiasr St., Tehran, Iran.
smyamini@alumni.kntu.ac.ir
2Associate Professor, Dep. of Civil Engineering K.N. Toosi University of Technology, Valiasr St., Tehran, Iran.
hshamloo@kntu.ac.ir
3Ph.D., Dep. of Civil Engineering Univ. of Tehran, Enqelab St., Tehran, Iran. sarvenazghafari@ut.ac.ir

Abstract

정확하고 신뢰할 수 있는 CFD 모델링 결과를 얻는 것은 이러한 시뮬레이션에서 입력의 중요성 때문에 종종 정밀 조사의 대상입니다.

난류 모델링이 RANS(Reynolds-Averaged Navier-Stokes) 방정식을 기반으로 하는 경우 난류 스칼라 전송을 추정하려면 난류 흐름에서 질량 1에 대한 운동량 확산의 비율로 정의되는 난류 슈미트 수(Sct)의 정의가 필요합니다.

그러나 이 매개변수는 난류 흐름의 속성이므로 보편적인 값이 허용되지 않았습니다. 우수 저류지의 수치 연구에서 적절한 Sct를 설정하는 실제 역할은 수력 효율의 평가가 추적자 테스트의 출력 질량 농도를 기반으로 하기 때문에 가장 중요합니다.

본 연구에서는 FLOW-3D를 사용하여 와류형 우수 저류지의 여러 수치 시뮬레이션을 체계적으로 수행했습니다. 다양한 난류 슈미트 수의 범위는 메쉬 감도를 조사하기 위해 다른 수의 계산 셀에 의해 수행된 수치 시뮬레이션에 도입되었습니다.

또한 사용자 정의 또는 자동 계산 값으로 최대 난류 혼합 길이의 영향을 평가했습니다. 이 연구의 결과는 실험 결과와 밀접한 일치를 제공하는 Sct= 0.625와 함께 수리학적 직경의 7%와 동일한 최대 난류 혼합 길이의 일정한 값을 갖는 확립된 수치 모델입니다.

특히 수치적 무차원 RDT 곡선의 피크 값은 극적으로 감소하여 실험 결과와 거의 일치했습니다. 이것은 FLOW-3D가 난류 유동의 와류형 물리학에서 질량 확산도를 적절하게 예측하는 상당한 능력을 가지고 있다는 결론을 내립니다.

– Achieving accurate and reliable CFD modelling results often is the subject of scrutiny because of the importance of the inputs in those simulations. If turbulence modelling is based on Reynolds-Averaged Navier-Stokes (RANS) equations, estimating the turbulent scalar transport requires the definition of the turbulent Schmidt number (Sct), defined as the ratio of momentum diffusivity to mass one in a turbulent flow. However, no universal value has been accepted for this parameter as it is a property of turbulent flows.

The practical role of establishing a suitable Sct in numerical studies of stormwater retention ponds is of the utmost importance because the assessment of the hydraulic efficiency of them is based on output mass concentration of tracer tests. In this study, several numerical simulations of a vortex-type stormwater retention pond were systematically carried out using FLOW-3D. A range of various turbulent Schmidt numbers were introduced in numerical simulations performed by different number of computational cells to investigate mesh sensitivity.

Moreover, the effects of maximum turbulent mixing length as a user-defined or automatically computed value were assessed. The outcome of this study is an established numerical model with a constant value of maximum turbulent mixing length equal to 7% of the hydraulic diameter along with Sct= 0.625 which provides a close agreement with experimental results.

Noticeably, the peak values of numerical dimensionless RDT curves are dramatically decreased, resulted in a close match with experimental results. This concludes that FLOW-3D has a considerable ability to appropriately predict mass diffusivity in vortex-type physics of turbulent flows.

Keywords:

turbulent Schmidt number – maximum turbulent mixing length – CFD – mesh sensitivity – vortex-type
stormwater retention pond – environmental fluid mechanics

Figure 1- The experimental model [17]
Figure 1- The experimental model [17]
Figure 2- Schematic of boundary conditions in the numerical model
Figure 2- Schematic of boundary conditions in the numerical model
Figure 3- Positioning of mesh blocks
Figure 3- Positioning of mesh blocks

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Hydraulic Analysis of Submerged Spillway Flows and Performance Evaluation of Chute Aerator Using CFD Modeling: A Case Study of Mangla Dam Spillway

CFD 모델링을 이용한 침수 배수로 흐름의 수리학적 해석 및 슈트 폭기장치 성능 평가: Mangla Dam 배수로 사례 연구

Hydraulic Analysis of Submerged Spillway Flows and Performance Evaluation of Chute Aerator Using CFD Modeling: A Case Study of Mangla Dam Spillway

Muhammad Kaleem SarwarZohaib NisarGhulam NabiFaraz ul HaqIjaz AhmadMuhammad Masood & Noor Muhammad Khan 

Abstract

대용량 배출구가 있는 수중 여수로는 일반적으로 홍수 처리 및 침전물 세척의 이중 기능을 수행하기 위해 댐 정상 아래에 제공됩니다. 이 방수로를 통과하는 홍수 물은 난류 거동을 나타냅니다. 

게다가 이러한 난류의 수력학적 분석은 어려운 작업입니다. 

따라서 본 연구는 파키스탄 Mangla Dam에 건설된 수중 여수로의 수리학적 거동을 수치해석을 통해 조사하는 것을 목적으로 한다. 또한 다양한 작동 조건에서 화기의 유압 성능을 평가했습니다. 

Mangla Spillway의 흐름을 수치적으로 모델링하는 데 전산 유체 역학 코드 FLOW 3D가 사용되었습니다. 레이놀즈 평균 Navier-Stokes 방정식은 난류 흐름을 수치적으로 모델링하기 위해 FLOW 3D에서 사용됩니다. 

연구 결과에 따르면 개발된 모델은 최대 6%의 허용 오차로 흐름 매개변수를 계산하므로 수중 여수로 흐름을 시뮬레이션할 수 있습니다. 

또한, 여수로 슈트 베드 주변 모델에 의해 계산된 공기 농도는 폭기 장치에 램프를 설치한 후 6% 이상으로 상승한 3%로 개발된 모델도 침수형 폭기 장치의 성능을 평가할 수 있음을 보여주었습니다.

Submerged spillways with large capacity outlets are generally provided below the dam crest to perform the dual functions of flood disposal and sediment flushing. Flood water passing through these spillways exhibits turbulent behavior. Moreover; hydraulic analysis of such turbulent flows is a challenging task. Therefore, the present study aims to use numerical simulations to examine the hydraulic behavior of submerged spillways constructed at Mangla Dam, Pakistan. Besides, the hydraulic performance of aerator was also evaluated at different operating conditions. Computational fluid dynamics code FLOW 3D was used to numerically model the flows of Mangla Spillway. Reynolds-averaged Navier–Stokes equations are used in FLOW 3D to numerically model the turbulent flows. The study results indicated that the developed model can simulate the submerged spillway flows as it computed the flow parameters with an acceptable error of up to 6%. Moreover, air concentration computed by model near spillway chute bed was 3% which raised to more than 6% after the installation of ramp on aerator which showed that developed model is also capable of evaluating the performance of submerged spillway aerator.

Keywords

  • Aerator
  • CFD
  • FLOW 3D
  • Froude number
  • Submerged spillway
  • Fig. 1extended data figure 1Fig. 2extended data figure 2Fig. 3extended data figure 3Fig. 4extended data figure 4Fig. 5extended data figure 5Fig. 6extended data figure 6Fig. 7extended data figure 7Fig. 8

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그림 3. 수중 4차 횡파 영향

Validation of Sloshing Simulations in Narrow Tanks

This case study was contributed by Peter Arnold, Minerva Dynamics.

이 작업의 목적은 FLOW-3D  를 검증하는 것입니다. 밀폐된 좁은 스팬 직사각형 탱크의 출렁거림 문제에 대비하여 탱크의 내부 파동 공명 주기에 가깝거나 같은 주기로 롤 운동을 하여 측면 및 지붕 파동 충격 이벤트가 발생합니다.

탱크는 물이나 해바라기 기름으로 두 가지 다른 수준으로 채워졌고 위의 공간은 공기로 채워졌습니다. 압력 센서는 여러 장소의 벽에 설치되었으며 처음 4개의 출렁이는 기간 동안 기록된 롤 각도와 시간 이력이 있습니다. 오일을 사용하는 경우의 흐름은 레이놀즈 수가 1748인 층류인 반면, 물로 채워진 경우의 흐름은 레이놀즈 수가 97546인 난류입니다. 

CFD 시뮬레이션은 탱크의 고조파 롤 운동을 복제하기 위해 본체력 방법을 사용했으며, 난류 및 공기 압축성을 설명하기 위해 다른 모델링 가정과 함께 그리드 의존성 테스트를 수행했습니다.

The objective of this work is to validate FLOW-3D against a sloshing problem in a sealed narrow span rectangular tank, subjected to roll motion at periods close to or equal to the tank’s internal wave resonance period, such that side and roof wave impact events occur. The tank was filled to two different levels with water or sunflower oil, with the space above filled by air. Pressure sensors were installed in the walls at several places and their time histories, along with the roll angle, recorded for the first four sloshing periods. For the cases using oil, the flow is laminar with a Reynolds number of 1748, while for the cases filled with water the flow is turbulent with a Reynolds number of 97546. The CFD simulations used the body force method to replicate the harmonic roll motion of the tank, while grid dependence tests were performed along with different modelling assumptions to account for turbulence and air compressibility.

Experimental Problem Setup

원래 실험은 Souto-Iglesias 및 Botia-Vera[1]에 의해 수행되었으며 모든 실험 데이터 파일은 문제 설명, 비디오 및 불확실성 분석과 함께 사용할 수 있습니다. 그림 1에 표시된 형상은 길이 900mm, 높이 508mm, 스팬 62mm의 직사각형 탱크로 구성되어 있으며 물이나 해바라기 기름으로 93mm 또는 355.3mm로 채워져 있으므로 4가지 경우가 고려됩니다. 탱크 벽과 같은 높이로 설치된 압력 센서의 위치도 표시됩니다. 탱크 회전 중심은 수평에 대한 회전 각도와 함께 그림 1에 나와 있습니다. 각 실험 실행은 반복성을 평가할 수 있도록 100번 수행되었습니다.

The original experiment was performed by Souto-Iglesias and Botia-Vera [1] and all experimental data files are available along with problem description, videos and an uncertainty analysis. The geometry shown in Fig. 1 consists of a rectangular tank of 900mm length, 508mm height and 62mm span, filled to either 93mm or 355.3 mm with either water or sunflower oil, hence four cases are considered. The locations of the pressure sensors that were installed flush with the tank walls are also shown. The tank rotation center is shown in Fig. 1, along with the rotation angle relative to the horizontal. Each of the experimental runs was performed 100 times to enable their repeatability to be assessed.

Tank dimensions and locations of pressure sensors
Figure 1. Tank dimensions and locations of pressure sensors

Numerical Simulation

문제는 FLOW-3D 내에서 비관성 기준 좌표계 모델을 사용하여 비교적 간단하게 설정할 수 있으며  , 이는 로컬 기준 좌표계의 가속도에 따라 유체에 체력 을 적용합니다. Z축 회전 속도는 탱크의 롤 운동을 시뮬레이션하기 위한 주기 함수로 정의되었으며 음의 수직 방향으로 작용하는 일정한 중력이 가해졌습니다.

메쉬 미세화, 운동량 이류에 대한 수치 근사 순서, 층류 대 난류 모델 및 탱크 내 공기에 대한 세 가지 다른 처리(즉, 일정 압력, 압축성 기체 및 비압축성 기체)와 같은 것을 조사하기 위해 여러 시뮬레이션을 수행했습니다.

93mm 깊이로 채워진 모든 케이스에 대해 압력은 압력 센서 P1에서만 실험 값과 비교되었으며, 355.3mm 깊이로 채워진 모든 케이스에서는 P3 센서의 데이터만 비교되었습니다.

The problem was relatively simple to set up using the non-inertial reference frame model within FLOW-3D, which applies a body force to the fluid depending on the acceleration of the local reference frame. The Z axis rotational velocity was defined as a periodic function to simulate a roll motion of the tank, and a constant gravity force acting in the negative vertical direction was applied.

Multiple simulations were performed to investigate such things as mesh refinement, the numerical approximation order for momentum advection, laminar versus turbulent models and three different treatments for the air in the tank (i.e., constant pressure, compressible gas and incompressible gas).

For all 93mm depth-filled cases, the pressure was compared to the experimental values at pressure sensor P1 only, while for all 355.3mm depth-filled cases, only data at the P3 sensor was compared.

Results

P1에서 측정된 측면 워터 슬로싱에 대한 메쉬 해상도의 영향은 그림 2에서 볼 수 있습니다. 피크 값 예측 측면에서 특별한 편향을 보이지 않습니다. 모든 측면 사례에서 초기 피크 직후의 압력은 시뮬레이션에서 일관되게 과대 평가되었습니다. 모든 메쉬는 피크의 타이밍 측면에서 우수한 일치를 보입니다. 100회 실행에서 보고된 실험 시간 기록은 평균 값에 가장 가까운 최고 압력을 가진 기록입니다.

The effect of mesh resolution on lateral water sloshing measured at P1 is seen in Fig. 2. It shows no particular bias in terms of the prediction of peak values. In all the Lateral cases, the pressures immediately after the initial peaks are consistently over estimated in the simulations. All meshes have excellent agreement in terms of the timing of the peaks. The experimental time histories reported from the 100 runs made are those with peak pressures closest to the average values.

Lateral water case
Figure 2. Tank dimensions and locations of pressure sensors

실험 결과의 반복성은 Souto-Iglesias & Elkin Botia-Vera[1]에 의해 각 테스트를 100번 실행하고 처음 4개의 피크 압력의 평균 및 표준 편차를 측정하여 평가했습니다. CFD 실행이 다른 실험 실행으로 간주되는 경우 오류 막대 내에 있을 확률이 95%입니다. 그러나 CFD 결과의 16개 피크 압력 중 9개만 실험 결과의 2 표준 편차 내에 있으므로 CFD 모델이 실험을 대표하지 않거나 피크 압력이 정규 분포를 따르지 않는다는 결론을 내려야 합니다.

어쨌든 표준 편차는 피크 자체에 비해 상당히 크며, 수성 케이스와 측면 오일의 비율이 가장 작은 피크 값에 대한 표준 편차의 비율이 가장 큰 것으로 나타났습니다. 이러한 결과는 그림 1과 2에서 볼 수 있는 벽 충격 역학의 복잡성을 고려할 때 그리 놀라운 일이 아닙니다. 3,4.

The repeatability of the experimental results was assessed by Souto-Iglesias & Elkin Botia-Vera [1] running each test 100 times and measuring the average and standard deviation of the first four peak pressures. If a CFD run is considered to be another experimental run there is a 95% chance it will lie within the error bars. However, only nine of the 16 peak pressures from the CFD results fall within two standard deviations of the experimental results, so we must conclude that either the CFD model is not representative of the experiment or that the peak pressures are not normally distributed.

In any event, the standard deviations are quite large compared to the peaks themselves, with the largest ratio of standard deviation to peak values occurring for the water-based cases and the lateral oil having the smallest ratio. These results are perhaps not too surprising when one considers the complexity of the wall impact dynamics as seen in Figs. 3,4.

Lateral Wave Impact in Water
Figure 3. 4th Lateral Wave Impact in Water
Wave Impact of Water on Roof
Figure 4. 4th Wave Impact of Water on Roof

Conclusions

좁은 탱크 슬로싱 문제의 네 가지 구성은 자유 표면 흐름을 위해 설계된 상용 CFD 코드를 사용하여 수치적으로 시뮬레이션되었습니다. 대략 2 X 10 3  및 1 X 10 5 의 Reynolds 수에 해당하는 두 가지 다른 유체  와 두 가지 유체 깊이가 네 가지 경우를 정의하는 데 사용되었습니다. 4가지 경우 모두에 대해 메쉬 셀 크기 독립성 테스트를 수행했지만 메쉬 해상도가 증가함에 따라 실험 결과에 대해 약한 수렴만 발견되었습니다. 조사는 또한 두 가지 다른 운동량 이류 수치 차분 계획을 테스트했으며 두 번째 방법을 사용하여 더 가까운 일치를 발견했습니다 1차 체계를 사용하는 것보다 차수 단조성 보존 체계. 기본 층류 흐름을 포함한 세 가지 난류 모델이 테스트되었지만 더 낮은 계산 비용으로 인해 층류 이외의 모델에 대한 선호도가 발견되지 않았습니다. 실험 데이터와 공기 감소 일치의 압축성을 포함하여 그 이유는 불분명합니다.

실험 압력 프로브 시간 이력 데이터 세트에는 100회 반복 테스트에서 파생된 각 압력 피크에 대해 100개의 값이 포함되어 있으므로 CFD 시뮬레이션과의 일치의 통계적 유의성을 조사할 수 있었습니다. 수치 시뮬레이션과 실험 모두 출렁이는 파동 충격에 해당하는 매우 가파른 압력 펄스를 발생시켰고 실험 결과는 피크 값에서 높은 정도의 자연적 변동성을 갖는 것으로 나타났습니다. CFD 시뮬레이션의 감도 테스트(예: 약간 다른 초기 시작 조건 사용)는 공식적으로 수행되지 않았지만 수치 솔루션은 또한 다른 메쉬, 차분 체계 및 난류 모델,

모든 경우에 압력 피크가 발생하는 수치해의 타이밍은 매우 정확함을 알 수 있었다. 그러나 가장 난이도가 낮은 Lateral Oil의 경우에도 압력 피크와 바로 뒤따르는 압력 값이 과대 평가되어 수치 모델링의 단점이 나타났습니다. 실험적 피크 압력 변동성을 고려할 때 CFD 생성 값은 CFD 솔루션이 통계적 유의성을 나타내기 위해 필요한 15개 이상이 아니라 16개 피크 중 9개에서 2개의 표준편차 한계 내에 떨어졌습니다. 실험을 대표했다. 이것은 피크가 정규 분포를 따르지 않거나 CFD 모델이 피크를 예측하는 데 어떤 식으로든 결함이 있음을 나타냅니다.

Four configurations of a narrow tank sloshing problem were numerically simulated using a commercial CFD code designed for free surface flow. Two different fluids corresponding to Reynolds numbers of approximately 2 X 103 and 1 X 105 and two fluid depths were used to define the four cases. Mesh cell size independence tests were conducted for all four cases, but only a weak convergence towards the experimental results with increasing mesh resolution was found. The investigation also tested two different momentum advection numerical differencing schemes and found closer agreement using the 2nd order monotonicity preserving scheme than by using a first order scheme. Three turbulence models, including the default laminar flow, were tested but no preference was found for any model other than the laminar by virtue of its lower computational cost. Including the compressibility of the air-reduced agreement with the experimental data, the reasons for this are unclear.

The experimental pressure probe time history data sets included 100 values for each of the pressure peaks derived from 100 repeat tests, and thus we were able to examine the statistical significance of the agreement with the CFD simulations. Both the numerical simulations and the experiments gave rise to very steep pressure pulses corresponding to the sloshing wave impacts, and the experimental results were found to have a high degree of natural variability in the peak values. Although sensitivity tests of the CFD simulations (using, for example, slightly different initial starting conditions) were not formally conducted, the numerical solutions also showed a high degree of variability in the pressure peak magnitudes resulting from the use of different meshes, differencing schemes and turbulence models, which could be considered to show that the numerical solution also had a high degree of natural variability.

In all cases, the numerical solutions’ timing of the occurrence of the pressure peaks were found to be very accurate. However, even for the least challenging Lateral Oil case, the pressure peaks and the immediately following pressure values were overestimated, which indicated a shortcoming in the numerical modelling. When the experimental peak pressure variability was taken into account, the CFD-generated values fell inside the two Standard Deviation margin in nine of the 16 peaks rather than the 15 or more that would be required to show statistical significance in the sense that the CFD solution was representative of the experiment. This indicates that either the peaks are not normally distributed and/or the CFD model is in some way deficient at predicting them. Further work is required to establish how the peak pressures are distributed and/or to establish the physical reasons why the CFD model is overestimating the pressure peaks for even the least challenging Lateral Oil configuration.

References

  1. Spheric Benchmark Test Case, Sloshing Wave Impact Problem, Antonio Souto-Iglesias & Elkin Botia-Vera, https://wiki.manchester.ac.uk/spheric/index.php/Test10
  2. Peregrine DH (1993). Water-wave impact on walls. Annual Review of Fluid Mechanics. Vol 35, pp 23-43.

Editor’s Note

The complete document from which this note was extracted and the related data and input files are available on our Users Site. Readers are encouraged to read the original validation to get a full appreciation of the detail in this work investigating comparisons between simulation and experimental data. This study is especially noteworthy since it deals with highly non-linear sloshing of fluids interacting with the boundaries of a confining tank.

With regard to the author’s conclusions, it should be mentioned that the over prediction of fluid impact pressures in simulations could be the result of not allowing for sufficient compressibility effects in the liquids. For instance, in Fig. 3, it appears that there has been some air entrained in the liquid near the side wall. Also, negative pressures (i.e., below atmospheric) recorded experimentally might result from liquid drops remaining on the pressure sensors after the main body of liquid has drained away. Such details, which may be hard to quantify, only emphasize the difficulties involved in undertaking detailed validation studies. The author is commended for his excellent work.

Fig. 6. Configuration of Johnson (1958) hydraulic experiment.

전체 수심 범위에서 선박 파고에 대한 방정식

Equation for ship wave crests in the entire range of water depths

Byeong Wook Lee a
, Changhoon Lee b,
*a Coastal Development and Ocean Energy Research Center, Korea Institute of Ocean Science & Technology, 385 Haeyang-ro, Busan, 49111, Republic of Korea
b Department of Civil and Environmental Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 05006, Republic of Korea

ABSTRACT

An equation for ship wave crests y/x in the entire range of water depths is developed using the linear dispersion relation. In deep water, the developed equation is reduced to the equation of Kelvin (1906). The locations of ship wave crests in the x – and y -directions are obtained using a dimensionless constant C. The wave ray angle θc at the cusp locus is determined using the condition that θc is maximal at the cusp locus and the cusp locus angle is determined as αc=−tan−1(y/x)max. Numerical experiments are conducted using the FLOW-3D to simulate ship wave propagation. The cusp locus angles of the FLOW-3D are similar to both those of the present theory and Havelock (1908) theory in the entire range of the Froude number. Both the present theory and the FLOW-3D yield that, with the increase of ship speed, the Froude number increases and does the wavelength. For the Froude number equal to or greater than unity, the wavelength becomes infinitely large and the transverse waves disappear. The wavelengths of the FLOW-3D are slightly smaller than those of the present theory because the FLOW-3D considers the decrease of wavelength due to energy dissipation which happens because of viscosity of water and turbulence of high-speed particle velocities.

Fig. 6. Configuration of Johnson (1958) hydraulic experiment.
Fig. 6. Configuration of Johnson (1958) hydraulic experiment.
Fig. 8. Comparison of ship wave crest patterns: (a) Fr ¼ 0:66 (Us ¼ 6:5m=s,  kh � 0:724π), (b) Fr ¼ 0:86 (Us ¼ 8:5m=s, kh � 0:342π), (c) Fr ¼ 1:21 (Us ¼ 12:0m=s, kh � 0:003π). Line definition: red solid line ¼ present theory; yellow  dashed line ¼ Kelvin theory; white dot ¼ FLOW-3D solution. (For interpretation  of the references to colour in this figure legend, the reader is referred to the  Web version of this article.)
Fig. 8. Comparison of ship wave crest patterns: (a) Fr ¼ 0:66 (Us ¼ 6:5m=s, kh >= 0:724π), (b) Fr ¼ 0:86 (Us ¼ 8:5m=s, kh >= 0:342π), (c) Fr ¼ 1:21 (Us ¼ 12:0m=s, kh >= 0:003π). Line definition: red solid line ¼ present theory; yellow dashed line ¼ Kelvin theory; white dot ¼ FLOW-3D solution. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Keywords

Ship wave crests
Cusp locus angle
Entire range of water depths
Theoretical solution
Numerical experiment

References

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of ship-borne waves – solutions from a Boussinesq-type model. Cost Eng. 127,
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disturbance in a shallow channel of finite width. J. Fluid Mech. 169, 275–292.
Fang, M.-C., Yang, R.-Y., Shugan, I.V., 2011. Kelvin ship wake in the wind waves field
and on the finite sea depth. J. Mech. 27 (1), 71–77.
Havelock, T.H., 1908. The propagation of groups of waves in dispersive media with
application to waves on water produced by a travelling disturbance. Proc. Royal Soc.
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Hennings, I., Romeiser, R., Alpers, W., Viola, A., 1999. Radar imaging of Kelvin arms of
ship wakes. Int. J. Remote Sens. 20 (13), 2519–2543.
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Fig. 11. Velocity vectors along x-direction through the center of the box culvert for B0, B30, B50, and B70 respectively.

Numerical investigation of scour characteristics downstream of blocked culverts

막힌 암거 하류의 세굴 특성 수치 조사

NesreenTahabMaged M.El-FekyaAtef A.El-SaiadaIsmailFathya
aDepartment of Water and Water Structures Engineering, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt
bLab Manager, Faculty of Engineering, Zagazig University, Zagazig 44519, Egypt

Abstract

횡단 구조물을 통한 막힘은 안정성을 위협하는 위험한 문제 중 하나입니다. 암거의 막힘 형상 및 하류 세굴 특성에 미치는 영향에 관한 연구는 거의 없습니다.

이 연구의 목적은 수면과 세굴 모두에서 상자 암거를 통한 막힘의 작용을 수치적으로 논의하는 것입니다. 이를 위해 FLOW 3D v11.1.0을 사용하여 퇴적물 수송 모델을 조사했습니다.

상자 암거를 통한 다양한 차단 비율이 연구되었습니다. FLOW 3D 모델은 실험 데이터로 보정되었습니다. 결과는 FLOW 3D 프로그램이 세굴 다운스트림 상자 암거를 정확하게 시뮬레이션할 수 있음을 나타냅니다.

막힌 경우에 대한 속도 분포, 최대 세굴 깊이 및 수심을 플롯하고 비차단된 사례(기본 사례)와 비교했습니다.

그 결과 암거 높이의 70% 차단율은 상류의 수심을 암거 높이의 2.3배 증가시키고 평균 유속은 기본 경우보다 3배 더 증가시키는 것으로 입증되었다. 막힘 비율의 함수로 상대 최대 세굴 깊이를 추정하는 방정식이 만들어졌습니다.

Blockage through crossing structures is one of the dangerous problems that threaten its stability. There are few researches concerned with blockage shape in culverts and its effect on characteristics of scour downstream it.

The study’s purpose is to discuss the action of blockage through box culvert on both water surface and scour numerically. A sediment transport model has been investigated for this purpose using FLOW 3D v11.1.0. Different ratios of blockage through box culvert have been studied. The FLOW 3D model was calibrated with experimental data.

The results present that the FLOW 3D program was capable to simulate accurately the scour downstream box culvert. The velocity distribution, maximum scour depth and water depths for blocked cases have been plotted and compared with the non-blocked case (base case).

The results proved that the blockage ratio 70% of culvert height makes the water depth upstream increases by 2.3 times of culvert height and mean velocity increases by 3 times more than in the base case. An equation has been created to estimate the relative maximum scour depth as a function of blockage ratio.

1. Introduction

Local scour is the removal of granular bed material by the action of hydrodynamic forces. As the depth of scour hole increases, the stability of the foundation of the structure may be endangered, with a consequent risk of damage and failure [1]. So the prediction and control of scour is considered to be very important for protecting the water structures from failure. Most previous studies were designed to study the different factors that impact on scour and their relationship with scour hole dimensions like fluid characteristics, flow conditions, bed properties, and culvert geometry. Many previous researches studied the effect of flow rate on scour hole by information Froude number or modified Froude number [2][3][4][5][6]. Cesar Mendoza [6] found a good correlation between the scour depth and the discharge Intensity (Qg−.5D−2.5). Breusers and Raudkiv [7] used shear velocity in the outlet-scour prediction procedure. Ali and Lim [8] used the densimetric Froude number in estimation of the scour depth [1][8][9][10][11][12][13][14]. “The densimetric Froude number presents the ratio of the tractive force on sediment particle to the submerged specific weight of the sediment” [15](1)Fd=uρsρ-1gD50

Ali and Lim [8] pointed to the consequence of tailwater depth on scour behavior [1][2][8][13]. Abida and Townsend [2] indicated that the maximum depth of local scour downstream culvert was varying with the tailwater depth in three ways: first, for very shallow tailwater depths, local scouring decreases with a decrease in tailwater depth; second, when the ratio of tailwater depth to culvert height ranged between 0.2 and 0.7, the scour depth increases with decreasing tailwater depth; and third for a submerged outlet condition. The tailwater depth has only a marginal effect on the maximum depth of scour [2]. Ruff et al. [16] observed that for materials having similar mean grain sizes (d50) but different standard deviations (σ). As (σ) increased, the maximum scour hole depth decreased. Abt et al. [4] mentioned to role of soil type of maximum scour depth. It was noticed that local scour was more dangerous for uniform sands than for well-graded mixtures [1][2][4][9][17][18]. Abt et al [3][19] studied the culvert shape effect on scour hole. The results evidenced that the culvert shape has a limited effect on outlet scour. Under equivalent discharge conditions, it was noted that a square culvert with height equal to the diameter of a circular culvert would reduce scour [16][20]. The scour hole dimension was also effected by the culvert slope. Abt et al. [3][21] showed that the culvert slope is a key element in estimating the culvert flow velocity, the discharge capacity, and sediment transport capability. Abt et al. [21][22] tested experimentally culvert drop height effect on maximum scour depth. It was observed that as the drop height was increasing, the depth of scour was also increasing. From the previous studies, it could have noticed that the most scour prediction formula downstream unblocked culvert was the function of densimetric Froude number, soil properties (d50, σ), tailwater depth and culvert opening size. Blockage is the phenomenon of plugging water structures due to the movement of water flow loaded with sediment and debris. Water structures blockage has a bad effect on water flow where it causes increasing of upstream water level that may cause flooding around the structure and increase of scour rate downstream structures [23][24]. The blockage phenomenon through was studied experimentally and numerical [15][25][26][27][28][29][30][31][32][33]. Jaeger and Lucke [33] studied the debris transport behavior in a natural channel in Australia. Froude number scale model of an existing culvert was used. It was noticed that through rainfall event, the mobility of debris was impressed by stream shape (depth and width). The condition of the vegetation (size and quantities) through the catchment area was the main factor in debris transport. Rigby et al. [26] reported that steep slope was increasing the ability to mobilize debris that form field data of blocked culverts and bridges during a storm in Wollongong city.

Streftaris et al. [32] studied the probability of screen blockage by debris at trash screens through a numerical model to relate between the blockage probability and nature of the area around. Recently, many commercial computational fluid programs (CFD) such as SSIIM, Fluent, and FLOW 3D are used in the analysis of the scour process. Scour and sediment transport numerical model need to validate by using experimental data or field data [34][35][36][37][38]. Epely-Chauvin et al. [36] investigated numerically the effect of a series of parallel spur diked. The experimental data were compared by SSIIM and FLOW 3D program. It was found that the accuracy of calibrated FLOW 3D model was better than SSIIM model. Nielsen et al. [35] used the physical model and FLOW 3D model to analyze the scour process around the pile. The soil around the pile was uniform coarse stones in the physical models that were simulated by regular spheres, porous media, and a mixture of them. The calibrated porous media model can be used to determine the bed shear stress. In partially blocked culverts, there aren’t many studies that explain the blockage impact on scour dimensions. Sorourian et al. [14][15] studied the effect of inlet partial blockage on scour characteristics downstream box culvert. It resulted that the partial blockage at the culvert inlet could be the main factor in estimating the depth of scour. So, this study is aiming to investigate the effects of blockage through a box culvert on flow and scour characteristics by different blockage ratios and compares the results with a non-blocked case. Create a dimensionless equation relates the blockage ratio of the culvert with scour characteristics downstream culvert.

2. Experimental data

The experimental work of the study was conducted in the Hydraulics and Water Engineering Laboratory, Faculty of Engineering, Zagazig University, Egypt. The flume had a rectangular cross-section of 66 cm width, 65.5 cm depth, and 16.2 m long. A rectangular culvert was built with 0.2 m width, 0.2 m height and 3.00 m long with θ = 25° gradually outlet and 0.8 m fixed apron. The model was located on the mid-point of the channel. The sediment part was extended for a distance 2.20 m with 0.66 m width and 0.20 m depth of coarse sand with specific weight 1.60 kg/cm3, d50 = 2.75 mm and σ (d90/d50) = 1.50. The particle size distribution was as shown in Fig. 1. The experimental model was tested for different inlet flow (Q) of 25, 30, 34, 40 l/s for different submerged ratio (S) of 1.25, 1.50, 1.75.

3. Dimensional analysis

A dimensional analysis has been used to reduce the number of variables which affecting on the scour pattern downstream partial blocked culvert. The main factors affecting the maximum scour depth are:(2)ds=f(b.h.L.hb.lb.Q.ud.hu.hd.D50.ρ.ρs.g.ls.dd.ld)

Fig. 2 shows a definition sketch of the experimental model. The maximum scour depth can be written in a dimensionless form as:(3)dsh=f(B.Fd.S)where the ds/h is the relative maximum scour depth.

4. Numerical work

The FLOW 3D is (CFD) program used by many researchers and appeared high accuracy in solving hydrodynamic and sediment transport models in the three dimensions. Numerical simulation with FLOW 3D was performed to study the impacts of blockage ratio through box culvert on shear stress, velocity distribution and the sediment transport in terms of the hydrodynamic features (water surface, velocity and shear stress) and morphological parameters (scour depth and sizes) conditions in accurately and efficiently. The renormalization group (RNG) turbulence model was selected due to its high ability to predict the velocity profiles and turbulent kinetic energy for the flow through culvert [39]. The one-fluid incompressible mode was used to simulate the water surface. Volume of fluid (VOF) method was employed in FLOW 3D to tracks a liquid interface through arbitrary deformations and apply the correct boundary conditions at the interface [40].1.

Governing equations

Three-dimensional Reynolds-averaged Navier Stokes (RANS) equation was applied for incompressible viscous fluid motion. The continuity equation is as following:(4)VF∂ρ∂t+∂∂xρuAx+∂∂yρvAy+∂∂zρwAz=RDIF(5)∂u∂t+1VFuAx∂u∂x+vAy∂u∂y+ωAz∂u∂z=-1ρ∂P∂x+Gx+fx(6)∂v∂t+1VFuAx∂v∂x+vAy∂v∂y+ωAz∂v∂z=-1ρ∂P∂y+Gy+fy(7)∂ω∂t+1VFuAx∂ω∂x+vAy∂ω∂y+ωAz∂ω∂z=-1ρ∂P∂z+Gz+fz

ρ is the fluid density,

VF is the volume fraction,

(x,y,z) is the Cartesian coordinates,

(u,v,w) are the velocity components,

(Ax,Ay,Az) are the area fractions and

RDIF is the turbulent diffusion.

P is the average hydrodynamic pressure,

(Gx, Gy, Gz) are the body accelerations and

(fx, fy, fz) are the viscous accelerations.

The motion of sediment transport (suspended, settling, entrainment, bed load) is estimated by predicting the erosion, advection and deposition process as presented in [41].

The critical shields parameter is (θcr) is defined as the critical shear stress τcr at which sediments begin to move on a flat and horizontal bed [41]:(8)θcr=τcrgd50(ρs-ρ)

The Soulsby–Whitehouse [42] is used to predict the critical shields parameter as:(9)θcr=0.31+1.2d∗+0.0551-e(-0.02d∗)(10)d∗=d50g(Gs-1ν3where:

d* is the dimensionless grain size

Gs is specific weight (Gs = ρs/ρ)

The entrainment coefficient (0.005) was used to scale the scour rates and fit the experimental data. The settling velocity controls the Soulsby deposition equation. The volumetric sediment transport rate per width of the bed is calculated using Van Rijn [43].2.

Meshing and geometry of model

After many trials, it was found that the uniform cell size with 0.03 m cell size is the closest to the experimental results and takes less time. As shown in Fig. 3. In x-direction, the total model length in this direction is 700 cm with mesh planes at −100, 0, 300, 380 and 600 cm respectively from the origin point, in y-direction, the total model length in this direction is 66 cm at distances 0, 23, 43 and 66 cm respectively from the origin point. In z-direction, the total model length in this direction is 120 cm. with mesh planes at −20, 0, 20 and 100 cm respectively.3.

Boundary condition

As shown in Fig. 4, the boundary conditions of the model have been defined to simulate the experimental flow conditions accurately. The upstream boundary was defined as the volume flow rate with a different flow rate. The downstream boundary was defined as specific pressure with different fluid elevation. Both of the right side, the left side, and the bottom boundary were defined as a wall. The top boundary defined as specified pressure with pressure value equals zero.

5. Validation of experimental results and numerical results

The experimental results investigated the flow and scour characteristics downstream culvert due to different flow conditions. The measured value of maximum scour depth is compared with the simulated depth from FLOW 3D model as shown in Fig. 5. The scour results show that the simulated results from the numerical model is quite close to the experimental results with an average error of 3.6%. The water depths in numerical model results is so close to the experimental results as shown in Fig. 6 where the experiment and numerical results are compared at different submerged ratios and flow rates. The results appear maximum error percentage in water depths upstream and downstream the culvert is about 2.37%. This indicated that the FLOW 3D is efficient for the prediction of maximum scour depth and the flow depths downstream box culvert.

6. Computation time

The run time was chosen according to reaching to the stability limit. Hydraulic stability was achieved after 50 s, where the scour development may still go on. For run 1, the numerical simulation was run for 1000 s as shown in Fig. 7 where it mostly reached to scour stability at 800 s. The simulation time was taken 500 s at about 95% of scour stability.

7. Analysis and discussions

Fig. 8 shows the study sections where sec 1 represents to upstream section, sec2 represents to inside section and sec3 represents to downstream stream section. Table 1 indicates the scour hole dimensions at different blockage case. The symbol (B) represents to blockage and the number points to blockage ratio. B0 case signifies to the non-blocked case, B30 is that blockage height is 30% to the culvert height and so on.

Table 1. The scour results of different blockage ratio.

Casehb cmB = hb/hQ lit/sSFdd50 mmds/h measuredls/hdd/hld/hds/h estimated
B000351.261.692.50.581.500.275.000.46
B3060.30351.261.682.50.481.250.274.250.40
B50100.50351.221.742.50.451.100.244.000.37
B70140.70351.231.732.50.431.500.165.500.33

7.1. Scour hole geometry

The scour hole geometry mainly depends on the properties of soil of the bed downstream the fixed apron. From Table 1, the results show that the maximum scour depth in B0 case is about 0.58 of culvert height while the maximum deposition in B0 is 0.27 culvert height. There is a symmetric scour hole as shown in Fig. 9 in B0 case. An asymmetric scour hole is created in B50 and B70 due to turbulences that causes the deviation of the jet direction from the center of the flume where appear in Fig. 11 and Fig. 19.

7.2. Flow water surface

Fig. 10 presents the relative free surface water (hw/h) along the x-direction at center of the box culvert. From the mention Figure, it is easy to release the effect of different blockage ratios. The upstream water level rises by increasing the blockage ratio. Increasing upstream water level may cause flooding over the banks of the waterway. In the 70% blockage case, the upstream water level rises to 2.3 times of culvert height more than the non-blocked case at the same discharge and submerged ratio. The water surface profile shows an increase in water level upstream the culvert due to a decrease in transverse velocity. Because of decreasing velocity downstream culvert, there is an increase in water level before it reaches its uniform depth.

7.3. Velocity vectors

Scour downstream hydraulic structures mainly affects by velocities distribution and bed shear stress. Fig. 11 shows the velocity vectors and their magnitude in xz plane at the same flow conditions. The difference in the upstream water level due to the different blockage ratios is so clear. The maximum water level is in B70 and the minimum level is in B0. The inlet mean velocity value is about 0.88 m/s in B0 increases to 2.86 m/s in B70. As the blockage ratio increases, the inlet velocity increases. The outlet velocity in B0 case makes downward jet causes scour hole just after the fixed apron in the middle of the bed while the blockage causes upward water flow that appears clearly in B70. The upward jet decreases the scour depth to 0.13 culvert height less than B0 case. After the scour hole, the velocity decreases and the flow becomes uniform.

7.4. Velocity distribution

Fig. 12 represents flow velocity (Vx) distribution along the vertical depth (z/hu) upstream the inlet for the different blockage ratios at the same flow conditions. From the Figure, the maximum velocity creates closed to bed in B0 while in blocked case, the maximum horizontal velocity creates at 0.30 of relative vertical depth (z/hu). Fig. 13 shows the (Vz) distribution along the vertical depth (z/hu) upstream culvert at sec 1. From the mentioned Figure, it is easy to note that the maximum vertical is in B70 which appears that as the blockage ratio increases the vertical ratio also increases. In the non-blocked case. The vertical velocity (Vz) is maximum at (z/hu) equals 0.64. At the end of the fixed apron (sec 3), the horizontal velocity (Vx) is slowly increasing to reach the maximum value closed to bed in B0 and B30 while the maximum horizontal velocity occurs near to the top surface in B50 and B70 as shown in Fig. 14. The vertical velocity component along the vertical depth (z/hd) is presented in Fig. 15. The vertical velocity (Vz) is maximum in B0 at vertical depth (z/hd) 0.3 with value 0.45 m/s downward. Figs. 16 and 17 observe velocity components (Vx, Vz) along the vertical depth just after the end of blockage length at the centerline of the culvert barrel. It could be noticed the uniform velocity distribution in B0 case with horizontal velocity (Vx) closed to 1.0 m/s and vertical velocity closed to zero. In the blocked case, the maximum horizontal velocity occurs in depth more than the blockage height.

7.5. Bed velocity distribution

Fig. 18 presents the x-velocity vectors at 1.5 cm above the bed for different blockage ratios from the velocity vectors distribution and magnitude, it is easy to realize the position of the scour hole and deposition region. In B0 and B30, the flow is symmetric so that the scour hole is created around the centerline of flow while in B50 and B70 cases, the flow is asymmetric and the scour hole creates in the right of flow direction in B50. The maximum scour depth is found in the left of flow direction in B70 case where the high velocity region is found.

8. Maximum scour depth prediction

Regression analysis is used to estimate maximum scour depth downstream box culvert for different ratios of blockage by correlating the maximum relative scour by other variables that affect on it in one formula. An equation is developed to predict maximum scour depth for blocked and non-blocked. As shown in the equation below, the relative maximum scour depth(ds/hd) is a function of densimetric Froude number (Fd), blockage ratio (B) and submerged ratio (S)(11)dsh=0.56Fd-0.20B+0.45S-1.05

In this equation the coefficient of correlation (R2) is 0.82 with standard error equals 0·08. The developed equation is valid for Fd = [0.9 to 2.10] and submerged ratio (S) ≥ 1.00. Fig. 19 shows the comparison between relative maximum scour depths (ds/h) measured and estimated for different blockage ratios. Fig. 20 clears the comparison between residuals and ds/h estimated for the present study. From these figures, it could be noticed that there is a good agreement between the measured and estimated relative scour depth.

9. Comparison with previous scour equations

Many previous scour formulae have been produced for calculation the maximum scour depth downstream non-blockage culvert. These equations have been included the effect of flow regime, culvert shape, soil properties and the flow rate on maximum scour depth. Two of previous experimental studies data have been chosen to be compared with the present study results in non-blocked study data. Table 2 shows comparison of culvert shape, densmetric Froude number, median particle size and scour equations for these previous studies. By applying the present study data in these studies scour formula as shown in Fig. 21, it could be noticed that there are a good agreement between present formula results and others empirical equations results. Where that Lim [44] and Abt [4] are so closed to the present study data.

Table 2. Comparison of some previous scour formula.

ResearchersFdCulvert shaped50(mm)Proposed equationSubmerged ratio
Present study0.9–2.11square2.75dsh=0.56Fd-0.20B+0.45S-1.051.25–1.75
Lim [44]1–10Circular1.65dsh=0.45Fd0.47
Abt [4]Fd ≥ 1Circular0.22–7.34-dsh=3.67Fd0.57∗D500.4∗σ-0.4

10. Conclusions

The present study has shown that the FLOW 3D model can accurately simulate water surface and the scour hole characteristics downstream the box culvert with error percentage in water depths does not exceed 2.37%. Velocities distribution through and outlets culvert barrel helped on understanding the scour hole shape.

The blockage through culvert had caused of increasing of water surface upstream structure where the upstream water level in B70 was 2.3 of culvert height more than non-blocked case at the same discharge that could be dangerous on the stability of roads above. The depth averaged velocity through culvert barrel increased by 3 times its value in non-blocked case.

On the other hand, blockage through culvert had a limited effect on the maximum scour depth. The little effect of blockage on maximum scour depth could be noticed in Fig. 11. From this Figure, it could be noted that the residual part of culvert barrel after the blockage part had made turbulences. These turbulences caused the deviation of the flow resulting in the formation of asymmetric scour hole on the side of channel. This not only but in B70 the blockage height caused upward jet which made a wide far scour hole as cleared from the results in Table 1.

An empirical equation was developed from the results to estimate the maximum scour depth relative to culvert height function of blockage ratio (B), submerged ratio (S), and densimetric Froude number (Fd). The equation results was compared with some scour formulas at the same densimetric Froude number rang where the present study results was in between the other equations results as shown in Fig. 21.

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.

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