Concrete 3D Printing

Computational fluid dynamics modelling and experimental analysis of reinforcement bar integration in 3D concrete printing

3D 콘크리트 프린팅에서 철근 통합에 대한 전산 유체 역학 모델링 및 실험적 분석

Md Tusher Mollah, Raphaël Comminal, Wilson Ricardo Leal da Silva, Berin Šeta, Jon Spangenberg

Abstract


A challenge for 3D Concrete Printing is to incorporate reinforcement bars without compromising the concrete-rebar bonding. In this paper, a Computational Fluid Dynamics (CFD) model is used to analyze the deposition of concrete around pre-installed rebars. The concrete is modelled with a yield-stress dependent elasto-viscoplastic constitutive model. The simulated cross-sections of the deposited layers are compared with experiments under different configurations and rebar sizes, and found capable of capturing the air void formation with high accuracy. This proves model robustness and provides a tool for running digital experiments prior to full-scale tests. Additionally, the model is employed to conduct a parametric study under three different rebar-configurations: i) no-rebar; ii) horizontal rebar; and iii) cross-shaped (horizontal and vertical) rebars. The results illustrate that air voids can be eliminated in all investigated cases by changing the toolpath, process parameters, and rebar joint geometry, which emphasizes the great potential of the digital model.

Keywords


3D Concrete Printing (3DCP); Reinforcement bars (rebars); Computational Fluid Dynamics (CFD); Multilayer deposition; Air voids

1. Introduction


3D Concrete Printing (3DCP) [1] is an extrusion-based automated construction process that belongs to Digital Fabrication with Concrete (DFC) [2,3]. The 3DCP offers high-quality built-structures with customizable structural design in a cost- and time-efficient manner [[4], [5], [6], [7]]. Structures in 3DCP are fabricated in a layer-by-layer approach, where a concrete extrusion nozzle is controlled by a robotic arm, cylindrical robot, gantry system, or delta system [[8], [9], [10], [11]]. Despite the enormous potential of 3DCP, one of its crucial limitations is the integration of reinforcement for the production of load-bearing structures.
Most structural applications require the use of reinforcement to withstand tensile forces and introduce structural ductility [[12], [13], [14], [15]]. However, the introduction of reinforcement with 3DCP has never been an easy task, and difficulties were recognized at early stages of the technology [4] and various design solutions have been tested in practice to either circumvent the need for reinforcement or integrate reinforcement after the concrete is printed [[16], [17], [18], [19], [20]]. As a result, several reinforcement techniques have been proposed, such as bar reinforcement [21], micro-cable reinforcement [22,23], fiber reinforcement into the cementitious material [[24], [25], [26]], steel reinforcement using robotic arc welding [27,28], and in-process mesh reinforcement [29]. For comprehensive details on the reinforcement strategies, refer to [30]. Nevertheless, these reinforcement strategies are still rudimentary in many instances.
This study focuses on bar reinforcement methods, where rebars are integrated with freshly deposited cementitious material. A few approaches can be found in the literature, for example, penetration of vertical bars through multiple printed layers [31,32], placement of horizontal bars into a printed layer along the printing direction and then covered by the next layer on top [33,34], and depositing around pre-installed bi-directional rebars [35]. However, in most approaches, the bonding between the rebar and concrete was compromised by the air void around the rebar [21,36]. To overcome this constraint, a large amount of trial and error is required, which is costly and time-consuming.
An approach to mitigate extensive experimental campaigns is to apply numerical models. In the context of 3D printing technologies, like Fused Filament Fabrication (FFF), Robocasting, and 3DCP, CFD modelling has been found to be very beneficial [[37], [38], [39], [40], [41], [42], [43], [44]]. The morphology of the deposited strands in FFF was studied by Comminal et al. [45]. Furthermore, Serdeczny et al. [46] addressed how to reduce the porosities and enhance the bonding between subsequent layers. Mollah et al. [[47], [48], [49]] studied ways to minimize the deformation and thereby stabilize layers printed by Robocasting, while for 3DCP, the geometrical shapes of the single- and multiple-deposited layers have been investigated in detail in [[50], [51], [52]].
This paper uses the CFD model and extends the preliminary results recently published in [53]. The model uses elasto-viscoplastic constitutive equations to approximate the rheology of the concrete. The CFD model is validated by comparison with a number of experiments, and the model is subsequently exploited to make an in-depth analysis of air void formation between rebars and concrete using the cross-sections of the deposited part and the calculated volume fraction of air voids. Different material properties, such as yield stress and plastic viscosity, and processing parameters, like the rebar diameter, nozzle-rebar distance, a geometric ratio (i.e., the distance from nozzle to the substrate divided by the nozzle diameter), as well as a speed ratio (i.e., the printing speed divided by the extrusion speed) are varied. Section 2 describes the methodology of the study, along with the experimental and numerical details. Next, Section 3 presents and discusses the results. Finally, Section 4 summarizes the results with the conclusion.

2. Methodology

2.1. Materials’ properties and 3DCP experiments

A fresh cement-based mortar was used to perform the 3DCP experiment around the rebars. The mortar includes a binder system with white cement CEM I 52.5 R-SR 5 (EA), limestone filler with sand of maximum particle size 0.5 mm, admixtures, and water. The binder was prepared with a 75 L Eirich Intensive Mixer Type Ro8W. The water to cement ratio was 0.39. The admixtures dosage (by weight of cement) was set at 0.1 % high-range water-reducing agent, 0.1 % viscosity-modifying agent, and 0.5 % hydration retarder.

The rheological characterization of the mortar was done using an Anton Paar rheometer MCR 502, as used in [50,54]. The rotational and oscillatory tests were performed with a vane-in-cup measuring device. The obtained flow curve of the mortar from the rotational rheometric tests, with a ramp-down controlled shear rate (CSR), was fitted by a linear regression to determine the yield stress τ0= 630 Pa and plastic viscosity ηP= 7.5 Pa·s. The oscillatory test showed that the constitutive behavior of the unyielded mortar had a factorized relationship between the storage modulus G′ and loss modulus G′′ within the linear viscoelastic (LVE) region, where G′= 200 kPa was captured. Therefore, the mortar’s rheology was modelled as a yield stress limited elasto-viscoplastic material, where the storage modulus is used as the linear elastic shear modulus of the unyielded mortar. Furthermore, the rheological characterization showed that the mortar exhibited time-independent rheological characteristics within the actual printing process, see [50] for more details.

The setup for 3DCP experiments around ribbed rebars is presented in Fig. 1. It comprised a 6-axis industrial robot (Fanuc R-2000iC/165F) with a custom-designed nozzle ∅20 mm (i.e., nozzle diameter, Dn= 20 mm) made by fused filament fabrication of ABS thermoplastic, cf. Fig. 1-a. The robot also included a progressive cavity pump (NETZSCH) equipped with a hopper and a long steel-wire rubber hose (cf. Refs. [50, 52] for details). A 25 mm thick plywood plate was used as the built substrate as seen in Fig. 1-b. The 1000 mm long rebars of diameter Dr= 8 and 12 mm were placed horizontally on top of the substrate at a distance Hr= 14 mm. The horizontal rebars were held in place by two vertical rebars with a height of 37 mm. The setup was used to print a structure of four successive layers of parallel strands around the rebars. Details on the printing toolpath around the rebars are illustrated in the subsections below.

Fig. 1

Fig. 1. 3DCP experiment around rebars: (a) 6-axis robotic arm [50]; (b) plywood built platform with integrated rebars; (c) example of printing (picture is taken during printing of the third layer).

The extrusion nozzle was placed above the substrate with a nozzle height Dn/2 for the first layer, whereas for subsequent number of layers (Nl), the nozzle height was set at Nl∗Dn/2. Thus, the nominal height of a layer was h=Dn/2. The print was done with a material extrusion rate 0.91 dm3/min and nozzle speed 35 mm/s. An example of a physical print is presented in Fig. 1-c. After the prints hardened, cross-sections were collected to investigate the rebar-concrete bonding. The cross-section slices were taken at specific positions to analyze the print around the horizontal rebar and cross-shaped rebar (i.e., horizontal and vertical rebars). To avoid destroying the specimens while cutting them, the printed part were impregnated with epoxy resin in a vacuum chamber.

2.2. Computational models and governing equations

Three different CFD models are built. The first model only simulated the mortar flow to understand the void formation pattern without rebars. The last two models simulated the 3DCP experiment around rebars: one model simulated the mortar flow around the horizontal rebar, while the other considered the cross-shaped rebar. This subdivision enabled the CFD models to consider a smaller computational domain than if the two scenarios were combined.

The CFD models comprised a cylindrical nozzle, a solid-substrate, and an artificial solid component (at the top) within the computational domain of size 8.5D×6D×2D+4h as shown in Fig. 2 (top), where Model 1 excluded rebars (left), Model 2 included the horizontal rebar (middle), and Model 3 considered the cross-shaped rebar (right). The printing toolpath of the models are illustrated in Fig. 2. The toolpath for Models 1 and 2 are presented in 3D (left bottom figure), where the only difference was the presence of the horizontal rebar. The toolpath in 2D presented at the bottom right is for Model 3. For all the models, the toolpath of the extrusion nozzle kept a distance of Dnr from the axis of the nearest rebar. The lengths of the horizontal and vertical rebars were 50 and 40 mm, respectively. The other printing parameters were similar to the ones used in the experiment, cf. Section 2.1. Finally, the models were used to simulate four successive layers with a length of 125 mm. Note that the rebars are modelled as cylindrical solid objects (i.e., smooth rebar).

Fig. 2

Fig. 2. Model geometry with the extrusion nozzle, substrate, integrated rebars, and computational domain (top) and toolpath (bottom).

The computational domain was meshed by a uniform Cartesian grid. A mesh sensitivity test was performed for different meshes with cell sizes 0.9, 1.0, and 1.1 μm. Even if the change in absolute size of the cells were small, the total number of cells within the domain was 1.1, 1.5, and 2.0 million, respectively. A cell size of 1.0 μm was chosen as that was found to be time-efficient and had a negligible effect on the accuracy of the results. The top plane of the domain was an inlet boundary, where the artificial solid component was defined in order to prevent material flow outside the nozzle orifice, cf. Fig. 2 (top). On the bottom plane, a wall boundary was applied to represent the solid substrate. The other planes were assigned continuative boundary conditions, but had no influence on the results. Furthermore, no-slip boundary conditions were applied between fluids and solids.

Table 1 lists the printing parameters and their values for each of the investigated cases. All the models and cases are simulated for 4 successive layers.

Table 1. Description of case IDs with printing parameters and accompanying values. The reference values (corresponding to the experimental print) are written in bold, while the parameter change for each case is highlighted by underlining the value.

Empty CellModel/case ID
ParametersModel 1 (no rebar), Model 2 (horizontal rebar), and Model 3 (cross-shaped rebar)
Case 1
(reference)
Case 2Case 3Case 4Case 5Case 6Case 7Case 8Case 9
Nozzle diameter Dn (mm)202020202020202020
Rebar diameter Dr (mm)8612888888
Nozzle-rebar distance Dnr (mm)202020191820202020
Layer height h (mm)1010101010981010
Geometric ratio Gr=h/Dn0.50.50.50.50.50.450.40.50.5
Printing speed V (mm/s)353535353535353535
Extrusion speed U (mm/s)48.4248.4248.4248.4248.4248.4248.4251.4753.84
Speed ratio Sr=V/U0.720.720.720.720.720.720.720.680.65

The cementitious mortar flow was assumed transient and isothermal. Thus, the flow dynamics of the mortar are governed by the mass and momentum conservation equations of incompressible fluid:

where u is the velocity vector, ρ is the density, g=00−g is the gravitational acceleration vector, t is the time, p is the pressure, and σ is the deviatoric stress tensor.

The rheological behavior of the mortar was modelled by the following elasto-viscoplastic constitutive equation that represents σ as the sum of the deviatoric part of the viscous stress σV and elastic stress σE tensors; i.e.:

The deviatoric viscous stress tensor was predicted as:

is the deformation rate tensor, and T represents the transpose notation.

The deviatoric elastic stress tensor was modelled by the Hookean assumption of a small strain rate tensor E between each small time steps Δt=t−t0, to represent the elastic response of unyielded materials 

Ewhere G is the shear modulus and Et=Et0+ΔtDT is the incremental strain rate tensor approximated by integrating the deformation rate tensor over Δt.

The incremental representation of Eq. (5) can be written as:

 is the vorticity tensor. The first term of the left-hand side of Eq. (6) represents the change in stress at a fixed location in space. The change in stress due to advection and rotation of material particle is approximated by the second and third terms, respectively. The right-hand side takes into account the change in stress due to shearing.

The elastic stress tensor of the yielded material was approximated by imposing the yield stress τ0 limit as follows:

where σvM is the von Mises stress predicted as:

where IIσE∗=trσE∗2 is the second invariant of σE∗. The material was yielded when σvM exceeded the yield stress. The properties of the material used in the different models and cases are presented in Table 2. Note that the CFD model does not include the solidifications of the printed layers.

Table 2. Material properties.

Parameter with symbolUnitValueValue for reference simulation
Density, ρkg·m−321122112
Shear modulus, GkPa20–10020
Dynamic yield stress, τ0Pa400–800630
Plastic viscosity, ηPPa·s3.5–107.5

2.3. Numerical method

The computational model was developed in the commercial CFD tool FLOW-3D® (V12.0; Flow Science Inc.) [55]. It uses the FAVOR technique (Fractional Area/Volume Obstacle Representation) to embed solid objects (i.e., the nozzle, rebars, substrate, etc.) in the computational domain. The computational domain was meshed with a Cartesian grid and discretized with the Finite Volume Method.
The governing equations of the mortar flow were solved by the implicit pressure-velocity solver GMRES (Generalized Minimum Residual) [[56], [57], [58]]. The predictions of pressure and forces near solid objects were modelled by the immersed boundary method [59]. The yield stress limited elasto-viscoplastic criterion was built in the software, and the elastic stress was calculated explicitly. An implicit technique, successive under-relaxation, was used to solve the viscous stress of the momentum equation (Eq. (2)). The free surface of the mortar was captured by the Volume-of-Fluid technique, see details in Ref. [60, 61]. The momentum advection was calculated explicitly by an upwind-difference technique and ensured first-order accuracy. The time step size was controlled dynamically with a stability limit in order to avoid numerical instabilities [55]. All the simulations were run with 20 cores on a high-performance computing cluster. The study was carried out with a first-order accuracy in both space and time in order to reduce the computational time, which was extensive due to the elasto-viscoplastic material model that computes both viscous and elastic stresses (e.g., the computational time was six days for model 1 case 1). In this regard, one should note that the model can simulate a multitude of scenarios simultaneous.

2.4. Results post-processing

The simulated results were processed in two steps. The first step was to show the cross-sectional shapes which were done in the post-processing tool FLOW-3D®POST, and the second step was to calculate the volume fraction of air voids inside the printed structure. The cross-sectional shapes were used to investigate the interior of the structure and the rebar-concrete bonding. The cross-sectional shapes were obtained in the plane parallel to the yz-plane at the middle of the layer’s length, as shown in Fig. 3-d. Fig. 3-c sketches the nominal positions of the air void creation in a four-layered structure. The positions of the air voids were defined as outer-bottom, bottom, mid, top, and outer-top in this study. The presence of the air void was quantified by calculating the volume fraction of air voids around the middle of the layer’s length. The calculation enabled to capture the presence of air voids for Model 3, i.e., around the vertical rebar, as seen in the dashed-box of Fig. 3-b.

Fig. 3

Fig. 3. Post-processing of results; (a) introduction of volume sampling cuboid to calculate the volume fraction of air voids; (b) presence of air voids around the vertical rebar in the experiment; (c) schematic of air void creation; (d) cross-sectional shapes and void sampling area for the different models.

In order to calculate the volume fraction of air voids, a cuboid of size 20×25×3h mm3 was introduced to the CFD models as a volume sampling object, as seen in Fig. 3-a. Note that the size and position of the object were the same for all the models. The volume sampling was a three dimensional data collection tool built in the software that enabled calculating the amount of material as well as air void inside of it. Finally, the volume fraction of air voids VV was calculated as below:

3. Results and discussions

his section compares the simulated and experimental results of 3DCP around the rebars. Furthermore, it discusses the influence of different parameters on the air void formation in the cross-sectional shapes of printed parts and the volume fraction of air voids inside the structure. The parametric study includes the material properties (i.e., yield stress and plastic viscosity) and the printing properties (i.e., rebar diameter, rebar-nozzle distance, geometric ratio, and speed ratio).

3.1. Experiments and validation of the CFD model

The CFD models (Models 2 and 3) are compared and validated with the experiments. The results are presented in Fig. 4. Two rebar diameters, i.e., Dr= 8 and 12 mm, are taken into account, where the nozzle-rebar distances are 20 and 24 mm, respectively. The other printing and material parameters are kept constant in the experiments with different rebar diameters, see Table 1 (cases 1 and 3). In the case of the simulations, all parametric details are the same as implemented in the experiments except for the elastic shear modulus. The choice of shear modulus is subject to the analysis presented in Appendix A. The shear modulus is reduced to 100 kPa from the measured value (i.e., 200 kPa) to compare the simulated results with experiments. Furthermore, a shear modulus of 20 kPa is chosen for the parametric study in the later sections. These assumptions seem reasonable to avoid extensive computational time consumption since the differences found in void formation are limited (see Fig. A.1).

Fig. 4

Fig. 4. 3DCP experiments (left column), simulations (middle column), and comparison (right column). (a) Horizontal rebar with Dr= 8 mm and Dnr= 20 mm; (b) horizontal rebar with Dr= 12 mm and Dnr= 24 mm; (c) cross-shaped rebar with Dr= 8 mm and Dnr= 20 mm; and (d) cross-shaped rebar with Dr= 12 mm and Dnr= 24 mm. The blue part in the experiments is epoxy resin. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

The cross-sectional shapes of the 3DCP experiments around the horizontal rebar of
8 mm in Fig. 4-a illustrate the presence of a top air void as well as mid and bottom air voids positioned respectively above and below the horizontal rebar. The mid and bottom air voids are found to be smaller than the top one. This is due to the presence of the rebar that occupies the mortar’s flowable space as well as the deformation of the previously printed layers. For a detailed analysis of the deformation pattern, refer to [53]. The air voids at the top and bottom are significant when the rebar diameter is increased to 12 mm (Fig. 4-b). This is due to the fact that the nozzle-rebar distance was increased, which enhances the flowable space between the strands. In addition, the larger size of the rebar creates larger channels below and above itself, where the mortar of the second and third layers is forced to be squeezed into. The mid-air void is found to be absent as its area is fully occupied by the larger rebar. In the case of the cross-shaped rebars, the existence of the vertical rebar seems to restrict the merging of parallel strands, and therefore, the presence of air void content increases, cf. Fig. 4-c, d. This limitation is found to be pronounced for the larger rebar diameter with the larger nozzle-rebar distance.
The cross-sectional shapes of the simulations (middle column in Fig. 4) illustrate high accuracy predictions of the position and size of the air voids when compared with the experiments. Particularly, the models capture small details around the vertical rebar for both diameters. This can clearly be seen in the comparison of experiments and simulation, cf. right column in Fig. 4. A discrepancy is found in the strand’s width of the bottom layer as well as the shape of the printed part, specifically in the shape of strands of all the layers next to the vertical rebar and the height of the part for the smaller rebar diameter. These could be due to a combined effect of the idealized rheological model, as well as slight differences in the processing parameters, e.g. nozzle height above the printing surface, nozzle-rebar distance, as well as printing- and extrusion-speed. Note that the height of the vertical rebar in the experiments is a bit shorter than the one in the simulations (40 mm), although it does not influence the results.

3.2. Influence of materials properties

The influence of the material properties, yield stress and plastic viscosity, on the air void formation is presented in Fig. 5, Fig. 6, Fig. 7. The process parameters of Case 1 (cf. Table 1) are utilized.

Fig. 5

Fig. 5. Air void formation in the cross-sections of the printed parts for different yield stress.

Fig. 6

Fig. 6. Air void formation in the cross-sections of the printed parts for different plastic viscosity.

Fig. 7

Fig. 7. Volume fraction of air voids for different models as a function of (a) yield stress and (b) plastic viscosity.

Yield stress

Fig. 5 presents cross-sectional shapes for different yield stress, 400, 630, and 800 Pa. It can be seen that Models 1 and 2 predict a top air void, while for Model 3 the two topmost strands to the left are not in contact with the vertical rebar. The cross-sections illustrate that an increased yield stress causes less deformation of the printed layers and create stands with less round shape. This is due to the reduced effective gap (i.e., the distance between the nozzle and previous printed layer), which results in a reduced air void content for most models as seen quantitatively in Fig. 7-a. This behavior is converse to conventional concrete castings where a more fluid material (e.g. self-compacting concrete) can lead to a lower void content. An exception to the observed behavior that a higher yield stress leads to less voids formation is seen in case of Model 2 with
800 Pa, where the top air void is slightly larger as compared to the one for
630 Pa. Another exception is that an outer bottom air void appears for Models 1 and 2 when increasing the yield stress to 800 Pa. Both exceptions are a consequence of the yield stress now restricting the flow in confined spaces, which illustrates that it is a non-trivial task to fully eradicate air voids only by increasing the yield stress.

Plastic viscosity

As the plastic viscosity is varied, cross-sections for Model 1 show a slight change in air voids, see Fig. 6. A mid-air void is produced when the plastic viscosity is small, while the two largest plastic viscosities only produce the top air void. This is due to the increase in extrusion pressure that leads to larger deformation of the printed layers when the plastic viscosity is increased, cf. details in ref. [47]. When integrating a horizontal rebar (see Model 2), the air void formation increases at higher plastic viscosities. This could be due to the fact that the sideway flow of the depositing material (i.e., y-velocity) is limited by the flow resistance that comes from both the larger plastic viscosity and the presence of the solid rebar. No noticeable change can be seen in the cross-sections of Model 3 for different plastic viscosities. The same findings are quantitatively highlighted in Fig. 7-b, which illustrates that the volume fraction of air voids is not influenced much by the plastic viscosity except for Model 2.

3.3. Influence of processing conditions

The influence of processing conditions such as rebar diameter, nozzle-rebar distance, geometric ratio, and speed ratio on air void formation is presented in terms of cross-sectional shapes and volume fraction of air void, see Fig. 8, Fig. 9, Fig. 10, Fig. 11, Fig. 12. Models 1 to 3 are simulated with the reference material properties, cf. Table 2.

Fig. 8

Fig. 8. Air void formation in the cross-sections of the printed parts for different rebar diameters.

Fig. 9

Fig. 9. Air void formation in the cross-sections of the printed parts for different nozzle-rebar distances.

Fig. 10

Fig. 10. Air void formation in the cross-sections of the printed parts for different geometric ratios.

Fig. 11

Fig. 11. Air void formation in the cross-sections of the printed parts for different speed ratios.

Fig. 12

Fig. 12. Volume fraction of air voids for different models as a function of (a) rebar diameter, (b) nozzle-rebar distance, (c) geometric ratio, and (d) speed ratio.

Rebar diameter

The influence of the rebar diameter on the air void formation is presented in Fig. 8, Fig. 12-a. Models 2 and 3 are simulated (Model 1 does not contain a rebar) for Cases 1, 2, and 3, cf. Table 1. Fig. 8 illustrates that the top air void appears almost constant for Model 2, whereas the air void below the rebar increases with an enlarged rebar diameter. Two phenomena with opposite effects on the void formation play a role in this regard. On the one hand, increasing the rebar size reduces the space that the strands need to occupy to fully merge and thereby eliminate voids. On the other hand, the resistance towards flow and merging of the parallel strands next to the rebar increases proportionally with the size of the reinforcement. The latter effect is dominating in this case. For Model 3, the air void formation also increases when increasing the reinforcement. In addition to the previously mentioned argument, this is due to the left strands having to flow longer to reach the vertical rebar (i.e., Dnr+Dr/2). Conversely, additional air voids take place on the right-hand side of the vertical rebar for the smallest rebar diameter, because the nozzle-rebar distance Dnr= 20 mm is kept constant. Fig. 12-a underlines quantitatively that the volume fraction of air voids reduces when the rebar diameter is small. The trend is more pronounced for the cross-shaped rebar (Model 3), but in absolute values the air voids are substantially less for Model 2.

Nozzle-rebar distance

Fig. 9, Fig. 12-b show the effect of different nozzle-rebar distances on the formation of air voids. All the models are simulated for Cases 1, 4, and 5, cf. Table 1. Fig. 9 shows that the presence of air voids is reduced when the nozzle-rebar distance reduces. This is because the flowable space around the rebars shrinks. Interestingly, no significant air voids are present in Model 1 and 2 when Dnr= 18 mm, see Fig. 12-b. Fig. 12-b also depicts that the trend is more pronounced for the cross-shaped rebar (Model 3). One should be careful though about decreasing the nozzle-rebar distance too much, as a ridge is forming on the top layer since material from the left strand starts to flow on top of the right strand (Fig. 9), which potentially could affect the final shape of the structure. In case of the cross-shaped rebar model, air voids are formed for all investigated Dnr. One could potentially with benefit reduce the Dnr further, but not more than the sum of half of the nozzle diameter (10 mm), the nozzle wall thickness (2.5 mm), and half of the rebar diameter (4 mm), i.e., 16.5 mm, otherwise the nozzle will collide with the rebar.

Geometric ratio

The effect of the geometric ratio on the formation of air voids is presented in Fig. 10, Fig. 12-c. The considered simulations are Cases 1, 6, and 7 cf. Table 1. Fig. 10 illustrates that decreasing the geometric ratio can reduce the presence of air voids in the cross-sections. This is because a smaller geometric ratio results in wider strands, which then occupy more of the flowable space around the rebars. Note that when Gr= 0.50, 0.45, and 0.40 the layer height is 10, 9, and 8 mm, respectively. No air voids are formed for Model 1 and 2 when Gr= 0.45, and 0.40. However, for the smallest ratio ridges are obtained on either side of the strands as clearly seen for the top layer. These ridges can as previously mentioned have a negative effect on the final shape of the structure. Consequently, Gr= 0.45 is preferable for these two models. In the case of Model 3, air voids are still present next to the vertical rebar, even for the smallest investigated geometric ratio. The volume fraction of air voids is approximately 1.5 %, see Fig. 12-c. The geometric ratio could be reduced further in order to decrease the air voids even more, but the ridges already form at Gr= 0.40. Consequently, it is not possible to fully eliminate air voids while at the same time avoiding ridges when only varying the geometric ratio for Model 3.

Speed ratio

Fig. 11, Fig. 12-d illustrate the formation of air voids for different speed ratios. The considered simulations are Case 1, Case 8, and Case 9, cf. Table 1. The three speed ratios are obtained by applying an extrusion speed of 48.4 mm/s, 51.5 mm/s, and 53.8 mm/s. Fig. 11 show that less air voids are formed when decreasing the speed ratio (i.e., higher extrusion speed). Reducing the speed ratio increases the cross-sectional area of the strands proportionally, thereby decreasing the air voids. Model 1 obtains no air voids for the two smallest ratios, and the same is almost the case for Model 2; only a very small air void is formed when Sr= 0.68, see Fig. 12-d. Model 3 forms air voids for all speed ratios. For the lowest speed ratio, the third strand to the left is in contact with the vertical rebar, but air voids are still formed around the horizontal reinforcement, which underlines the fact that it is difficult to fully eliminate air voids for the cross-shaped rebars.

3.4. Cross-shaped reinforcement

Based on the above analysis, it is clear that the air voids around the horizontal rebar can be eliminated by changing some of the processing conditions, such as the nozzle-rebar distance, geometric ratio, and speed ratio. However, it remains unsolved to fully omit the presence of air voids around the cross-shaped rebar, although the processing conditions can reduce the volume fraction of air voids. A parametric study was conducted by varying some combinations of processing conditions; however, the same conclusion was achieved that the air voids could not be fully eliminated. In order to solve this predicament, a new stepped toolpath is investigated (see Fig. 13) along with three different rebar geometries: 1) cylindrical rebars as in the previous analysis, see Fig. 14-a; 2) a squared horizontal rebar, cf. Fig. 14-b; and 3) cylindrical rebars with a smooth transition between them, see Fig. 14-c. In all scenarios, the speed ratio is 0.665, the size (i.e., diameter or side of square) of the rebars are 6 mm, and the horizontal rebar is placed at a height of 8 mm from the substrate. The other processing parameters are the same as for Case 2 and reference material properties are applied. For scenarios one and two small air voids are formed, but for scenario three air voids are eliminated, see Fig. 14. This numerical analysis illustrates that although it is difficult to get rid of air voids for the cross-shaped rebars, one can do it when carefully selecting the material- and processing-parameters and remembering to have a smooth transition between the rebars.

Fig. 13

Fig. 13. New toolpath planning around the cross-shaped rebar.

Fig. 14

Fig. 14. Simulated structure with new toolpath and different rebar geometries. (a) Cylindrical horizontal- and vertical-rebar, (b) square horizontal rebar and cylindrical vertical rebar, (c) cylindrical horizontal- and vertical-rebar with smooth transition. Note that Dr= 6 mm, Sr= 0.665, and Hr= 8 mm.

4. Conclusions

A CFD model was used to predict the morphology of strands and the formation of air voids around reinforcement bars when integrated with 3DCP. The model used an elasto-viscoplastic constitutive model to mimic the cementitious mortar flow. The CFD model was compared with experiments that constituted a horizontal and a cross-shaped rebar configuration. The results illustrated that the model with high-accuracy could predict the air void formation in the structures. The simulations had though slightly less wide bottom strands as compared to the experimental counterpart, which was attributed to small differences in material behavior and processing parameters.
The CFD model was exploited to investigate the effect of material properties on the air void formation. The results illustrated that by increasing the yield stress less air voids were formed due to the reduced effective gap. However, the air voids could not be eliminated as the increased yield stress also restricted the flow in confined spaces. In contrast to the effect of the yield stress, the void formation decreased somewhat when decreasing the plastic viscosity (although not enough to omit air voids fully).
The process parameters were found to have a substantial effect on the air void formation. The air void formation increased when increasing the rebar diameter, because the resistance towards flow around the reinforcement and thereby merging of the strands increased proportional with the size of the rebars. The air voids could be reduced and in some of the horizontal cases fully avoided by reducing the nozzle-rebar distance, but it could come with the expense of ridges (which could affect the final geometry of the structure), since material from one strand would flow on top of a previously deposited stand. Similarly, decreasing the geometric ratio was found to reduce the presence of air voids, because a smaller geometric ratio resulted in wider stands that occupied more of the space around the rebars. However, the smallest ratios also resulted in ridges. It was also found that less air voids were formed when decreasing the speed ratio, since the cross-sectional area of the strands increased proportionally, thereby occupying more space around the rebars.
By decreasing the nozzle-rebar distance, geometric ratio, and speed ratio, voids were omitted around the horizontal rebar, but air voids would still be introduced for the cross-shaped rebar. Those air voids could be eliminated by changing the toolpath and some processing parameters, as well as altering the geometry of the reinforcement joint to a smooth transition between the horizontal and vertical rebar. The results highlight that it is non-trivial to avoid air voids when integrating rebars in 3DCP, but that the CFD model is a very strong digital tool when it comes to securing a good bonding between the reinforcement and concrete.
A limitation of the CFD model is that with the current computational power it is not possible to simulate a full 3DCP structure. Nevertheless, the CFD model is powerful when it comes to understanding and optimizing printing strategies for individual reinforcement details. In future research, it would be interesting to exploit the CFD model to systematically investigate various reinforcement setups and based on the model results generate response surfaces or lookup tables, which can be coupled with the 3DCP toolpath software. This approach would have several benefits: 1) the computational heavy CFD model could run all scenarios in parallel, thereby minimizing the physical time spent on calculations; 2) one could avoid repetition of individual reinforcement studies; and 3) the response surfaces or lookup tables could in a computational light manner come up with printing strategies for all reinforcement details in a full 3DCP structure.

CRediT authorship contribution statement

Md Tusher Mollah: Conceptualization, Methodology, Investigation, Formal analysis, Visualization, Writing – original draft, Writing – review & editing. Raphaël Comminal: Conceptualization, Formal analysis, Writing – review & editing, Supervision. Wilson Ricardo Leal da Silva: Conceptualization, Formal analysis, Writing – review & editing, Resources. Berin Šeta: Investigation, Formal analysis, Writing – review & editing. Jon Spangenberg: Conceptualization, Investigation, Formal analysis, Writing – review & editing, Supervision, Resources, Project administration.

Declaration of competing interest

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

Acknowledgements

The authors would like to acknowledge the support of the Danish Council for Independent Research (DFF) | Technology and Production Sciences (FTP) (Contract No. 8022-00042B). Also, the authors would like to acknowledge the support of the Innovation Fund Denmark (Grant No. 8055-00030B: Next Generation of 3D-printed Concrete Structures and Grant no. 0223-00084B: ThermoForm – Robotic ThermoSetting Printing of Large-Scale Construction Formwork), Moreover, the support of FLOW-3D® regarding licenses is acknowledged.

Appendix A.

This analysis varies the shear modulus (i.e., 20, 50, and 100 kPa) in the case Dr= 8 mm, as seen in Fig. A.1, which presents the cross-sectional shapes (top) and the volume fraction of air voids (bottom). It can be seen that increasing the shear modulus slightly reduces the air void formation. This is because the larger shear modulus enhances the ability of the material to act against the shear deformation. However, an increase in shear modulus also extensively increases the computational time of solving the non-linear elastic response of the elasto-viscoplastic material. For example, the computational time of Model 3 is about 6, 12, and 18 days for a shear modulus of 20, 50, and 100 kPa, respectively. Therefore, the shear modulus is reduced to 100 kPa from the measured value (i.e., 200 kPa) to compare the simulated results with experiments. Furthermore, the shear modulus 20 kPa is chosen for the parametric study in 3.2 Influence of materials properties, 3.3 Influence of processing conditions, 3.4 Cross-shaped reinforcement. These assumptions seem reasonable to avoid extensive computational time consumption since the differences found in Fig. A.1 are not substantial.

Fig. A.1

Fig. A.1. Air void formation in the cross-sections of the printed parts (top) and the volume fraction of air voids (bottom) for different shear modulus.

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The distribution of the computed maximum current speed during the entire duration of the NAMI DANCE and FLOW-3D simulations. The resolution of computational domain is 10 m

Performance Comparison of NAMI DANCE and FLOW-3D® Models in Tsunami Propagation, Inundation and Currents using NTHMP Benchmark Problems

NTHMP 벤치마크 문제를 사용하여 쓰나미 전파, 침수 및 해류에서 NAMI DANCE 및 FLOW-3D® 모델의 성능 비교

Pure and Applied Geophysics volume 176, pages3115–3153 (2019)Cite this article

Abstract

Field observations provide valuable data regarding nearshore tsunami impact, yet only in inundation areas where tsunami waves have already flooded. Therefore, tsunami modeling is essential to understand tsunami behavior and prepare for tsunami inundation. It is necessary that all numerical models used in tsunami emergency planning be subject to benchmark tests for validation and verification. This study focuses on two numerical codes, NAMI DANCE and FLOW-3D®, for validation and performance comparison. NAMI DANCE is an in-house tsunami numerical model developed by the Ocean Engineering Research Center of Middle East Technical University, Turkey and Laboratory of Special Research Bureau for Automation of Marine Research, Russia. FLOW-3D® is a general purpose computational fluid dynamics software, which was developed by scientists who pioneered in the design of the Volume-of-Fluid technique. The codes are validated and their performances are compared via analytical, experimental and field benchmark problems, which are documented in the ‘‘Proceedings and Results of the 2011 National Tsunami Hazard Mitigation Program (NTHMP) Model Benchmarking Workshop’’ and the ‘‘Proceedings and Results of the NTHMP 2015 Tsunami Current Modeling Workshop”. The variations between the numerical solutions of these two models are evaluated through statistical error analysis.

현장 관찰은 연안 쓰나미 영향에 관한 귀중한 데이터를 제공하지만 쓰나미 파도가 이미 범람한 침수 지역에서만 가능합니다. 따라서 쓰나미 모델링은 쓰나미 행동을 이해하고 쓰나미 범람에 대비하는 데 필수적입니다.

쓰나미 비상 계획에 사용되는 모든 수치 모델은 검증 및 검증을 위한 벤치마크 테스트를 받아야 합니다. 이 연구는 검증 및 성능 비교를 위해 NAMI DANCE 및 FLOW-3D®의 두 가지 숫자 코드에 중점을 둡니다.

NAMI DANCE는 터키 중동 기술 대학의 해양 공학 연구 센터와 러시아 해양 연구 자동화를 위한 특별 조사국 연구소에서 개발한 사내 쓰나미 수치 모델입니다. FLOW-3D®는 Volume-of-Fluid 기술의 설계를 개척한 과학자들이 개발한 범용 전산 유체 역학 소프트웨어입니다.

코드의 유효성이 검증되고 분석, 실험 및 현장 벤치마크 문제를 통해 코드의 성능이 비교되며, 이는 ‘2011년 NTHMP(National Tsunami Hazard Mitigation Program) 모델 벤치마킹 워크숍의 절차 및 결과’와 ”절차 및 NTHMP 2015 쓰나미 현재 모델링 워크숍 결과”. 이 두 모델의 수치 해 사이의 변동은 통계적 오류 분석을 통해 평가됩니다.

The distribution of the computed maximum current speed during the entire duration of the NAMI DANCE and FLOW-3D simulations. The resolution of computational domain is 10 m
The distribution of the computed maximum current speed during the entire duration of the NAMI DANCE and FLOW-3D simulations. The resolution of computational domain is 10 m

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Acknowledgements

The authors wish to thank Dr. Andrey Zaytsev due to his undeniable contributions to the development of in-house numerical model, NAMI DANCE. The Turkish branch of Flow Science, Inc. is also acknowledged. Finally, the National Tsunami Hazard Mitigation Program (NTHMP), who provided most of the benchmark data, is appreciated. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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  1. Deniz Velioglu SogutPresent address: 1212 Computer Science, Department of Civil Engineering, Stony Brook University, Stony Brook, NY, 11794, USA

Authors and Affiliations

  1. Middle East Technical University, 06800, Ankara, TurkeyDeniz Velioglu Sogut & Ahmet Cevdet Yalciner

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Correspondence to Deniz Velioglu Sogut.

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Velioglu Sogut, D., Yalciner, A.C. Performance Comparison of NAMI DANCE and FLOW-3D® Models in Tsunami Propagation, Inundation and Currents using NTHMP Benchmark Problems. Pure Appl. Geophys. 176, 3115–3153 (2019). https://doi.org/10.1007/s00024-018-1907-9

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  • Received22 December 2017
  • Revised16 May 2018
  • Accepted24 May 2018
  • Published07 June 2018
  • Issue Date01 July 2019
  • DOIhttps://doi.org/10.1007/s00024-018-1907-9

Keywords

  • Tsunami
  • depth-averaged shallow water
  • Reynolds-averaged Navier–Stokes
  • benchmarking
  • NAMI DANCE
  • FLOW-3D®

냉각 열 응력과 변형 해석

FLOW-3D로 해석한 냉각 열 응력과 변형 시뮬레이션

Temperature contour after cooling

Flow Science, INC 소속의 AHG Isfahani & JM Brethour기 발표한 FLOW-3D로 냉각 열 응력과 변형을 시뮬레이션 한 결과입니다.

주조 업계에서는 고형화 및 냉각 중 열응력을 예측하고 그 결과로 변형되는 현상을 예측하는 것이 여전히 어려운 과제입니다.

플로우 사이언스는 최근 이러한 종류의 예측을 고객에게 제공하기 위해 FSI(Fuid-Structure Interaction)와 TSE(Thermal Stress Evolution) 모델을 개발했습니다. Fuid-cocus 모델링 포트폴리오에 솔리드 메카니즘이 추가됨에 따라 FLOW-3D*(www.fow3d.com)는 이제 하나의 소프트웨어 패키지에서 완전히 결합된 Auid-structure 상호 작용 모델을 제공하는 몇 안 되는 시뮬레이션 툴 중 하나가 되었습니다.

내장된 유한 요소 분석과 FLOW-3D의 입증된 자유 표면 Aows 기록은 주조 업계에 매력적인 선택입니다. 많은 사용자들이 주조 프로세스를 포함한 유체 구조 상호 작용 문제를 시뮬레이션하기 위해 여러 소프트웨어 패키지를 결합해 왔습니다.

모델 제작자는 Auid 역학을 별도로 해결한 다음 표면 경계 조건을 고체 역학적 패키지로 가져와 응력과 변형을 얻은 다음 변형된 형상을 다시 조류 해결기로 공급하고 주기는 계속됩니다.

이 프로세스의 수동 구현은 지루함을 증명하고 스크립트 및 래퍼를 통해 프로세스를 자동화하는 것은 어려운 일입니다. 게다가, 대부분의 경우 이 커플링은 사례별로 수행되어야 합니다.

FLOW-3D는 이 프로세스의 두 측면을 단일 시뮬레이션의 결과로 두 솔루션이 모두 제공되는 하나의 패키지로 원활하게 통합했습니다.

이 기사에서는 시뮬레이션 결과를 실제 주조 부품의 변형과 비교하는 경우를 제시한다. 부품 및 실험 결과는 Littler Diecast Corporation의 Mark Littler에 의해 제공되었습니다.

Introduction
In the casting industry, the ability to predict thermal stresses and resulting deformations during solidification and cooling continues to be a challenge. Flow Science has recently developed its fuid-structure interaction (FSI) and thermal stress evolution (TSE) models to provide these kinds of predictions to its customers. With the addition of solid mechanics to its existing fuid focused modeling port- folio, FLOW-3D*(www.fow3d.com) is now one of the few simulation tools that provide a fully coupled Auid-structure interaction model within one software package. The built- in finite element analysis along with FLOW-3D’s proven record in free surface Aows makes it an attractive choice to the casting industry. Many users have been coupling multiple software packages in order to simulate fuid-structure interaction problems including casting processes. The modeler solves the Auid mechanics separately, then imports the surface boundary conditions into a solid mechanics package, obtains the stresses and deformations and then feeds the deformed geometry back into the fow solver and the cycle continues. The manual implementation of this process proves tedious and automating it through scripts and wrappers is challeng- ing. Besides, most of the time, this coupling has to be done on a per case basis. FLOW-3D has seamlessly integrated both aspects of this process into one package where both solutions come out as the result of a single simulation. In this article, a case where the simulation results are compared to deformations from an actual cast part is pre- sented. The part and experimental results were provided by Mark Littler of Littler Diecast Corporation.

결론

FLOW-3D는 최근 고체 역학을 컴퓨팅하면서 Auid Aow를 동시에 시뮬레이션하는 기능을 추가했습니다.

업계에서 단일 시뮬레이션 내에서 완전히 결합된 Auid-Structure 상호 작용을 해결할 수 있는 소프트웨어 패키지는 몇 개 되지 않습니다. 이 모델은 선형 후크 모델을 기반으로 하지만 각 시간 단계에서 스트레스가 점진적으로 계산되기 때문에 큰 변형이 가능합니다.

이 방법에서, 각 작은 증가 동안의 응력-변형 관계는 대부분의 경우 선형으로 가정할 수 있다. 또한 다이 및 응고 합금의 온도 의존성 탄성 특성을 지정할 수 있습니다. 이 모델은 열 잔류 응력으로 인해 냉각 중에 부품이 원하는 형상에서 변형되는 주조 업계에 특히 유용합니다.

캐스터는 이러한 변형을 예측하고 다이를 아주 약간만 변화시켜 최종 변형 기하학이 원하는 형태가 되도록 수정합니다.

이 작업은 FLOW-3D 사용자에게 흥미로운 새로운 경로를 제시하며 향후 릴리즈에서 몇 가지 새로운 기능을 제공하는 토대가 됩니다.

그러한 노력에는 플라스틱 변형과 인접한 고체 구성 요소 간, 그리고 고체 구성 요소와 고체화된 Auid 영역 사이의 완전한 결합이 포함됩니다.

Conclusions

FLOW-3D has recently added the capability of simulta- neously simulating the Auid Aow while computing the solid mechanics. There are only a few software packages in the industry that can solve a fully coupled Auid-struc- ture interaction within a single simulation. Although the model is based on a linear Hookean model, large deformations are possible because the stress is computed incrementally during each time step. In this method, the stress-strain relationship during each small incre- ment can be assumed to be linear in most cases. Fur- thermore, temperature-dependent elastic properties of the die and solidified alloy can be specified. This model is particularly beneficial to the casting industry where thermal residual stresses cause the part to deform from the desired geometry during cooling. Casters can predict these deformations and correct for them by changing the die ever so slightly so that in fact the final deformed geometry is the desired shape. This work represents an exciting new path for FLOW- 3D users and serves as a foundation for several new capabilities in future releases. Such efforts will include plastic deformations and full coupling between neigh- boring solid components and between solid components and solidified Auid regions.

Incremental Elastic Stress Model

Introduction
Elastic stress has been incorporated into FLOW-3D® to emulate viscoplastic materials, which are materials which behave as solids up to a yield stress, beyond which they behave like a viscous liquid.

The incremental elastic stress model recently incorporated into FLOW-3D® computes the elastic stress using linear Hookean theory (Equation 2 above). Although this constitutive equation predicts only a linear response to stress, implementation as an incremental model, in which the stress changes in each time step are accumulated, allows the prediction of highly nonlinear responses. This works because the response within each small time step can be well approximated as linear. Pictorially, with this model, FLOW-3D® predicts the total stress as a summation of the viscous stress and the elastic stress, as shown in Figure 1.