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M. Kato (1993)
The modeling of turbulent flow around stationary and vibrating square cylinders
T. Tamura, H. Kawai, S. Kawamoto, Kojiro Nozawa, Shigehiro Sakamoto, T. Ohkuma (1997)
Numerical prediction of wind loading on buildings and structures : Activities of AIJ cooperative project on CFDJournal of Wind Engineering and Industrial Aerodynamics
(2003)
A new low-Reynolds number turbulence model with hybrid time-scale of meanflow and turbulence for complex wall flow
(2003)
Large Eddy Simulation of building
Y. Tominaga, A. Mochida (1999)
CFD prediction of flowfield and snowdrift around a building complex in a snowy regionJournal of Wind Engineering and Industrial Aerodynamics, 81
D. Lakehal, W. Rodi (1997)
Calculation of the flow past a surface-mounted cube with two-layer turbulence modelsJournal of Wind Engineering and Industrial Aerodynamics
By, M. Smith (2003)
Renormalization group analysis of turbulence
Y. Meng, K. Hibi (1998)
Turbulent measurments of the flow field around a high-rise buildingWind Engineers, JAWE, 1998
M. Tsuchiya, S. Murakami, A. Mochida, K. Kondo, Y. Ishida (1997)
Development of a new k−ε model for flow and pressure fields around bluff bodyJournal of Wind Engineering and Industrial Aerodynamics, 67
R. Yoshie (1999)
CFD Analysis of flow field around a high-rise building, 1999
S. Murakami (1993)
COMPARISON OF VARIOUS TURBULENCE MODELS APPLIED TO A BLUFF BODYJournal of Wind Engineering and Industrial Aerodynamics
T. Shih, Jiang Zhu, J. Lumley (1993)
A Realizable Reynolds Stress Algebraic Equation Model
P. Durbin (1996)
On the k-3 stagnation point anomalyInternational Journal of Heat and Fluid Flow, 17
Hiroto Kataoka, M. Mizuno (2002)
Numerical flow computation around aeroelastic 3D square cylinder using inflow turbulenceWind and Structures, 5
T. Shih, W. Liou, A. Shabbir, Zhigang Yang, Jiang Zhu (1995)
A new k-ϵ eddy viscosity model for high reynolds number turbulent flowsComputers & Fluids, 24
V. Yakhot, S. Orszag (1986)
Renormalization group analysis of turbulence. I. Basic theoryJournal of Scientific Computing, 1
S. Murakami, A. Mochida, Y. Hayashi (1990)
Examining the κ-ϵ model by means of a wind tunnel test and large-eddy simulation of the turbulence structure around a cubeJournal of Wind Engineering and Industrial Aerodynamics, 35
Recently, prediction of the wind environment around a high-rise building using Computational Fluid Dynamics (CFD) has been carried out at the practical design stage. However, very few studies have examined the accuracy of CFD including the velocity distribution at pedestrian level. Thus, a working group for CFD prediction of the wind environment around a building was organized by the Architectural Institute of Japan (AIJ). This group consisted of researchers from several universities and private companies. In the first stage of the project, the working group planned to carry out cross comparison of CFD results of flow around a single high-rise building model placed within the surface boundary layer and flow within a building complex in an actual urban area obtained from various numerical methods. This was done in order to clarify the major factors affecting prediction accuracy. This paper presents the results of this comparison. Keywords: CFD; wind environment assessment; cross comparison; revised k-ε models; actual urban area Introduction numerical methods, in order to clarify the major factors Recently, prediction of the wind environment around affecting prediction accuracy. The first part of this paper a high-rise building using Computational Fluid compares results of CFD prediction of flow around a Dynamics (CFD) has been carried out at the practical 2:1:1 shaped building model and a 4:4:1 shaped building design stage. The performance of CFD prediction of flow model placed within the surface boundary layer using around a bluff body based on various turbulence models various turbulence models. The latter part describes the has been investigated by many authors [1-5]. However, cross comparison of results of the wind environment at these previous researches focused mainly on the pedestrian level within a building complex in an actual prediction accuracy of the separating flow and pressure urban area using different grid systems. distribution around the roof. Few have examined the accuracy of CFD prediction of the velocity distribution 2 Outline of cross comparisons at pedestrian level. Thus, a working group for CFD 2.1 Flowfields tested prediction of the wind environment around a building 1) Test Case A (2:1:1 shaped building model) was organized by the Architectural Institute of Japan Test Case A is the flowfield around a high-rise building (AIJ). This group consists of researchers from several model with the scale ratio of 2:1:1 placed within a surface universities and private companies [Note]. boundary layer (Fig.1a). For this flowfield, detailed At the first stage of the project, the working group measurement was reported by Ishihara & Hibi [6]. The planned to carry out cross comparison of CFD results Reynolds number based on H (building height) and U0 of flow around a high rise building predicted by various (inflow velocity at z=H) was 2.4×10 . 2) Test Case B (4:4:1 shaped building model) For Test Case B, the flowfield around a building model *Contact Author: Yoshihide Tominaga, Niigata Institute with the scale ratio of 4:4:1 (Fig.1b) was selected. A of Technology, 1719, Fujihashi, Kashiwazaki-shi, Niigata, wind tunnel experiment was carried out by the present 945-1195, Japan authors to obtain the experimental data for assessing the Tel & Fax:+81-257-22-8176 accuracy of CFD results. The Reynolds number based E-mail:tominaga@abe.niit.ac.jp on H (building height=4b) and U (inflow velocity at (Received November 8, 2003 ; accepted April 6, 2004) z=H=4b) was 7.2×10 . Journal of Asian Architecture and Building Engineering/May 2004/70 63 3) Test Case C (a building complex in an actual urban measured by non-directivity thermistor anemometers for area) case C. The target for Test Case C was the flowfield within a 2.2 Specified Conditions building complex in an actual urban area (Fig.1(c)). A In order to assess the performance of turbulence wind tunnel experiment was carried out by the present models, the results should be compared under the same authors. computational conditions. Special attention was paid to In the experiments for cases A and B, the wind velocity this point in this study. The computational conditions, was measured by a split fiber type anemometer that could i.e., grid arrangements, boundary conditions, etc., were monitor each component of an instantaneous velocity specified by the organizers of the cross comparison, and vector. On the other hand, the mean wind velocity was is summarized in the Appendix 1 and Table 4. The Fig.1. Flowfields tested in this study Table 1. Computed cases for 2:1:1 shaped building model(Test CaseA) 64 JAABE vol.3 no.1 May. 2004 Yoshihide Tominaga contributors were requested to follow the given conditions. 3. Results and discussion 3.1 Test Case A (2:1:1 shaped building model) The computed cases are outlined in Table 1. Nine groups have submitted a total of eighteen datasets of results. The performance of the standard k-ε and five types of revised k-ε models was examined. Furthermore, Differential Stress Model (DSM)[7] and Direct Fig.2. Lateral distribution of <u> along lateral direction (y) Numerical Simulation (DNS) with third-order upwind near ground surface at z=1/16H height scheme [8] and Large Eddy Simulation (LES) using the Smagorinsky subgrid-scale model [9] were also included compared here except for LES1. It is surprising to see for comparison. The computational conditions in this that there are significant differences between the X test case are described in Appendix 1 and Table 4. values of the standard k-ε model. As is already noted, 1) Reattachment lengths the grid arrangements and boundary conditions were set The predicted reattachment lengths on the roof, X , to be identical in all cases, and QUICK scheme was used and that behind the building, X , are given for all cases for convection terms in many cases. The reason for the in Table 1. As shown by the results of the standard k-e difference in X values predicted by the standard k-ε (KE1~8), the reverse flow on the roof, which is clearly models is not clear, but it may be partly due to differences observed in the experiment, is not reproduced. This was in some details of the numerical conditions, e.g. the convergence condition, etc. The results of the revised k- pointed out in previous researches by the present authors [1,2]. On the other hand, the reverse flow on the roof ε models except for the Durbinís model are in the appears in the results for all revised k-ε models (LK1, tendency to evaluate X larger than the standard k-ε RNG1, MMK1, RNG1, LK2, LK3, MMK2, DBN), model. This discrepancy is improved in the LES and DNS although it becomes a little larger than that in the computations. On the other hand, DSM greatly experiment. In the DSM result, the predicted separated overestimates X . The overestimation of reattachment flow from a windward corner is too large, and does not length behind a three-dimensional obstacle was also reattach to the roof. The result of LES without inflow reported by Lakehal and Rodi [5]. In ref. [5], predicted turbulence (LES1) can reproduce the reattachment on results of flow around a surface mounted cube obtained the roof, but X is somewhat overestimated in this case. by five types of k-ε models, i.e. the standard k-ε model, 1/2 velocity-scale-based On the other hand, the result of LES with inflow Kato-Launder model, Two-layer k 1/2 turbulence (LES2) shows close agreement with the model, Two-layer k velocity-scale-based model with 2 1/2 experiment. Kato-launder modification and Two-layer (v’ ) The evaluated reattachment length behind the velocity-scale-based model, were compared. The all building, X , is larger than in the experiment in all cases models compared in ref. [5] including three types of the Table 2. Computed cases for 4:4:1 shaped building model (Test Case B) JAABE vol.3 no.1 May. 2004 Yoshihide Tominaga 65 Fig.3. Horizontal distribution of each component of velocity along the lateral direction (y) near the ground surface at z=1/16H height (<u>, <v>, <w> indicate streamwise, lateral and vertical components of mean velocity vector, respectively. Values are normalized by the velocity at the same height at the inflow boundary) two-layer models overpredicred the reatchment length case are described in Appendix 1 and Table 4. behind the obstacle as well as in this study. In the two 1) Reattachment length layer models, viscous-affected near-wall region is The predicted reattachment lengths behind the resolved by a low Reynolds type one-equation model, building, X , are given for all cases in Table 2. The result while the outer region is simulated by the k-ε model. In of the DNS with a third-order upwind scheme shows the one-equation model, the eddy viscosity is made very close agreement with the experiment. The evaluated proportional to a velocity scale and a length scale. X value is larger than the experimental value in all The size of the recirculation region behind the building computed results based on the standard and revised k-ε is strongly affected by the momentum transfer models for this test case, as well as in the results for Test mechanism in the wake region, where vortex shedding Case A presented in 3.1. The results of the revised k-ε plays an important role. Thus, the reproduction of vortex models except for Durbin’s model predict a larger X shedding is significantly important for accurately value than the result of the standard k-ε. This tendency predicting the X value. However, none of the k-ε models is also similar to the results for Test Case A. compared here could reproduce vortex shedding. This 2) Lateral distributions of each component of velocity resulted in underestimation of the mixing effect in the vector near ground surface (z=1/16H) lateral direction causing too large a recirculation region Fig. 3(a) shows the lateral distributions of scalar behind the building. velocity and each component of mean velocity vector 2) Lateral distributions of <u> near ground surface near the ground surface in the area affected by the (z=1/16H) separation at the frontal corner. These values are Fig.2 shows the lateral distributions of the streamwise normalized by the velocity value at the same height at mean velocity component, <u>, near the ground surface the inflow boundary. The peak measured scalar velocity in the area affected by the separation at the front corner distribution appears at y/b 3. The standard k-ε and the in the selected cases. The peak in the measured velocity revised k-ε models overestimate the velocity around this distribution appears at y/b=-0.9. The standard k-ε (KE8) point. As shown in Fig. 3(b), in this area, the streamwise and the modified LK model (LK3) underestimate the component, <u>, of the mean velocity vector decreases velocity around this point. For the Durbin’s model as the distance from the side-wall decreases in the (DBN), the position and the peak value in the velocity experimental result. On the other hand, the measured distribution are well reproduced. In DSM, the evaluated <u> values decrease in the area and increase in the area velocities are generally larger in the region of y/b<-1.5 4<y/b as distance from the wall increases. The results of than those with other computations. the standard k-ε model do not reproduce this tendency 3.2 Test Case B (4:4:1 shaped building model) at all, while the result of the revised k-ε models show Outlines of computed cases are listed in Table 2. Five better agreement with the measured distribution. groups have submitted a total of twelve datasets of Between the results of the two revised k-ε models results. The performance of the standard k-ε and six types compared here, the distribution of <u> obtained from of revised k-ε models was examined. Furthermore, DNS the LK model shows much better agreement with the with a third-order upwind scheme [15] was also included experiment than do the RNG models. for comparison. Computational conditions in this test As shown in Fig. 3(d), the peak in the measured <w> 66 JAABE vol.3 no.1 May. 2004 Yoshihide Tominaga distribution appears at y/b 2.5. For the standard k-ε, wind directions in Niigata City. Since no clear differences the peak value is hardly reproduced. However, the result were observed between the horizontal distributions of of the RNG and LK models show generally close scalar velocity near the ground surface (z=2m) predicted agreement with the experiment. by the three CFD codes, the results from Code T are 3.3 Test Case C shown in Fig. 6. This figure illustrates the horizontal (building complex in actual urban area) distributions of scalar velocity near the ground surface Finally, prediction accuracy for wind environment (z=2m). The values in Fig. 6 are normalized by the within an actual building complex, located in Niigata velocity at the same height at the inflow boundary. It City, Niigata Prefecture, Japan, is examined. Fig. 6 can be seen that high velocity regions appear in the area illustrates three-target buildings (A~C). Building A is around the corner of the north and east sides of building 60m high, and buildings B and C are both 18m high. A and strong wind blows into the space between The surrounding area is mostly covered with low-rise buildings with the wind direction from NNE. On the residential houses. The wind rose of Niigata Local other hand, a high velocity region is observed in the area Meteorological Observatory is shown in Fig. 4. around the corner of the south side of building A with Here, we compare the results predicted with three the wind direction from W. The velocities in the street different codes: a homemade CFD code and two for the NNE wind direction are smaller than those for commercial CFD codes. The computational conditions the W wind direction. are described in Appendix 1 and Table 4. Data from an Fig. 7 shows the correlation between the normalized identical CAD file is used to reproduce the geometries velocities obtained for each code and those of the wind of the surrounding building blocks. This CAD file is tunnel experiment. The black circle indicates the produced from a drawing of the experimental model. Specifications of the CFD codes are compared in Table 3. Fig. 5 illustrates an enlarged view of the computational grid around the high-rise building model in all cases. Although CFD simulations were performed for sixteen different wind directions, only the wind distributions for wind directions NNE and W are shown here due to the limitation of available space. These are the prevailing Fig.4. Wind Rose of Niigata Local Meteorological Observatory Fig.5. Grid arrangements Table 3. Computed cases for building complex in actual urban area (Test Case C) JAABE vol.3 no.1 May. 2004 Yoshihide Tominaga 67 (1) Wind direction: NNE (2) Wind direction: W Fig.6. Distributions of normalized scalar velocity near ground surface (z=2m)(Code T) Fig.7. The correlation between the normalized velocity predicted by each code and wind tunnel exp. velocities at the measuring points in the wake region. A Fig. 8 compares the normalized velocities at each similar tendency is observed for all results in Figs. 7(1) measuring point. It is confirmed that all three CFD codes and (2). It is found that the scalar velocity predicted by compared here can predict the distribution of scalar all CFD codes tested here tends to be smaller in the wake velocity in reasonable agreement with the measurements region compared to the experimental value, as well as in except for the wake region and the region far from the the results for Test Cases A and B. Except for the target buildings. The prediction error in the far region is velocities in the wake region, the CFD analyses agree mainly caused by the insufficient grid resolution in this closely with the experimental results. The difference region, which is obviously not fine enough. between the scalar velocities in the wake region from 4 Conclusions the CFD and the experimental results is partly because 1) In the first part of this paper, the flowfields around the definition of the mean scalar velocity measured by two types of a high-rise building model, i.e. a 2:1:1 the non-directivity thermistor anemometers is different shaped model and a 4:4:1 shaped model placed within from that of CFD (cf. Appendix 3). This point will be the surface boundary layer, were predicted using the examined in more detail in the next stage of this project. standard k-e model, the revised k-ε models, DSM, LES 68 JAABE vol.3 no.1 May. 2004 Yoshihide Tominaga Fig.8. Comparison of normalized velocity value for each measurement point and DNS with a 3rd order upwind scheme. Results of Note The working group members are: A. Mochida (Chair, Tohoku Univ.), these predictions were compared with experimental data. Y. Tominaga (Secretary, Niigata Inst. of Tech.), Y. Ishida (Kajima Corp.), 2) The standard k-ε model could not reproduce the T. Ishihara (Univ. of Tokyo), K. Uehara (National Inst. of Environ. reverse flow on the roof in Test Case A. This drawback Studies), R. Ooka (I.I.S., Univ. of Tokyo), H. Kataoka (Obayashi Corp.), was corrected by all revised k-e models tested here. T. Kurabuchi (Tokyo Univ. of Sci.), N. Kobayashi (Tokyo Inst. However, the revised k-ε models except for the Durbin’s Polytechnics), N. Tuchiya (Takenaka Corp.), Y. Nonomura (Fujita Corp.), T. Nozu (Shimizu Corp.), K. Harimoto (Taisei Corp.), K. Hibi (Shimizu model overestimated the reattachment length behind the Corp.), S. Murakami (Keio Univ.), R. Yoshie (Maeda Corp.) building in comparison with the standard k-ε model in Test Cases A and B. Appendix 1 Outline of computational conditions 3) The LK and RNG models provided more accurate specified by the organizer results than did the standard k-ε model in the area around 1) Computational domain: the side face of the building near the ground surface in The computational domain covers the specified sizes, which corresponds Test Case B. to the size of the wind tunnel in the experiment. The computational 4) In the latter part, the flowfield within a building domain was divided into a specified number of grids. The size of the computational domain, grid discretization and the minimum grid interval complex in an actual urban area (Test Case C) was are summarized in Table 4. predicted by three different CFD codes based on different 2) Inflow boundary: grid systems. Results of these predictions were compared At the inflow boundary, the interpolated values of <u> and k obtained with experimental data. No clear differences were from the experimental results are imposed. The vertical profile of mean observed between the CFD results given from these three velocity <u(z)> approximately obeyed the power law expressed as <u(z)>∝z in the experiment. The value of ε is obtained from the relation codes for this test case under the computational Pk=ε. The α value for each test case is shown in Table 4. conditions specified by the organizer. 3) Ground surface boundary [18]: 5) The CFD codes compared here can predict the In these cross comparisons, the wall function based on the logarithmic distribution of the scalar velocity at pedestrian level law of the form containing the roughness length z is employed. This is within the actual building complex in reasonable mainly because the velocity profile should be maintained in the area agreement with the measurements except for the wake apart from the building. z values for each test case are shown in Table 4. The friction velocity u* is obtained from the relation using the value of region and the region far from the target buildings where k at the closest point to the ground in the experiment. It was confirmed the grid resolution is obviously not fine enough. in the preliminary calculation without the building model that the profile at inflow was maintained at the outflow boundary with this boundary Acknowledgements condition. Regarding the boundary condition for the ground surface near The authors would like to express their gratitude to the buildings, more detailed investigation will be done in the next stage of this project. the members of working group for CFD prediction of 4) Lateral and upper surfaces of computational the wind environment around a building [cf. Note]. JAABE vol.3 no.1 May. 2004 Yoshihide Tominaga 69 Table 4 Computational conditions domain: 3) Kato, M. and Launder, B.E. (1993), “The modeling of turbulent In Test Case A, the wall functions based on a logarithmic law for a flow around stationary and vibrating square cylinders”, Prep. of smooth wall are used. 9th Symp. on Turbulent shear flow, 10-4-1-6 In Test Cases B and C, the normal velocity components defined at the 4) T.Tamura, H. Kawai, S. Kawamoto et al(1997), “Numerical boundaries and the normal gradients of the tangential velocity prediction of wind loading on buildings and structure - AIJ components, k, ε across the boundaries, were set to zero. cooperative project on CFD”, J. of Wind Eng. and Ind. Aerodyn 5) Building surface boundary: 67&68, 671-685 The wall functions based on logarithmic law for a smooth wall are used. 5) D. Lakehal, W. Rodi(1997), “Calculation of the flow past a surface- 6) Downstream boundary: mounted cube with two-layer turbulence models”, J. Wind Eng. Zero gradient condition is used for all velocity components, k and ε. Ind. Aerodyn.,67&68(1997) 65-78 Appendix 2 Grid arrangements employed in Test Case C 6) Ishihara,T. and Hibi,K. (1998), “Turbulent measurements of the Code M: A structured grid system was employed. The whole flow field around a high-rise building”, J. of Wind Eng., Japan, computational domain was divided into 150×140×38 grids. The target No.76, 55-64(in Japanese) buildings were surrounded by 2m×2m grids. 7) Murakami,S., Mochida, A. and Ooka, R. (1993), “Numerical Code D: An unstructured grid system with prismatic cells over the ground simulation of flowfield over surface-mounted cube with various and building surface was used. The whole computational domain was second-moment closure models”, 9th Symp. on Turbulent Shear divided into 800,000 using Tetra, Pyramid and Prism cells. The distance Flow,13-5 from solid surfaces of ground and building to the first interior grid point 8) Kataoka,H. and Mizuno, M. (2002), “Numerical flow computation was set to about 0.6m. around aeroelastic 3D square cylinder using inflow turbulence”, Code O: An overlapping structured grid system was employed. The whole Wind and Structures, Vol. 5, No. 2-4, pp.379-392 computational domain was divided into 250,000. The grid interval was 9) Tominaga, Y. , Mochida, A. and Murakami, S.(2003) “Large Eddy 5m in the horizontal directions. The sub-computational domain was Simulation Flowfield around a High-rise Building”, 11th divided into 250,000. The grid interval in the horizontal directions was ICWE,B10.5 2m. The distance between the ground surface and the first interior grid 10) Yakhot, V. and Orszag,S.A, (1986), “Renormalization group point was set to about 0.7m. analysis of turbulence”, J. Sci. Comput. 1, 3 Appendix 3 11) Tsuchiya, M., Murakami, S., Mochida, A., Kondo, K. and Ishida,Y. The mean scalar velocity measured in the wind tunnel using a non- (1997), “Development of a new k-e model for flow and pressure directivity thermistor anemometer (S ) is regarded as the time averaged fields around bluff body”, J. of Wind Eng. and Ind. Aerodyn. 67/ exp instantaneous scalar velocity, which can be expressed as: 68, 169-182 2 2 2 1/2 S =<(u +v +w ) >. 12) Tominaga, Y. and Mochida, A. (1999), “CFD prediction of flowfield exp On the other hand, the mean scalar velocity given from k-ε model (S ) and snowdrift around building complex in snowy region”, J. Wind. k-ε is the calculated from the time averaged velocities vector, namely, Eng. Ind. Aerodyn. 81, 273-282 2 2 2 1/2 S =(<u> +<v> +<w> ) . 13) Durbin,P.A. (1996), “On the k-e stagnation point anomaly”, Int. J. k-ε Thus, the output of the thermistor anemometer is larger than that given Heat and Fluid Flow, 17, 89-90 from the k-e model. 14) T.H. Shih, W. W. Liou, A. Shabbir, Z. Yang and J. Zhu(1995), “A 2 2 2 1/2 S =<(u +v +w ) > New k-e Eddy Viscosity Model for High Reynolds Number exp 2 2 2 1/2 =<{(<u>+u’) +(<v>+v’) +(<w>+w’) } > Turbulent Flows” Computers Fluids Vol. 24 No.3 pp.227-238 2 2 2 2 2 2 1/2 =<(<u> +<v> +<w> +<u’ +v’ +w’ >) > 15) T.H. Shih, J. Zhu, J.L. Lumley(1993), “A realizable Reynolds stress 2 2 2 1/2 =(<u> +<v> +<w> +2k) algebraic equation model”, NASA TM-105993 2 1/2 =(S +2k) 16) Nagano, Y. and Hattori, H. , (2003)” A new low-Reynolds number k-ε Here, u,v,w: three components of instantaneous velocity vector, <f>: turbulence model with hybrid time-scale of meanflow and time-averaged value of f, f ’=f-<f>. turbulence for complex wall flow”, Proc. 4th Int. Symp. On Turbulence, Heat and Mass Transfer(Eds. K. Hanjalic, Y. Nagano and F. Arinc), Antalya, Turkey, October 12-17 References 17) Kataoka,H., (2003) “Large Eddy Simulation of building”, 1) Murakami, S., Mochida, A. and Hayashi, Y. (1990),”Examining Summaries of Technical Papers of Annual Meeting, Environ. Engg. the k-e model by means of a wind tunnel test and large eddy II, AIJ (in Japanese) simulation of turbulence structure around a cube”, J. Wind Eng. 18) Yoshie,R. (1999), “CFD analysis of flow field around a high-rise Ind. Aerodyn. 35, 87-100 building”, Summaries of Technical Papers of Annual Meeting, 2) Murakami,S. (1993), “Comparison of various turbulence models Environ. Engg. II, AIJ (in Japanese) applied to a bluff body”, J. Wind Eng. Ind. Aerodyn., 46&47, 21- 70 JAABE vol.3 no.1 May. 2004 Yoshihide Tominaga
Journal of Asian Architecture and Building Engineering – Taylor & Francis
Published: May 1, 2004
Keywords: CFD; wind environment assessment; cross comparison; revised k-e models; actual urban area
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