Cooperative roject for CFD rediction of edestrian ind nvironment in the Architectural Institute of Japan

EACWE4 The Fourth European & African Conference on Wind Engineering J. Náprstek & C. Fischer (eds); ITAM AS CR, Prague, 11-15 July, 2005, Paper #292 Cooperative roject for CFD rediction of edestrian ind nvironment in the Architectural Institute of Japan R. Yoshie 1, A. Mochida 2, Y. Tominaga 3, H. Kataoka 4, K. Harimoto 5, T. Nozu 6, T. Shirasawa 7 ABSTRACT: CFD is being increasingly applied to the prediction of the wind environment around actual high-rise buildings. Despite this increasing use, the prediction accuracy and many factors that might affect simulation results are not yet thoroughly understood. In order to clarify ambiguities and make a guideline for CFD prediction of the wind environment, a working group was organized by the Architectural Institute of Japan. This group has carried out various comparative studies as follows. First stage: Flowfields around two types of single high-rise buildings. Second stage: Flowfield around a high-rise building located in a city. Last stage: Flowfields around two types of Building Complexes in actual urban areas. This paper describes some of the results of the investigation by the working group, and discusses the influences of various calculating conditions on CFD results, and also on the present status and the problems in CFD prediction of the wind environment. 1 INTRODUCTION Progress in high-speed processing by personal computer and rapid propagation of software for numerical analysis of fluid dynamics in recent years have enabled prediction of the pedestrian wind environment around high-rise buildings based on CFD (Computational Fluid Dynamics). It is becoming common for calculation to be performed for 16 wind directions on the situation of before and after construction of buildings, and for the pedestrian wind environment to be assessed by probability evaluation. However, there have been very few reports on the prediction accuracy of CFD simulations of the pedestrian wind environment around buildings in urban areas. Furthermore, the influences of various calculation conditions (such as size of computational domain, grid resolution, boundary conditions, selection of turbulence model, etc.) on the results of CFD simulation are not yet thoroughly understood. Thus, a working group named Working Group for CFD Prediction of the Wind Environment around a Building has been organized by the Architectural Institute of Japan. The name of this working group has subsequently been changed to Working Group for Preparation of Wind Environment Evaluation Guideline based on CFD. Since its inception, it has been making continuous efforts to prepare guideline for proper use of CFD for calculation of the wind environment. Comparative and parametric studies have been carried out on several building configurations to elucidate the problems on setting or selecting various calculation conditions and turbulence models for CFD simulation of the pedestrian wind environment in urban areas. The present article introduces some of the results achieved by the working group and discusses the influence of calculation conditions and turbulence models on CFD calculation results and also on the present status and problems in CFD prediction of the pedestrian wind environment around buildings. 2 GENERAL FEATURES OF COMPARATIVE AND PARAMETRIC STUDIES Figures 1-6 show models for comparative and parametric studies as investigated by theworking group. The results of studies will be introduced here on the flowfield around a single square prism of 2:1:1 (height:width:depth) placed in a turbulent 1 Prof., Tokyo Polytechnic University, e-mail yoshie@arch.t-kougei-ac.jp 2 Assoc. Prof., Graduate School of Engineering, Tohoku University, e-mail mochida@sabine.pln.archi.tohoku.ac.jp 3 Prof., Niigata Institute of Technology, e-mail tominaga@abe.niit.ac.jp 4 Chief Research Engineer, Technical Research Institute, Obayashi Corp., e-mail kataoka.hiroto@obayashi.co.jp 5 Research Engineer, Technology Center, Taisei Corp., e-mail kazuyoshi.harimoto@sakura.taisei.co.jp 6 Research Engineer, Institute of Technology, Shimizu Corp., e-mail nozu@shimz.co.jp 7 Research Associate, The University of Tokushima, e-mail shirasawa@ce.tokushima-u.ac.jp 1

The Fourth European & African Conference on Wind Engineering, Paper #292 boundary layer flow (Figure 1), the flowfield around a high-rise building located in a city (Figure 4), and flowfields around building complexes in actual Urban areas in Niigata and Shinjuku, Japan (Figures 5 and 6). In the studies discussed here, the standard k- model or modified k- models or DSM were used, but LES (Large Eddy Simulation) was not applied except for flowfields around two types of single prisms (Figures1 and 2). It is desirable to use LES for highly accurate CFD. However, it is very difficult to use because it requires a lot of time for calculation in practical analysis due to the limited conditions of computer resources currently available. This is because, prediction and evaluation of the wind environment around buildings in practical application requires a wide computational domain including surrounding building groups and a vast number of grids associated with it. In addition, a number of calculation cases (such as multiple wind directions, situations before and after construction of a building under planning, and measures after construction) are required, and time for evaluation is also limited in the practical design stages. Therefore, the guideline currently under preparation in the working group is also based on the assumption that the analysis is performed using standard k- model or modified k- models. b Wind H=2b wind 4b Figure 1 Single high-rise building (2:1:1 square prism) b b 4b Figure 2 Single high-rise building (4:4:1 square prism) Figure 3 Simple city block Figure 4 A high-rise building in city Figure 5 Building complexes in actual Urban areas (Niigata) Figure 6 Building complexes in actual Urban areas (Shinjuku) 3 FLOWFIELD AROUND SINGLE SQUARE PRISM of 2:1:1 3.1 General outlines of wind tunnel experiment In the comparative and parametric studies on the flow around a square prism of 2:1:1 as carried out in the first step of the working group s investigation, the experimental results by Meng and Hibi 1) were used to verify the results of CFD simulation. In this experiment, detailed measurement was made of the flow field around a 2:1:1 (height : width : depth) shaped square prism placed in a turbulent boundary layer, in which the exponent for the power law of the vertical profile of average wind speed was approximately 0.27 (Figure 7). A split film probe was used to measure wind velocity, and the average wind velocity in each direction of 3-dimensional space and the standard deviation of fluctuating wind velocities were determined. The model building was 0.08m square (b and d) and 0.16m high (h). The turbulence statistics were measured on a vertical cross-section (Figure 8(a)) and on horizontal planes at 1/16 (z/b = 0.125) and 10/16 (z/b = 1.25) of the building height (Figure 8(b)). 3.2 Calculation conditions for comparative study (standard calculation conditions) In the working group, the conditions shown in Table 1 and Figures 9 and 10 were given as the standard calculation conditions for the comparative studies (hereinafter referred as standard calculation conditions ). In addition to the standard calculation conditions, we investigated the influence on the calculation results of changing the boundary conditions, the computational domain, the grid resolution, and the turbulence models, etc. 0.27 U z b 0.08m h 0.16m Figure 7 Configuration of experimental model and 2

R. Yoshie, A. Mochida, Y. Tominaga, H. Kataoka, K. Harimoto, T. Nozu, T. Shirasawa approaching wind speed profile (a) Measuring points in vertical cross-section (y=0) (b) Measuring points in horizontal plane (z=0.125b and 1.25b) Figure 8 General outlines of wind tunnel experiment Side wall of wind tunnel Side wall of wind tunnel (a) Horizontal plane Table 1 Standard calculation conditions ceiling ceiling ceiling Ceiling of wind tunnel Floor of wind tunnel (b) Vertical section Figure 9 Computational domain and grid arrangement height from floor Inflow B.C. Exp. height from floor Inflow B.C. Exp. height from floor Figure 10 Inflow boundary conditions Inflow B.C. 3.3 Calculation results by standard k- model based on standard calculation conditions. The CFD results utilizing the standard k- model and based on the standard calculation conditions are compared below with experimental results of average wind velocities. 1) Wind velocity distribution on vertical crosssection The distribution of average wind velocity U and W on the vertical cross-section at the center of the building is shown in Figures 11 and 12. In the Figures, the longitudinal dotted lines represent the positions of the measuring lines in the experiment. Wind velocities are plotted transversely using this as the origin. (Positive values are plotted on the right side of the measuring line, and negative values on the left side.) The calculation values agree relatively well with the experimental values. Near the roof surface of measurement line x/b=-0.25 (the third measuring line from the left), U is negative in the experiment and reverse flow occurs, but this is not reproduced in the calculation. On the lower portion of measuring line x/b=3.25 (the rightmost measuring line), calculated U is lower than the experimental value. 2) Wind velocity distribution on horizontal crosssection The distributions of U and V on the horizontal plane (z/b = 0.125) near the ground surface are shown in Figures 13 and 14, respectively. The calculation values and the experimental values agree relatively well except that the calculated U is lower than the experimental value in the wake region. The reattachment length behind the building is longer in the calculation. 3

The Fourth European & African Conference on Wind Engineering, Paper #292 3) Wind speed increase ratio near the ground surface Figure 15 compares the experimental and calculated scalar wind velocity. The scalar wind velocity (wind speed) near the ground surface (z=0.125b) is normalized according to the wind speed at the same height when there is no building (i.e. wind speed increase ratio). The results based on the modified k- models (Launder-Kato type k- model 2) (LK) and Re-Normalization Group k- model (RNG) ) are also given. If it is limited to the wind speed increasing region (region where wind speed increase ratio is 1.0 or more), which is important in the evaluation of the pedestrian wind environment, it is predicted within an accuracy of approximately ±10%. However, in the low wind speed region behind the building, the wind speed ratio is evaluated lower in the calculation than in the experiment. When the modified k- models are compared with the standard k- model, prediction accuracy is slightly higher in the modified models in the strong wind region, while it is lower in the weak wind region. The reattachment length behind the building is longer in the modified k- models than in the standard k- model. Figure 11 Distribution of U in vertical section (y=0) Figure 12 Distribution of W in vertical section (y=0) Figure 13 Distribution of U in Horizontal section (z=0.125b) Figure 14 Distribution of V in Horizontal section (z=0.125b) (a) Standard k-model (b) LK k- model Figure 15 Wind speed increase ratio near floor (z=0.125b) (c) RNG k- model 4

R. Yoshie, A. Mochida, Y. Tominaga, H. Kataoka, K. Harimoto, T. Nozu, T. Shirasawa 3.4 Influence of various calculation conditions on calculation results Here, the results obtained by changing the calculation conditions are summarized without showing Figures. Furthermore, the findings obtained from the benchmark test on the flow field around a square prism of 4:4:1 (Figure 2) are also given. (Detailed information on the studies is in references 3) - 7).) 1) When the modified k- models were used, a reverse flow on the roof was reproduced, and the prediction accuracy in the strong wind region near the separation region closer to the ground surface was improved. However, in the region behind the building, the reattachment length was longer than for the standard k- model, and agreement with the experimental results deteriorated. 2) When LES was performed, the prediction accuracy in the flowfield behind the building was dramatically improved. This is mainly because the periodic vortex shedding behind the square prism was well reproduced by LES 5). 3) When calculation was conducted on a finer grid (by decreasing the grid width of the standard calculation grid to 1/2), the results were very close to those for the standard mesh. Thus, the grid arrangement of the standard condition was sufficient. 4) When the standard computational domain (21b 13.75b 11.25b) was narrowed down to a small region (13.8b 7.56b 7.75b), there was almost no change in the results. 5) When k and in the inflow were varied, the calculation results varied widely. Thus, it is important to provide appropriate values for k and. 6) When a first-order upwind scheme was used for advection term, the velocity distribution at the side region of the building, where wind enters the computational grids diagonally, become less steep. This is not desirable. 7) Comparative studies performed by unifying the calculating conditions showed small differences between the calculation results for three commercial codes and two self-made codes. wind tunnel experiment was carried at the Niigata Institute of Technology. The low-rise urban block was assumed to be 40m square and 10m high as shown in Figure 16 (simulating a condition where low-rise houses are densely jammed), with a highrise building 25m square and 100m high (1:1:4) in a block at the center of this area. One urban block is assumed to be enclosed by two roads (each 10m wide) and roads 20m and 30m wide. The wind velocity measuring points are shown in Figurer17. The scale of the experimental model was 1/400 and the measuring height was 5mm above the floor of the wind tunnel (2m above ground in real scale). Wind velocity was measured in three wind directions (0, 22.5 and 45 ) using a thermister anemometer. In addition, for wind direction 0 only, wind velocity was measured using a split film probe. The inflow wind velocity U H at the height of the central high-rise building H (H=250mm in the experiment and 100m in real scale) was 6.61 m/s. Figure 16 General features of wind tunnel experiment 40m 20m 40m 30m 40m Figure 17 Measuring points 10m 10m Experiment Scale: 1/400 Measuring height 4 FLOWFIELD AROUND HIGH RISE- BUILDING LOCATED IN CITY This chapter describes the results of the study on the flowfield near a high-rise building in a typical (regular) urban block. 4.1 General features of wind tunnel experiment The flowfield analyzed here is that around a highrise building in a simple urban area, for which the 4.2 General outline of calculation The problems with the CFD analysis on the urban area, as described above, are: (1) How wide should the computational domain be maintained in the horizontal and vertical directions? (2) How fine should the grid resolution be? (3) To what extent should the surrounding urban blocks be reproduced? (4) What model should be used as a turbulence 5

closure? Based on the standard calculation conditions shown in Table 2 and Figure 18, the prediction accuracy of CFD simulation was examined. By varying the calculation conditions of (1)-(4) above, the influences of the calculation conditions on the CFD results were investigated. Table 2 Standard calculation conditions y The Fourth European & African Conference on Wind Engineering, Paper #292 x (a) Whole computational domain and grid resolution High-rise building was divided into 12(x)12(y)27(z) (b) Macrograph of central area Figure18 Computational domain and grid resolution for standard calculating condition 4.3 Comparison of CFD results with experimental results based on standard calculation conditions The calculation results based on the standard calculation conditions and the experimental results are compared in Figure 19(a) (wind direction 0 ) and in Figure 19(b) (wind direction 45 ). The wind speed ratio between the scalar wind velocity and U H at the measuring point is represented on the ordinate. At measuring points 35, 38 where the wind velocity was highest for wind directions 0 and 45, respectively, the calculation results were about 16% lower than the experimental results, while relatively good matching was observed for the other strong wind regions. (a) Wind direction0 (b) Wind direction45 Figure 19 Comparison between CFD based on standard calculation conditions and experiment 4.4 Influence of various calculation conditions on CFD analysis results 1) Influence of size of horizontal computational domain The calculation was carried out in experimental scale. To evaluate the influence of the horizontal computational domain, it was expanded from the standard domain of 1.8m 1.8m to one of 3.6m 3.6m, and contracted to one of 1.5m 1.5m, which is near the rim of the surrounding block. The results are shown in Figure 20. When the horizontal computational domain was large (3.6m 3.6m), the wind speed tended to slightly decrease with the decrease of the obstruction ratio in the horizontal direction. On the other hand, when the calculation was carried out in the smaller domain (l.5m 1.5m), the wind speed became higher. The wind speed change for the small domain was larger than that for the large domain despite the fact that the contraction was only 20% for the small domain whereas the expansion was 200% for the large domain. Therefore, it is desirable to expand the horizontal computational domain to a certain extent outside the rim of the surrounding urban block. Figure 20 Influence of horizontal computational domain 6

2) Influence of vertical computational domain Figure 21 shows the results obtained when the vertical computational domain was lowered from the standard height of 7.2H to 3H and 2H. When the upper computational domain was 2H, the wind speed was just slightly higher. There was almost no difference between the cases of 7.2H and 3H. It appeared that no substantial problem occurred even when the vertical computational domain was lowered to about 3H. Figure 21 Influence of vertical computational domain 3) Influence of grid resolution Figure 22 shows the calculation results when a fine grid and a coarse grid were used. For the fine grid (215 (x) 202(y) 101 (z) = 4,386,430 meshes), the grid width was set to about 1/1.5 of the standard grid in all three directions x, y and z. For the coarse grid (74 (x) 68 (y) 48 (z) = 241,536 meshes), it was about 1.5 times the standard grid. The difference between the calculation results for the standard grid and the fine grid was very small. The difference between the calculation results for the coarse grid and the other cases was also small. The standard grid would be satisfactory, i.e. with one side of the highrise building divided into 10 portions or more. R. Yoshie, A. Mochida, Y. Tominaga, H. Kataoka, K. Harimoto, T. Nozu, T. Shirasawa Figure 22 Influence of grid width 4) Influence of reproduction range of surrounding urban blocks Figure 23 shows the results of calculation with two rows and three rows each deleted from the peripheral region of the surrounding urban blocks, as shown in Figure 22. The difference from the standard case was very small except at measuring points 1, 2, 3 and 4 on the roads on the windward side. Therefore, the reproduction range of the surrounding urban blocks would be satisfactory for practical application if two or more were maintained in the surroundings of the region to be evaluated. 5) Influence of modification on turbulence modelling Figure 25 shows calculation results based on the modified k- models of Launder-Kato (LK) and RNG. At measuring points 35, 38, etc., where the wind speed was highest, that of the modified k- models was evaluated as higher than that of the standard k- model, and matching with the experimental results was improved. However, in the weak wind regions such as at measuring points 15 25, where the wind speed was low, matching with the experimental results deteriorated. (a) deleting 2 rows (b) deleting 3rows Figure 23 Reproduction range of surrounding urban blocks Figure 24 Influence of reproduction range of surrounding urban blocks Figure 25 Influences of deferent turbulence models 4.5 Summary According to the results of the present study, the influence on the calculation results of the computational domain, the grid resolution, and the reproduction range of the surrounding urban block was relatively low. In the calculation for practical application, the condition setting criteria would be as follows: two or more urban blocks each of several tens of meters should be reproduced in the area surrounding the region to be evaluated, and the upper space region should be maintained at 3H or more, and one side of the high-rise building should be divided into 10 portions or more. If it is limited to the highest wind region, which is important for evaluation of the pedestrian wind environment around the building, the wind speed difference between CFD and experiment was 16% at most for the standard k- model. For the LK model and the RNG model, more accurate prediction can be made in the strong wind region. 7

The Fourth European & African Conference on Wind Engineering, Paper #292 5 FLOW FIELD IN ACTUAL URBAN AREA NIIGATA Up to this point, we have reported results of bench mark tests for relatively simple shapes such as single buildings and relatively regular model urban blocks. In actual urban areas, however, buildings have complicated shapes and are distributed in an irregular manner. In order to accurately reproduce them in CFD simulation, a great number of meshes are required. In particular, when an orthogonal structured grid system is used, it is difficult to provide a grid configuration that matches well with the building configuration, and special care must be taken to allow for the influence of mismatching on the prediction accuracy. This problem can be solved if an unstructured grid system is used, although there are some difficulties in preparing this kind of grid. Furthermore, for the wind environment in urban areas, prediction is normally made for 16 wind directions on two patterns, i.e. before and after the construction of the building under planning. In some situations, it is necessary to consider protection against wind such as planting trees. This increases the number of cases that need to be considered, and calculation accuracy must be maintained under restrictive conditions for practical application. This chapter describes a study in an actual urban area in Niigata, where low-rise houses are jammed closely together. Wind tunnel experiments and CFD simulation were performed to predict the wind speed distribution and to assess the pedestrian wind environment, and the results were compared. Inflow Boundary Computational domain Upper surface of computational domain Furthermore, the differences are shown between 3 types of grid system: a single structured grid system (orthogonal mesh), an overlapping structured grid system, and an unstructured grid system 7), 8). 5.1 Urban area model under study and outline of wind tunnel experiment The study was performed on an urban area model. This model consisted of an actual city block in Niigata city, Niigata prefecture, Japan with low-rise houses jammed closely together. A target building 60m high (Building A) and two target buildings 18m high (Buildings B and C) were assumed to be constructed (Figure 26 and 27). Wind tunnel experiments at 1/250 scale were performed on this model in a turbulent boundary layer with a power law exponent of 0.25. Scalar wind velocities at 8mm above the wind tunnel floor (2m above the ground surface in real scale) were measured by multi-point thermister anemometers. 5.2 General outline of numerical calculation The items shown in Table 3 were specified as common calculation conditions in the comparative study. For the configuration of the urban block, input data for each CFD code were prepared from the same CAD data obtained from the drawing of the wind tunnel model. The features of the compared CFD codes and the different calculation conditions are summarized in Table 4, as well as general features of the grid systems used in each CFD code. Table 3 Common calculation conditions specified Interpolated values of U and k from the experimental approaching flow. CD1/2kdU/dzPk Area about500m (x) 500m (y) 300m (z) that includes the whole urban block Free slip wall condition Outflow Boundary condition Zero gradient condition Ground surface boundary Logarithmic law with roughness length z 0 (z 0=0.024m) Figure 26 Actual urban model (CAD data) Building surface boundary Logarithmic law for smooth wall CFD Code Table 4 Outline of CFD codes and calculation conditions O Code M Code T Self-made code Commercial Code Commercial Code Computational method Overlapping structured grid Structured grid Unstructured grid and time integral scheme Artificial compressibility SIMPLE, steady state Simple, steady state Turbulence model Standard k- Standard k- Standard k- Scheme for advection term 3 rd -order Upwind QUICK MUSCL(2 nd -order) Grid arrangements 8

5.3 Results of numerical analysis 1) Comparison based on wind speed ratio CFD simulations were conducted for 16 wind directions. Here, prediction results and experimental results of wind speed ratio were compared for the wind direction NNE, which is the wind direction most frequently occurring in Niigata. The wind speed ratio is the ratio of wind speed (scalar velocity) at each measuring point (height=2m) and the wind speed at the same height at the inflow boundary. There was no substantial difference among codes for overall distribution of wind speed ratio. As a representative example, the distribution of wind speed ratio based on CFD code T (Table 4) is shown in Figure 27. Regions with very high wind speed were found at the corners on the northwest and east sides of Building A. Furthermore, strong wind caused by contraction flow was seen between Building B and Building C. Figure 28 represents the correlation of wind speed ratio obtained from CFD codes with the results of wind tunnel experiments. Plotting is shown separately inside and outside the wake region of the target buildings. The prediction results in the CFD codes were almost identical, and there was no clear difference among the codes. In the wake region of the target buildings, there was a tendency to underestimate the wind speed compared with the results of the wind tunnel experiment, while in other regions the matching was relatively satisfactory. The CFD results often tended to underestimate the wake region except for wake region R. Yoshie, A. Mochida, Y. Tominaga, H. Kataoka, K. Harimoto, T. Nozu, T. Shirasawa wake region except for wake region Target Bldg. (60m) Wake region In the vicinity of Bldg. Target Bldg. (10m) Figure 27 Distribution of wind speed ratio near ground surface (z=2m)(code T) wind speed in the wake region of the building in benchmark tests on other configurations. Figure 29 compares the wind speed ratios at each measuring point. For the positions of the measuring points, see Figure 30. The CFD results generally agree well the results of the wind tunnel experiment. In particular, the prediction accuracy is high for except for the wake region & near building. The difference from experimental results was large at several measuring points, but these were mostly in alleys in the wake region of the target buildings. This may be because a slight difference in the prediction of the separation shear layer due to the difference in reproducibility of the building configuration may have influenced the calculation results, and because there were shape errors in the actual wind tunnel model and CAD data used, and also errors in the positions of the evaluation point. (a) Code O (b) Code M (c) Code T Figure 28 Correlation of wind speed ratio between CFD result and experimental result (wind direction NNE) wake region except for wake region normalized scalar velocity Wind speed ratio wake w region region + & 1.4near in the vicinity building of bldg. 1.2 1 0.8 0.6 0.4 0.2 0 23 58 62 wake region + & except except for for wake w region region + & except for wwake region region + & far far away ay from bldg. building far away far ay from bldg. building near in the building vicinity of bldg. Exp. Code CodeM Code 72 35 48 51 54 66 69 78 3 14 24 27 30 42 56 63 1 8 11 17 20 32 40 Figure 29 Comparison of wind speed ratio at each measuring point (wind direction NNE) 76 9

2) Comparison based on criteria for assessing wind environment A rank evaluation was performed on the CFD prediction results according to criteria for assessing the wind environment proposed by Murakami et al. based on the occurrence frequency of daily maximum gust wind speed 9) using observation data from the Niigata Regional Meteorological Observatory. The results are summarized in Figure Exp. 1 1 2 3 4 12 The Fourth European & African Conference on Wind Engineering, Paper #292 11 21 10 9 20 32 19 8 7 33 6 18 45 5 16 17 31 4 44 24 2 43 3 13 14 15 57 25 42 41 26 27 56 58 63 40 22 29 60 23 28 38 39 61 64 30 62 51 71 72 73 75 37 36 52 59 34 35 54 70 53 69 76 55 68 46 48 49 50 74 80 47 67 79 66 78 30. The gust factor G.F. was assumed to be 2.5. Including the results at the measuring points with rank 4 on the northeast and south sides of Building A, the CFD results generally showed good matching with the wind tunnel experiment results. However, as described above, there were differences between some of the experimental results and CFD codes for the measuring points near low-rise houses in alleys or along large avenues. Code O 1 O 1 2 3 4 12 11 21 10 9 20 32 19 8 7 33 6 18 45 5 16 17 31 4 44 24 2 43 3 13 14 15 57 25 42 41 26 27 56 58 63 40 22 29 60 23 28 38 39 61 64 30 62 51 71 72 73 75 37 52 59 36 34 35 54 70 53 69 76 55 68 46 48 49 50 74 80 47 67 79 66 78 M 1 2 3 4 65 Code M 8 6 7 18 4 5 16 24 17 12 2 3 13 14 15 25 26 27 22 23 28 29 38 39 30 37 51 36 52 34 35 54 53 46 48 49 47 67 50 55 66 1 77 9 19 33 45 31 44 43 42 57 41 56 58 63 40 60 61 64 62 71 72 73 75 59 70 69 76 68 11 21 10 20 32 74 80 79 78 Code T T 1 2 3 4 65 8 6 7 18 4 5 16 24 17 12 2 3 13 14 15 25 26 27 22 23 28 29 38 39 30 37 51 36 52 34 35 54 53 46 48 49 47 67 50 55 66 1 77 9 19 33 45 31 44 43 42 57 41 56 58 63 40 60 61 64 62 71 72 73 75 59 70 69 76 68 11 21 10 20 32 74 80 79 78 65 77 Figure 30 Comparison of rank for criteria for assessing wind environment at each measuring point 6 FLOW FIELD IN CASE OF ACTUAL URBAN AREA (SHINJUKU) 6.1 General description of wind tunnel experiment and field measurement to be compared To verify the CFD prediction results, it is important to compare them not only with the wind tunnel experiment but also with field measurement. However, adequate field measurement results are not always available, and this has almost never been performed in the past. Thus, a benchmark test was conducted on the Shinjuku Sub-central Area in Tokyo, Japan in its early development stage, for which detailed wind tunnel experiments and field measurements had been carried out in cooperation with many research organizations during 65 construction 10,11), and the validity of the prediction accuracy of CFD was assessed. 1) Wind tunnel experiment A number of wind tunnel experiments had been performed on the Shinjuku Sub-central Area. Here, the CFD simulations were carried out based on the condition of Experiment for 1977. 2) Field measurement Field measurements were carried out from December 1975 to November 1983. The present CFD simulations were performed for 1977 when the situations of field measurement were similar to those of the wind tunnel experiment model. In the field measurement, three-cup anemometers were used. The measurement heights differed according to the measuring point, being 3-9m above the ground 77 10

R. Yoshie, A. Mochida, Y. Tominaga, H. Kataoka, K. Harimoto, T. Nozu, T. Shirasawa surface. The reproduced urban area and the measuring point distribution are shown in Figure 31. 6.2 General outline of numerical calculation As for the study on the urban area of Niigata City, common calculation items were designated. For the configuration of urban blocks, no wind tunnel experiment models at the time of measurement were available. Thus, CADs on the urban area configuration and topography at the time of measurement were obtained from the drawings, the photographs, and white maps at the time of measurement. These data were then used to obtain input data of CFD analysis code. Because no details of the models on topographical height difference were available, reproduction was made stepwise every 5 meters by referring to the maps used at the time of measurement. The CAD data thus prepared are shown in Figure 32. Figure 33 shows the grid arrangements of the CFD codes. Here, only CFD_A uses a structured grid system, while the others are based on a non-structured grid. However, CFD_A uses an overlapping grid, and the range of grid resolution in different horizontal regions is shown in Figure 31. In the comparison given below, measurement values for standard wind speeds of 5m/s or more were extracted from the observation data in the year 1977. The wind speed ratio with the standard wind speed was obtained for each measuring point, and the average value for each wind direction was used as the measurement value. D Finely divided region in CFD_A Coarsely divided region in CFD_A Intermediate region in CFD_A C Figure 31 Urban area reproduced and measuring points Figure 32 CAD data of urban area Around high-rise buildings Around high-rise buildings Around high-rise buildings Around low-rise buildings Around low-rise buildings Around low-rise buildings (a) CFD_A (b) CFD_B (c) CFD_C Figure 33 Grid arrangements of CFD codes 11

The Fourth European & African Conference on Wind Engineering, Paper #292 6.3 Comparison of CFD results with wind tunnel experiment results and field measurements Similarly to the wind tunnel experiment and the field measurement, the wind speed obtained by CFD was normalized by the wind speed at standard points. The standard points were the top of the Shinjuku Mitsui Building (D in Figure 31; height of observation 237m) for the wind directions NE - N - NW, and the top of the KDD Building (C in Figure 31; height of observation 187m) for the other wind directions. Figure 34 compares the experimental results and the field measurements for wind speed ratios at representative measuring points. As a general trend, the wind tunnel experiment results are within the standard deviation of the field measurements, and the CFD results are also generally within the same range. The CFD results deviate from the experiment results and field measurements in some cases, depending on the wind direction. This may have been caused by problems of reproduction accuracy of the prepared CAD data. Depending on wind direction, there are also differences among codes. In general, the CFD_B results showed good agreement with the experiment results and field measurements. This may be because the grid resolution around the building was finer for CFD_B (Figure 33), which may suggest that the grid resolution in the target region is important. Because an overlapping grid is used in CFD_A, where the measuring points are in intermediate regions with lower resolution such as measuring points No. 6 and No. 7 (Figure 31), the reproducibility of the surrounding low-rise houses is not satisfactory compared with CFD_B and CFD_C, and this may have influenced the prediction results. Next, Figure 35 compares the wind speed ratios at the measuring points with wind direction S. For the reasons described above, there were differences at some measuring points in CFD_A. In general, however, the CFD results showed good matching with the experimental results and field measurements. 6.4 Summary Wind environment prediction by CFD was performed for the flow fields around high-rise buildings in the Shinjuku Sub-central Area. Through comparisons of the CFD results with field measurements and wind tunnel experiment results, the following findings were obtained: In regions around the high-rise buildings with sufficient grid resolution, CFD results agreed well with wind tunnel experiment results and field measurements. Wind speed ratio Wind speed ratio Wind speed ratio Wind speed ratio However, in regions such as around low-rise houses where the grid resolution strongly influences the reproducibility of configurations, differences were seen in the CFD results due to the differences in grid resolution. Furthermore, CAD data used as the basis for the urban block model in the CFD analysis did not completely match the wind tunnel model and real urban block. This may have been one of the causes of the difference among the experimental results, field measurement results, and the CFD analysis results. No.6 Field meas.(mean) Field meas.() Target wind tunnel exp. Other wind tunnel exp. No.7 No.13 No.15 Figure 34 Comparison of wind speed ratio for 16 wind directions 12

Wind speed ratio R. Yoshie, A. Mochida, Y. Tominaga, H. Kataoka, K. Harimoto, T. Nozu, T. Shirasawa Measuring Point Figure 35 Comparison of wind speed ratio at each measuring point with wind direction S 7 CONCLUSION CURRENT STATUS AND PROBLEMS IN CFD PREDICTION This paper has described some results of a study by the Working Group for Preparation of Wind Environment Evaluation Guideline based on CFD. In general, prediction accuracy for the weak wind regions behind buildings was not satisfactory, while prediction accuracy for the strong wind region was comparatively high. In single building models, which are considered to give the highest accuracy in the experiment, the CFD analysis results were consistent with experimental results within an accuracy about 10% in the strong wind region. For the urban block model, which is considered to give the next accurate results in the experiment, the CFD analysis results showed a prediction accuracy within ten or so % for the standard k- model and better accuracy for the modified k- models. In actual urban area models, the prepared CAD data for CFD simulation did not completely mach with experiment and field measurements, and it is difficult to quantitatively describe the prediction accuracy. However, relatively good matching was found in the strong wind region. The reason why the CFD analysis results underestimate the wind velocity behind the buildings may be because it is not possible to reproduce the vortex shedding in RANS type models such as the k- model. In LES, this can be improved, and the maximum instantaneous wind velocity can also be evaluated in LES. However, in order to use LES in general-purpose applications for predicting the wind environment around buildings, we need a dramatic increase in computer processing speed in the future. For the time being, we must be content with RANS type models currently in use. In RANS type models, it is only possible to evaluate average wind velocity. To evaluate pedestrian wind environment based on maximum gust wind speed we need to convert from average wind speed to maximum gust wind speed based on the assumption of gust factor. Although there are problems as described above in the CFD analysis using the RANS type turbulence models, it is advantageous that the detailed and overall spatial distribution of wind velocity can be identified in CFD analysis, while only limited information on wind velocity can be obtained from wind tunnel experiments. Strong wind points that may have been missed in wind tunnel experiments may be identified by the CFD simulation. Further, there are some uncertainties inherent in wind tunnel experiments (such as measuring instrument errors, incidental errors, errors in the position where the sensor is installed, etc.), but there are no such uncertainties in CFD. Furthermore, it is very difficult to have an arbitrary approach flow in the wind tunnel, while this can be freely done in CFD. It thus appears possible to reduce the differences in prediction accuracy between wind tunnel experiment and CFD on practical assessment. Finally, in the Working Group for Preparation of Wind Environment Evaluation Guideline based on CFD, we are comprehensively evaluating the results of benchmark tests and are preparing a final draft for the guideline. This will be completed and published within this year. We shall be very pleased if this guideline is helpful in achieving the best results within the current limitations of prediction by CFD as described above. NOMENCLATURE U :Average Wind velocity in stream-wise direction (x direction)[m/s] V : Average Wind velocity in transverse direction (y direction) [m/s] W : Average Wind velocity in vertical direction (z direction)[m/s] K : Turbulent kinetic energy [m 2 /s 2 ] : Dissipation rate of turbulent kinetic energy [m 2 /s 3 ] P k : Production of turbulent kinetic energy [m 2 /s 3 ] ACKNOWLEDGEMENT The authors would like to express their gratitude to the members of the Working Group for Preparation of Wind Environment Evaluation Guideline based on CFD [cf. Note] 13

The Fourth European & African Conference on Wind Engineering, Paper #292 NOTE The working group members are: A. Mochida (Chair, Tohoku Univ.), Y.Tominaga (Secretary, Niigata Inst. of Tech.), Y Ishida (Kajima Corp.), T.Ishihara (Univ. of Tokyo), K. Uehara (National Inst. of Environ. Studies), R. Ooka (I.I.S., Univ. of Tokyo), H. Kataoka (Obayashi Corp.), T. Kurabuchi (Tokyo Univ. of Sci.), N. Kobayashi (Tokyo polytechnic Univ.), N. Tuchiya (Takenaka Corp.), Y. Nonomura (Fujita Corp.), T. Nozu (Shimizu Corp.), K. Harimoto (Taisei Corp.), K. Hibi (Shimizu Corp.), S. Murakami (Keio Univ.), R. Yoshie (Tokyo Polytechnic Univ.) Criteria for assessing wind-induced discomfort, Journal of Architectural Institute of Japan, No. 325, pp.74-84.(written in Japanese) [10]Yoshida, M., Sanada, S., Fujii, K., Asami, Y., Iwasa, Y., Fukao, Y., Kawaguchi, A., and Members of AIJ (1978) Full-scale measurement of environmental wind on New- Shinjuku-Center -Characteristics of wind in built-up area (part1)-, Proceeding of fifth Symposium on wind effects on structures, pp.75-82.(written in Japanese) [11] Asami, Y., Iwasa, Y., Fukao, Y., Kawaguchi, A., Yoshida, M., Sanada, S., Fujii, K., and Members of AIJ (1978) Fullscale measurement of environmental wind on New- Shinjuku-Center -Characteristics of wind in built-up area (part2)-, Proceeding of fifth Symposium on wind effects on structures, pp.83-90.(written in Japanese) REFERENCES [1] Meng, Y. and Hibi, K. (1998) Turbulent measurements of the flow field around a high-rise building, Journal of Wind Engineering, No.76, pp55-64.(written in Japanese) [2] Kato, M. and Launder, B.E. (1993) The modelling of turbulent flow around stationary and vibrating square cylinders, 9th Symposium on Turbulent Shear Flows, pp.10-4. [3] Working Group for CFD Prediction of Wind Environment Around Building (2001) Development of CFD method for predicting wind environment around a high-rise building, Part1: The cross comparison of CFD results using various k- models, AIJ Journal of Technology and Design, No.12, 119-124, 2001.(written in Japanese) [4] Mochida, A., Tominaga, Y., Murakami, S., Yoshie, R., Ishihara, T., and Ooka, R. (2002) Comparison of various k- models and DSM applied to flow around a high-rise building -report on AIJ cooperative project for CFD prediction on wind environment, Wind&Structures, Vol.5, No.24, pp.227-244. [5] Tominaga, Y., Mochida, A., Murakami, S. (2003) Large Eddy Simulation of Flowfield around a High-rise Building, 11th International Conference on Wind engineering, B10-5. [6] Shirasawa, T., Mochida, A., Tominaga, Y., Yoshie, R., Kataoka, H., Nozu T. and Yoshino, H. (2003) Development of CFD method for predicting wind environment around a high-rise building, Part2: The cross comparison of CFD results on the flow field around a 4:4:1 prism, AIJ Journal of Technology and Design, No.18, 441-446.(written in Japanese) [7] Tominagada, Y., Mochida, A., Shirasawa, T., Yoshie, R., Kataoka, H., Harimoto, K. and Nozu, T. (2004) Cross Comparisons of CFD results of wind environment at pedistrian level around a high-rise building and within a building complex, Journal of Asian Architecture and Building Engineering, vol.3 no.1, pp.63-70. [8] Tominagada, Y., Mochida, A., Harimoto, K., Kataoka, H., Yoshie, R. (2004) Development of CFD method for predicting wind environment around a high-rise building, Part3: The cross comparison of results for wind environment around building complex in actual urban area using different CFD codes, AIJ Journal of Technology and Design, No.19, 181-184. (written in Japanese) [9] Murakami, S., Iwasa, Y., Morikawa Y. (1983) Investigation of statistical characteristics of wind at ground level and criteria for assessing wind-induced discomfort part 14