AIJ COOPERATIVE PROJECT FOR PRACTICAL APPLICATIONS OF CFD TO URBAN VENTILATION

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1 The Seventh Asia-Pacific Conference on Wind Engineering, November 8-2, 29, Taipei, Taiwan AIJ COOPERATIVE PROJECT FOR PRACTICAL APPLICATIONS OF CFD TO URBAN VENTILATION Ryuichiro Yoshie, Akashi Mochida 2, Yoshihide Tominaga 3, Taichi Shirasawa 4, Hideyuki Tanaka Professor, Department of Architecture, Tokyo Polytechnic University, 83, Iiyama Atsugi, Kanagawa, Japan, 2 Professor, Department of Architecture and Building Science, Tohoku University, Aoba-ku , Sendai, Japan, 3 Professor, Department of Architecture, Niigata Institute of Technology, Kashiwazaki 79, Japan, 4 Researcher, Graduate School of Eng., Tokyo Polytechnic University, Iiyama 83, Atsugi, Japan, Researcher, Takenaka Research and Development Institute, Otsuka --, Inzai, Japan, ABSTRACT AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings were recently published, which were mainly targeted for strong wind problems around high-rise buildings. However, urban heat island phenomenon and air pollution problem become serious in weak wind regions such as behind buildings and within the street canyons. Urban ventilation is now broadly recognized as one of the effective countermeasures to tackle these problems, thus it is becoming extremely important to ensure adequate air ventilation in weak wind regions. In order to apply CFD techniques to estimate the air ventilation, thermal and pollutant dispersion in urban areas, it is important to assess the performance of turbulence models that to be adopted for simulating these phenomena. Thus, a new working group was organized by the Architectural Institute of Japan (AIJ) to implement this validation. As the first step of the work, wind tunnel experiments and CFD simulations for gas and thermal dispersion behind a high-rise building in unstable non-isothermal turbulent flow were carried out. Standard k-ε model and two-equation model for heat transfer were used as the investigated turbulence model in this study. The calculated results of these two models showed that there was little difference between these models, and both models overestimated the size of the recirculation region behind the building and underestimated the lateral dispersion of the gas. KEYWORDS: URBAN VENTILATION, POLLUTANT DISPERSION, NON-ISOTHERMAL FLOW, CFD Introduction AIJ (Architectural Institute of Japan) guidelines for practical applications of CFD to pedestrian wind environment around buildings were published in 27 and 28 (AIJ, 27 (Japanese version(figure )), Tominaga et al. 28 (English version)). During the process of preparing the guidelines, many comparative and parametric studies on various building configurations were investigated by the CFD Working Group of AIJ. The purpose was aimed to elucidate the problems on setting or selecting calculation conditions and the choice of turbulence models for CFD simulation of the pedestrian wind environment. These investigations mainly targeted for strong wind problems around high-rise buildings. However, the importance of air ventilation in urban areas is now broadly recognized as a

2 The Seventh Asia-Pacific Conference on Wind Engineering, November 8-2, 29, Taipei, Taiwan countermeasure to urban heat island phenomenon and air pollution problem, so it is becoming extremely important to ensure adequate air ventilation in weak wind regions. In order to apply CFD techniques to estimate the air ventilation, thermal dispersion and pollutant dispersion in urban areas, it is essential to assess the performance of turbulence models for these phenomena which occur in non-isothermal flows. However, such validation of CFD for the non-isothermal flows has rarely been conducted thus far in the field of wind engineering. One of the reasons is that there are few reliable experimental data to validate the CFD results, because wind velocity measurement by hot wire anemometer is difficult in the non-isothermal flows and in the weak wind regions such as behind buildings or within the street canyons. In the non-isothermal flow fields, output voltage from the hot wire are affected by temperature fluctuation, and in the weak wind regions where both positive and negative (reverse) flows exist, the hot wire cannot distinguish them. Thus, a new working group was organized by the AIJ to provide the reliable experimental data and conduct the CFD validation for air ventilation, thermal dispersion and pollutant dispersion in urban areas. As the first step of the work, wind tunnel experiments and CFD simulations for gas dispersion behind a high-rise building in both isothermal and nonisothermal flows were carried out. The results of the isothermal flow were already reported by the present authors (Shirasawa et al. 27). In that study, various RANS models (Standard k-ε model, RNG k-ε model, realizable k-ε model, Reynolds stress model) and LES were examined. The results of the LES analysis gave a good agreement with the experimental data in terms of size of recirculation region behind the building and lateral dispersion of the gas, while every RANS model overestimated the size of the recirculation region and underestimated the lateral dispersion of the gas. This was mainly because the periodic motions caused by the vortex shedding were not reproduced by the RANS models, in spite of the unsteady calculation. The present article presents the results of the unstable non-isothermal turbulent flow. Calculation results obtained from standard k-ε model and two-equation model for heat transfer were compared with those of the wind tunnel experiment. The symbols used in this paper are defined on the last page. Figure : AIJ guide book for numerical simulation of wind environment in urban areas Wind Tunnel Experiment Figure 2 shows experimental setup. A building model (a square cylinder:.8.8.6m) was placed in an unstable turbulent boundary layer. The experiment was

3 The Seventh Asia-Pacific Conference on Wind Engineering, November 8-2, 29, Taipei, Taiwan conducted in a thermally stratified wind tunnel of Tokyo polytechnic university. The size of the cross section at measuring part was.2m (width).m (height). Surface temperature of the wind tunnel floor Θ f was uniformly controlled to be 4. Wind velocity and air temperature at the building height, U H, Θ H were.4m/s and respectively. The vertical profile of inflow mean wind velocity, mean temperature, and turbulent kinetic energy at =-2., = are shown in Figure 3. Tracer gas (%C 2 H 4, 3 ) was released from a hole with diameter φ=mm on the floor behind the building. The C 2 H 4 gas flow rate was m 3 /s (. means %). For the measurement of velocity, temperature, and concentration, measuring technique developed by the present authors (Yoshie et al. 27) was used. The measuring system was composed of a split film, a cold wire, and a high speed flame ionization detector, which enabled the following. ) Simultaneous measurement of instantaneous wind velocity, temperature, and concentration. Therefore turbulent heat flux and turbulent concentration flux can be measured. 2) Distinction between positive flow and negative (reverse) flow. 3) Appropriate temperature compensation to the output voltage of the split film in a flow with a large temperature fluctuation. The sampling frequency was Hz to obtain 9, data in 9sec for each measuring point. 建物高さ風速 Wind velocity :U at the H height of building, U H H=.6m ガス排出口 Gas discharge (φ=mm) hole X 3 X 2 (φ=mm) C 2 H 4 % X <u >/U H (<θ>-θ f )/ΔΘ k/u H 2 Figure 2: Experimental set up Figure 3: Vertical profiles of mean wind velocity, mean temperature, and turbulent kinetic energy (=-2., =) Outline of CFD Simulation For turbulence modeling, the standard k-ε model and the two-equation model for heat transfer proposed by Nagano and Kim (988) were examined. Both of the models evaluate the turbulent heat fluxes <u i θ > by eddy-diffusivity approach as follows. ' i u θ ' α θ t x i The standard k-ε model determines the eddy diffusivity for heat transfer α t by using kinematic eddy viscosity γ t and constant turbulent Prandtl number Pr t as α t = γ t /Pr t. In the present research Pr t was set to be.9. On the other hand, the two-equation model for heat transfer evaluates α t by the functions of temperature variance <θ' 2 > and dissipation rate of half the temperature variance ε θ, together with k and ε as follows. t λ 2 2 k ε / θ' ε / 2 α C k (2) θ The k/ε and the <θ' 2 > /ε θ are the time scale for velocity field and temperature field respectively, and the (k/ε) /2 (<θ' 2 > /ε θ ) /2 expresses the mixed time scale. C λ is the numerical constant of.. As shown in Eq. (2), this model does not require any assumptions for turbulent Prandtl number. This model was chosen for the present work because it was reported that a very good agreements with experimental results were achieved for wall heat transfer on heated horizontal plate and inner surface of heated pipe (Nagano and Kim 988). ()

4 The Seventh Asia-Pacific Conference on Wind Engineering, November 8-2, 29, Taipei, Taiwan For both models, constant turbulent Schmidt number of.9 was given in the transport equation of the gas concentration. Table summarizes the calculation conditions, and Figure 4 illustrates computational domain and grid arrangement. Unsteady calculations were performed for both of the two models, but periodic fluctuations due to the vortex shedding were not reproduced. Computational domain Table Calculation conditions The computational domain covers 2.H in the stream-wise (x ), 7.H in the lateral (x 2 ) directions and 6.2H in the vertical (x 3 ) direction. The computational domain has the same lateral width and height as those of the wind tunnel. Grid discretization 69(x ) 68(x 2 ) 44(x 3 ) Inflow boundary Downstream boundary Floor and Building surfaces Lateral and upper boundaries Scheme for Convection terms <u >, <θ>, and k from the experimental data were imposed. <u 2 >=, <u 3 >=. The inflow value of was obtained from the relation of ε=p k +G k. P k =<u u 3 >(d<u >/dx 3 ) and G k =-gβ<u 3 θ > were estimated from the experimental data. <θ' 2 > from the experimental data were imposed for the two-equation model for heat transfer. Zero gradient condition was used. The logarithmic law for a smooth wall was adopted for wall shear stress. Floor surface temperature and building surface temperature from the experimental data were prescribed, and the logarithmic low for a smooth wall was adopted for surface heat flux. Symmetry boundary conditions (slip walls). The QUICK scheme was applied to all convection terms. building 6.2H (height of wind tunnel) building 2H H H (a) Vertical section (b) Horizontal Plane Figure 4: Computational domain and grid arrangement. 7.H (width of wind tunnel) Results and Discussions Comparison of two turbulence models Fig. compares the vertical distribution of eddy diffusivity for heat transfer α t calculated by the standard k-ε model and the two-equation model for heat transfer. The α t by the two-equation model for heat transfer showed about 2% larger than that of the standard k-ε model in the region around =.7-. behind the building. However, mean temperature distribution of the two models revealed little difference, as shown in Fig. 6. It seemed that the heat transport by advection was much larger than that of turbulent diffusion in this region. The differences between the results of these two models in velocity and gas concentration were also not significant. Thus, the results of the two-equation model for heat transfer were only shown hereafter.

5 The Seventh Asia-Pacific Conference on Wind Engineering, November 8-2, 29, Taipei, Taiwan ガス排出孔 (a) Standard k-ε model Fig. Vertical distribution of eddy diffusivity for heat transfer α t (=) ガス排出孔 (a) Standard k-ε model Fig. 6 Vertical distribution of mean temperature (<θ>-θ f )/ΔΘ (=) Comparison of experiment and CFD Mean wind velocity Scalar wind velocity and velocity vector of the experiment and the calculation are shown in Fig. 7 (vertical distribution) and Fig.8 (horizontal distribution). The result of the CFD showed an overestimation of the recirculation size behind the building. The reattachment lengths on the ground behind the building were.3 and 2.38 for the experiment and the calculation respectively. The calculated downward flow in the region around =.7-. was weaker than the experimental one. On the other hand, calculated reverse flow near the ground and rising flow along the rear surface of the building are stronger than that of the experiment. These tendencies were quite similar to those of the isothermal case (Shirasawa et al. 27) Fig. 7 Vertical distribution of scalar wind velocity Us/U H & vector (=)

6 The Seventh Asia-Pacific Conference on Wind Engineering, November 8-2, 29, Taipei, Taiwan Fig. 8 Horizontal distribution of scalar wind velocity Us/U H & vector (=.2) Mean temperature Figs. 9 and illustrate vertical and horizontal distributions of mean temperatures respectively. Although the calculated vertical distribution of the mean temperature was almost similar to the experiment, the calculated temperature along the rear surface of the building was higher and contour lines show vertical shape. The conceivable reason was that the strong rising flow along the rear surface of the building transported the hot air near the ground upper along the rear surface. In the experiment and the calculation, the area of the highest temperature was located just behind the building (Fig. 9) Fig. 9 Vertical distribution of mean temperature (<θ>-θf )/ΔΘ (=) Fig. Horizontal distribution of mean temperature (<θ>-θf )/ΔΘ (=.2) Mean gas concentration Figs. and 2 show the distribution of mean gas concentration. In the calculation results, the high concentration area near the ground did not spread downwind of the gas emission point (marked as black triangle ). Similar to the temperature distributions, shown previously, calculated gas concentration along the rear surface of the building was higher due to the rising flow from the ground. The calculation did not reproduce the periodic fluctuations due to vortex shedding, and as a result the dispersion in the X 2 direction was inhibited, and the gas was transported toward the rear surface of the building near the ground with the recirculation flow. These tendencies were also quite similar to those of isothermal case (Shirasawa et al. 27)

7 The Seventh Asia-Pacific Conference on Wind Engineering, November 8-2, 29, Taipei, Taiwan Fig. Vertical distribution of s mean concentration (=) Fig. Horizontal distribution of mean concentration (=.2) Turbulent heat flux Fig. 3 illustrates the vertical distribution of turbulent heat flux <u 3 θ >. In the experimental result, the largest <u 3 θ > was located in the downward flow region around =.7-.. The distribution pattern of the calculation was rather different from the experiment, but the order of the value was similar Fig. 3 Vertical distribution of turbulent heat flux <u 3 θ >/(U H ΔΘ) (=) Turbulent concentration flux Fig. 4 shows the horizontal distribution of turbulent concentration flux <u 2 c > near the ground surface. The shape of the lateral turbulent concentration flux of the calculation was narrower than that of the experiment because of the lack of periodic fluctuations due to vortex shedding Fig. 4 Horizontal distribution of turbulent concentration flux <u 2 c >/(U H C ) (=.2). 2 2.

8 The Seventh Asia-Pacific Conference on Wind Engineering, November 8-2, 29, Taipei, Taiwan Conclusions In this study, wind tunnel experiments and CFD simulations for gas and thermal dispersion behind a building in unstable non-isothermal turbulent flow were carried out. The standard k-ε model and the two-equation model for heat transfer were adopted in the CFD calculation. The both models did not reproduce the vortex shedding, in spite of the unsteady calculation. The calculated results of these two models showed little difference from each other, and both models overestimated the size of the recirculation region. The calculated reverse flow near the ground and rising flow along the rear surface of the building were stronger compared with the experimental result. These flows affected the distributions of temperature and gas concentration. Symbols f : instantaneous value of a quantity <f> : time-averaged value of f f : fluctuation from time-averaged value f =f-<f> x i : three components of space coordinates (i =,2,3: stream-wise, lateral, vertical) [m] u i : three components of velocity vector [m/s] c : gas concentration [m 3 /m 3 ] θ: temperature [ ] H : building height (.6 [m]) <U H >: inflow stream-wise velocity at height H (.4[m/s]) Θ H : inflow temperature at height H ( [ ]) Θ f : floor temperature (4 [ ]) ΔΘ: Θ f -Θ H (34 [ ]) q : gas emission rate ( [m 3 /s] ) C : reference gas concentration (q/<u H >H 2 ) k : turbulent kinetic energy [m 2 /s 2 ] ε:dissipation rate of turbulent kinetic energy [m 2 /s 3 ] ε θ : dissipation rate of half the temperature variance [ 2 /s] References Architectural Institute of Japan (27), Guide book for numerical simulation of wind environment in urban areas Tominaga, Y., Mochida, A., Yoshie, R., Kataoka, H., Nozu, T., Yoshikawa, M., and Shirasawa, T.(28), AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings, Journal of Wind Engineering and Industrial Aerodynamics, 96, Shirasawa, T., Yoshie, R., Tanaka, H., Kobayashi, T., Mochida, A., Endo, y., (28), Cross comparison of CFD results of gas diffusion in weak wind region behind a high-rise building, Proceedings of The 4th International Conference on Advances in Wind and Structures (AWAS 8), Jeju, Korea, May, 38-. Yoshie, Y., Tanaka, H., and Shirasawa, T. (27), Technique for Simultaneously Measuring Fluctuating Velocity, Temperature and Concentration in Non-isothermal Flow, Proceedings of the 2th International Conference on Wind Engineering, Cairns, Australia, July, Nagano, Y. and Kim, C. (988), A two-equation model for heat transport in wall turbulent shear flows, Trans. ASME, J. Heat Transfer,,