WIND TUNNEL MEASUREMENT AND ASSESSMENT ON THE PEDESTRIAN WIND ENVIRONMENT A CASE STUDY OF JINYING HIGH RISE BUILDING IN TAIPEI, TAIWAN

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1 WIND TNNEL MEASREMENT AND ASSESSMENT ON THE PEDESTRIAN WIND ENVIRONMENT A CASE STDY OF JINYING HIGH RISE BILDING IN TAIPEI, TAIWAN Bao-Shi Shiau 1 and Ben-Jue Tsai 2 ABSTRACT In this paper, wind tunnel measurement study on the pedestrian level (1.5 m to 2 m height from the ground) wind environment was arried out and applied to a ase measurement of JinYing high-rise building of a height of 86.8 m in Taipei, Taiwan. Wind tunnel measurements inorporating with statistial analysis of in-situ reorded wind data were applied to asses the wind environment of pedestrian level wind omfort and safety due to the JinYing building projet. Long term in-situ reorded wind data in the nearby of the high-rise building site was olleted and analyzed. The Weibull probability distribution was found to fit better for the wind speed data. For eah loation around the JinYin building, we integrated the measured wind tunnel pedestrian level peak wind speed and Weibull probability distribution of the wind speed to yield the results for assessing the pedestrian level wind omfort and safety around the building. Based on the pedestrian level wind aeptability riteria proposed by the RWDI ompany in Canada, it is onluded the omfort and safety of pedestrian level ativities are aeptable of the JinYing high rise building projet. Also the present study offered an example for assessing how the high-rise building projet affets the loal wind environment experiened by pedestrian ativities both to ensure omfort or safety and to failitate the attrativeness of the building projet. Keywords: wind tunnel, pedestrian wind, wind rose diagram, Weibull probability distribution INTRODCTION Due to the vast inrease of ommerial and living ativities in heavy ity, large and high-rise buildings are built intensively. The wind environment around the large or high-rise buildings has beome an important issue of engineering and environment. The pedestrian level wind is one of most onerned wind environment problems. The hange in pedestrian wind due to the newly built building may ause unomfortable and dangerous impats on the people ativities (suh as walk, sit, stroll, or stay) around the building. Therefore, it is neessary to evaluate the situation of pedestrian wind environment for the building projet. Reently, there have been progressive studies on the pedestrian level winds. Stathopoulos (2006) established an approah for an overall omfort index of pedestrian winds. Bu et al. (2009) made new 1 Corresponding author: Institute of Physis, Aademia Sinia, Taipei 115, Taiwan, and Department of Harbor and River Engineering, National Taiwan Oean niversity, Keelung 202, Taiwan. bsshiau@gate.sinia.edu.tw 2 Department of Harbor and River Engineering, National Taiwan Oean niversity, Keelung 202, Taiwan.

2 riteria for assessing loal wind environment at pedestrian level whih was based on exeedane probability analysis. Sanz-Andres and Cuerva (2006) investigated the feasibility study of riteria homogenization for pedestrian wind omfort. Visser et al. (2000) developed a KnoWind model whih is a database-oriented approah and an determine the pedestrian level wind environment around buildings. In this study we arried out the wind tunnel measurement on the pedestrian level wind around the JinYing high-rise building with height of 86.8 m in Taipei, Taiwan. The measurements inorporating with statistial analysis of in-situ mirometeorologial data (wind speed and diretion data) offer the wind environment assessment of pedestrian level wind omfort and safety due to the building projet. Long term of in-situ hourly reorded wind data in the nearby of the high-rise building site was olleted and analyzed. The Weibull probability distribution was applied to fit of the wind data. For eah loation around the building, we integrate measured wind tunnel pedestrian level wind speed and the statistial analysis of the wind limate data to yield the indiators for assessment of the wind omfort and safety around the building. Results will help to know and assess how the high-rise building projet affets the loal wind environment experiened by pedestrians both to ensure omfort or safety and to failitate the attrativeness of the building projet. EXPERIMENTAL SETP OF WIND TNNEL The measurements were onduted in the National Taiwan Oean niversity s Environmental Wind Tunnel. The wind tunnel test setion has a ross setion of 2 m wide by 1.4 m high, and 12.5 m long. The tunnel is an open sution type and it ontrats to the test setion with an area ratio of 4:1. The turbulene intensity of empty tunnel in test setion is less than 0.5 % at the mean veloity of 5 m/s. Four spires of 100 m height and ubi elements (5 m x 5 m x 5m) are properly arranged as the roughness at the entrane of test setion to generate a thik turbulent boundary layer whih is used as the approahing flow. An X-type hot-wire inorporating with the TSI IFA-300 onstant temperature anemometer was employed to measure the turbulent flow signals. Output of the analog signals for turbulent flow was digitized at a rate of 4k Hz eah hannel through the 12 bit Analog-to Digital onverter. Sine none of the analog signals ontaining signifiant energy or noise above 1k Hz, with the Nyquist riteria, a digitizing rate of 2k Hz was suffiient. The low pass frequeny for the analog signals is set as 1k Hz in the experiments. The pedestrian level wind speed was measured by using Irwin probe (Irwin(1981)). As indiated by Durgin (1992), Irwin probe is adequate for appliation in measuring pedestrian level wind speed. It is provided that an adequate and not too great frequeny response for the pressure sensing system is employed with the Irwin probe. The model sale used in the wind tunnel test is 1/400. Geometri and dynami similarity requirements were employed to simulate the neutral turbulent boundary layer flow in urban area whih is used as the approahing flow. The free stream veloity is 9 m/s, and boundary layer thikness 100 m. The Reynolds number in the experiments was about 8.4 x This ensures the Reynolds number similarity of flow between the model and prototype. The full sale of the building height is 86.8 m. And the building site area is 5276 m 2. Fig.1 shows the JinYing building model arrangement in the wind tunnel. And Fig.2 is the measurement loation label of pedestrian level wind around the building. PROBABILITY ANALYSIS OF IN-SIT MEASRED WIND DATA The in-situ measured wind data were olleted for eleven years from Taipei meteorologial station (No.46692), Central Weather Bureau, Taiwan. The wind data was reorded hourly. To analyze the wind data, the Weibull probability density funtion is adopted. The probability distribution for in-situ measured wind data is fit as, 2

3 3 ] ) ( exp[ ) ( ), ; ( 1 k k k k P = (1) where the is the saling fator, and k is the shape fator. And is the mean wind speed. Fig. 1. Main building model arrangement in wind tunnel Fig. 2. Label of measurement loation for pedestrian level wind

4 The umulative probability distribution of wind ourrene probability in i-th wind diretion for wind speed less and equal is expressed as: ki Pi ( speed ) = 1 exp[ ( ) i ] The total wind ourrene probability for wind speed less and equal is the summation of all sixteen wind diretions, and an be expressed as: P( speed ) = 16 i= 1 wi{1 exp[ ( ) where the w i represents wind ourrene perentage for wind diretion i. i k i ]} RESLTS Approahing Flow The turbulent boundary layer flow was generated as the approahing flow. Mean veloity profile of the simulated turbulent boundary layer flow is approximated by the power law shown as equation (4). ( Z ) Z n = ( ) (4) ref Z ref where (Z) is the mean veloity at height of Z, ref is the free stream veloity, and Z ref is the boundary layer thikness. The free stream veloity is ref =9 m/s; and the boundary layer thikness, Z ref is about 100 m. The measured mean veloity profile is shown in Fig. 3. Results indiate that the mean veloity profile expressed in power law is with a power exponent, n=0.24. Counihan (1975) indiated the power index range 0.23~0.40 for urban area. The present simulation of approahing flow fit to the power index range for terrain type of urban area as indiation of Counihan (1975). 1.2 =9.0m/s experimental data(x=9.5m,y=1m) =( Z ) n,n=0.24 ref Zref 0.8 Z/Zref (Z)/ref Fig. 3. The mean veloity profile of approahing flow 4

5 The simulated longitudinal turbulene intensity profile of approahing flow is shown in Fig. 4. Fig. 4 shows the simulated longitudinal turbulene intensity of approahing flow inreases with dereasing the height. As the height lose to the ground, the longitudinal turbulene intensity exeeds 20 % and approahes to about 25%. Counihan (1975) summarized that the longitudinal turbulene intensity for heights 2~30 m above ground level for rural area fell in the range of 0.2 to Fig. 4. The longitudinal turbulene intensity of approahing flow 10 1 Su(n)/u' 2 L x u Present Study von Karman nl xu / Fig. 5. The turbulene power spetrum of approahing flow at Z/Z ref =0.2 Fig. 5 shows the turbulene power spetrum of approahing flow measured at Z/Z ref =0.2. Maeda and Makino (1988) rewrote the Von-Karman type power spetrum equation as follows: ' u x 2u L Su ( n) = (5) u 5 x 2nL 2 [1 + ( ) ] 6 In Fig. 5, the spetrum density, S u (n) and frequeny, n are normalized, and they are denoted by 5

6 u S x u ( n) / u' L and nl u x /, respetively. Here u ' denotes the mean square of longitudinal veloity 2 ux flutuation, u ; is oeffiient of ; L is the integral length sale of longitudinal veloity in x diretion; is the longitudinal mean veloity at the height of z. The integral length sale is obtained by multiplying the integral time sale, T E with the longitudinal mean veloity,. The integral time sale, T E is omputed by integrating the longitudinal veloity autoorrelation oeffiient funtion, R u (τ ). The Von-Karman type power spetrum equation is also plotted and shown in the Fig. 5 for omparison. It is found that a satisfatory agreement is ahieved for the inertia-subrange of turbulent approahing flow struture simulation. Pedestrian Level Wind In the model study, pedestrian level winds of 20 loations around the building for sixteen wind diretion ases were measured inluding the mean wind speed, and peak wind speed, G. Results of the mean wind speed are listed in Table 1. The mean wind speed shown in the table is saled with the free stream veloity, i.e. / ref (%). The free stream veloity ref is 9 m/s. In the front fae region of building, there is a plaza. In the building front fae area, we measured loations labeled suh as: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and 11. Results listed in Table 1 show that the mean speed of pedestrian wind at these loations are all smaller than free stream veloity (i.e. < 100 %). The mean speeds of pedestrian wind at the plaza enter (loation 7) are greater than that of at other loations (like loations 3, 4, 5, 8, 9, 10) for all wind diretions. On the leeside area of building, the mean speed of pedestrian wind at loations 15, 16, 17, 18, 19, 20 are all smaller than free stream veloity (i.e. < 100 %) for all wind diretions. The mean speed of pedestrian wind at left hand side area of building (loation 12) is higher than that of at the right hand side area of building (loation 13, 14). The pedestrian level winds around the building under wind ation with different diretions are shown here by the wind rose diagram for onveniene. As an example, the wind rose diagram of mean wind speed of pedestrian level wind as examples at loations 7 and 15 are shown in Fig.6. In the figure, the mean wind speed is saled with the free stream veloity, i.e. / ref (%). As omparing pedestrian level wind for these two loations, we find that the mean wind speeds of pedestrian level at loation 7 are greater than that of loation 15 in all wind diretions. The peak wind speed is also an important index of assessment on omfort and safety for the pedestrian wind environment. The peak wind speed, G employed here is defined as: = + k (6) G u rms where gust fator k = 3.0 (Hunt et al, (1976)); is the mean wind speed; u rms is the root mean square of wind speed flutuation. The peak wind speed is saled with the free stream veloity, i.e. / ref (%). The free stream veloity ref is 9 m/s. Results of the saled peak wind speed at loations around building under ation of different wind diretions are shown in Table 2. Results of measured loations in the front fae region of building (labeled suh as: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and 11) show that the peak wind speed of pedestrian wind at these loations are all smaller than free stream veloity (i.e. < 100 %). The peak wind speed at loation 7 in the enter of plaza are greater than that of at the other measured loations in these area, suh as 3, 4, 5, 8, 9, 10. The measured peak wind speeds at loation 12 on left hand side of building are higher than that of loations 13, and 14 on the right hand side of building under the ation of wind diretions of N, NNE, NE, ENE, E, ESE, SE, SW, WNW, and NW. On the leeside region of the building, the peak wind speed at loation 20 exhibits higher value under the ation of southern wind. This is due to the orner wind effet when southern wind flows over the building. 6

7 Table 1. Mean speed of pedestrian level winds around the building for different wind diretions N NNE NE ENE E ESE SE SSE S SSW SW WW W WW NW NNW Fig. 6. The wind rose diagram for mean wind speed of pedestrian level wind at loation 7 and 15 7

8 Table 2. Peak speed of pedestrian level winds around the building for different wind diretions N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NNW Assessment and Evaluation on the Comfort and Safety of Pedestrian Level Ativities There had been several pedestrian wind omfort riteria whih were suggested to evaluate or assess the omfort and safety of loations around planned building. Ratliff and Peterka (1990) had made omparison of five pedestrian wind aeptability riteria. The riteria are generally based on the perent time ertain wind speeds are exeed annually but differ in implementation. They onluded differenes among the riteria are evident. In the present study, we ombined the loal long term mirometeorologial ondition with the wind tunnel measurements to analyze the pedestrian level wind environment. The in-situ reorded wind data were analyzed to yield the sale and shape fators of Weibull probability density funtion for eah wind diretion. The wind tunnel measured results of pedestrian level wind as shown in Table 2and 3 are inorporated with the umulative Weibulll probability density funtion to alulate the probability of pedestrian level wind speed. Aording to equation (3), the total wind ourrene probability for wind speed less and equal is the summation of all sixteen wind diretions. Calulated results for various pedestrian level peak wind speeds at different loations around the building are shown in Table 3. Results indiate that ourrene probability of peak wind speed less than or equal to 4.7 m/s for most of loations exept for loations 6,7,16, and 17, are smaller than 80 %. The ourrene probability of peak wind speed less than or equal to 6.9 m/s exeeds 80 % for all measured loations. At present, there is no general rule available for the assessment and evaluation of the pedestrian level wind omfort. For the purpose of feasibility and simpliity, the pedestrian level wind aeptability riteria 8

9 proposed by RWDI onsulting ompany, Canada, were employed in the present study to assess the pedestrian wind omfort and safety. It ategorized the wind omfort riteria for different pedestrian ativities as: (1) sitting (long time stay): The ourrene probability of peak wind speed less than or equal 4.7 m/s is at least 80%. (2) standing or strolling: The ourrene probability of peak wind speed less than or equal 6.9 m/s is at least 80%.. (3) walking: The ourrene probability of peak wind speed less than or equal 8.9 m/s is at least 80%. (4) nomfortable: The ourrene probability of peak wind speed greater than 6.9 m/s exeeds at least 20%. The riteria of safety or dangerous for pedestrian ativities is the ourrene frequeny of peak wind speed greater than 24.4 m/s exeeds at least 3 times per year. Results shown in Table 3 indiate that pedestrian winds for the loations 6, 7, 16, 17 are aeptable for long time stay or sitting ativities. And pedestrian ativities of standing or strolling are aeptable for all loations around the building. nomfortable or dangerous ourrene possibilities for pedestrian ativities seem to be lesser than 20 %. Based on the pedestrian level wind aeptability riteria of RWDI, it is onluded the omfort and safety of pedestrian level ativities are aeptable of the JinYing high rise building in Taipei ity, Taiwan. Table 3. Probability of pedestrian level peak wind speed for different loations around the building Probability (%) Loation Wind speed 4.7 m/s Wind speed 6.9 m/s Wind speed 8.9 m/s Wind speed 8.9 m/s CONCLSION Wind tunnel measurements inorporating with statistial analysis of in-situ reorded wind data were applied to asses the wind environment of pedestrian level wind omfort and safety due to the JinYing building projet in Taipei ity, Taiwan. Long term in-situ reorded wind data in the nearby of the high-rise 9

10 building site was olleted and analyzed. The Weibull probability distribution was found to fit better for the wind speed data. For eah loation around the JinYin building, we integrated the measured wind tunnel pedestrian level peak wind speed and Weibull probability distribution of the wind speed to yield the indiators for assessing the pedestrian level wind omfort and safety around the building. Based on the pedestrian level wind aeptability riteria proposed by the RWDI ompany in Canada, it is onluded the omfort and safety of pedestrian level ativities are aeptable of the JinYing high rise building projet. Also the present study offered an example for assessing how the high-rise building projet affets the loal wind environment experiened by pedestrian ativities both to ensure omfort or safety and to failitate the attrativeness of the building projet. ACKNOWLEDGMENTS The authors would like to aknowledge the Leaderman & Assoiates for partial finanial support in the present wind tunnel study. REFERENCES Bu, Z., S. Kato, Y. Ishida, and H. Huang, (2009), New Criteria for Assessing Loal Wind Environment at Pedestrian Level based on Exeedane Probability Analysis, Building and Environment, Vol.44, pp Counihan, J., (1975), Adiabati Atmospheri Boundary Layers: A Review and Analysis of the Data from the Period , Atmospheri Environment, Vol.9, pp Durgin, F.H., (1992), Pedestrian Level Wind Studies at the Wright Brothers Faility, Journal of Wind Engineering and Industrial Aerodynamis, Vol.41-44, pp Hunt, J.C.R., E.C. Poulton, and J.C. Mumford, (1976), The Effets of Wind on People: New Criteria Based on Wind Tunnel Experiments, Building and Environment, Vol.11, pp Irwin, H.P.A.H., (1981), A Simple Omnidiretional Sensor for Wind Tunnel Studies of Pedestrian-Level Wind, Journal of Wind Engineering and Industrial Aerodynamis, Vol.7, pp Maeda, J., and M. Makino, (1988), Power Spetra of Longitudinal and Lateral Wind Speed Near the Ground in Strong Winds, Journal of Wind Engineering and Industrial Aerodynamis, Vol.28, pp Ratliff, M., and J.A. Peterka, (1990), Comparison of Pedestrian Wind Aeptability Criteria, Journal of Wind Engineering and Industrial Aerodynamis, Vol.36, pp Sanz-Andres, A., and A. Cuerva, (2006), Pedestrian wind Comfort: Feasibility Study of Criteria Homogenization, Journal of Wind Engineering and Industrial Aerodynamis, Vol.94, pp Stathopoulos, A., (2006), Pedestrian Level Winds and Outdoor Human Comfort, Journal of Wind Engineering and Industrial Aerodynamis, Vol.94, pp Visser, G.Th., C.J. Folkers, and A. Weenk, (2000), KnoWind: a Database-Oriented Approah to Determine the pedestrian Level Wind Environment Around Buildings, Journal of Wind Engineering and Industrial Aerodynamis, Vol.87, pp