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RISS 인기검색어
- 검색키워드
- 저자 : Weimei Jiang (검색결과 8 건)
- 무료
- 기관 내 무료
- 유료
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Jiang, Dehai,Jiang, Weimei,Liu, Hongnian,Sun, Jianning Techno-Press 2008 Wind and Structures, An International Journal (WAS Vol.11 No.4
Large eddy simulations have been performed within and over different types of urban building arrays. This paper adopted three dimensionless parameters, building frontal area density (${\lambda}_f$) the variation degree of building height (${\sigma}_h$), and the staggered degree of building range ($r_s$), to study the systematic influence of building spacing, height and layout on wind and turbulent characteristics. The following results have been achieved: (1) As ${\lambda}_f$ decrease from 0.25 to 0.18, the mean flow patterns transfer from "skimming" flow to "wake interference" flow, and as ${\lambda}_f$ decrease from 0.06 to 0.04, the mean flow patterns transfer from "wake interference" flow to "isolated roughness" flow. With increasing ${\lambda}_f$, wind velocity within arrays increases, and the vortexes in front of low buildings would break, even disappear, whereas the vortexes in front of tall buildings would strengthen and expand. Tall buildings have greater disturbance on wind than low buildings do. (2) All the wind velocity profiles and the upstream profile converge at the height of 2.5H approximately. The decay of wind velocity within the building canopy was in positive correlation with ${\lambda}_f$ and $r_s$. If the height of building arrays is variable, Macdonald's wind velocity model should be modified through introducing ${\sigma}_h$, because wind velocity decreases at the upper layers of the canopy and increases at the lower layers of the canopy. (3) The maximum of turbulence kinetic energy (TKE) always locates at 1.2 times as high as the buildings. TKE within the canopy decreases with increasing ${\lambda}_f$ and $r_s$ but the maximum of TKE are very close though ${\sigma}_h$ varies. (4) Wind velocity profile follows the logarithmic law approximately above the building canopy. The Zero-plane displacement $z_d$ heighten with increasing ${\lambda}_f$, whereas the maximum of and Roughness length $z_0$ occurs when ${\lambda}_f$ is about 0.14. $z_d$ and $z_0$ heighten linearly with ${\sigma}_h$ and $r_s$, If ${\sigma}_h$ is large enough, $z_d$ may become higher than the average height of buildings.
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Dehai Jiang,Weimei Jiang,Hongnian Liu,Jianning Sun 한국풍공학회 2008 Wind and Structures, An International Journal (WAS Vol.11 No.4
Large eddy simulations have been performed within and over different types of urban building arrays. This paper adopted three dimensionless parameters, building frontal area density (λf), the variation degree of building height (σh), and the staggered degree of building range (rs), to study the systematic influence of building spacing, height and layout on wind and turbulent characteristics. The following results have been achieved: (1) As λf decrease from 0.25 to 0.18, the mean flow patterns transfer from “skimming” flow to “wake interference” flow, and as λf decrease from 0.06 to 0.04, the mean flow patterns transfer from “wake interference” flow to “isolated roughness” flow. With increasing σh, wind velocity within arrays increases, and the vortexes in front of low buildings would break, even disappear, whereas the vortexes in front of tall buildings would strengthen and expand. Tall buildings have greater disturbance on wind than low buildings do. (2) All the wind velocity profiles and the upstream profile converge at the height of 2.5H approximately. The decay of wind velocity within the building canopy was in positive correlation with λf and rs. If the height of building arrays is variable, Macdonald’s wind velocity model should be modified through introducing σh, because wind velocity decreases at the upper layers of the canopy and increases at the lower layers of the canopy. (3) The maximum of turbulence kinetic energy (TKE) always locates at 1.2 times as high as the buildings. TKE within the canopy decreases with increasing λf and rs but the maximum of TKE are very close though σh varies. (4) Wind velocity profile follows the logarithmic law approximately above the building canopy. The Zero-plane displacement zd heighten with increasing λf, whereas the maximum of and Roughness length z0 occurs when λf is about 0.14. zd and z0 heighten linearly with σh and rs, If σh is large enough, zd may become higher than the average height of buildings.
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A large eddy simulation on the effect of buildings on urban flows
Zhang, Ning,Jiang, Weimei,Miao, Shiguang Techno-Press 2006 Wind and Structures, An International Journal (WAS Vol.9 No.1
The effect of buildings on flow in urban canopy is one of the most important problems in local/micro-scale meteorology. A large eddy simulation model is used to simulate the flow structure in an urban neighborhood and the bulk effect of the buildings on surrounding flows is analyzed. The results demonstrate that: (a) The inflow conditions affect the detailed flow characteristics much in the building group, including: the distortion or disappearance of the wake vortexes, the change of funneling effect area and the change of location, size of the static-wind area. (b) The bulk effect of the buildings leads to a loss of wind speed in the low layer where height is less than four times of the average building height, and this loss effect changes little when the inflow direction changes. (c) In the bulk effect to environmental fields, the change of inflow direction affects the vertical distribution of turbulence greatly. The peak value of the turbulence energy appears at the height of the average building height. The attribution of fluctuations of different components to turbulence changes greatly at different height levels, in the low levels the horizontal speed fluctuation attribute mostly, while the vertical speed fluctuation does in high levels.
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Numerical method study of how buildings affect the flow characteristics of an urban canopy
Zhang, Ning,Jiang, Weimei,Hu, Fei Techno-Press 2004 Wind and Structures, An International Journal (WAS Vol.7 No.3
The study of how buildings affect wind flow is an important part of the research being conducted on urban climate and urban air quality. NJU-UCFM, a standard $k-{\varepsilon}$ turbulence closure model, is presented and is used to simulate how the following affect wind flow characteristics: (1) an isolated building, (2) urban canyons, (3) an irregular shaped building cluster, and (4) a real urban neighborhood. The numerical results are compared with previous researchers' results and with wind tunnel experiment results. It is demonstrated that the geometries and the distribution of urban buildings affect airflow greatly, and some examples of this include a changing of the vortices behind buildings and a "channeling effect". Although the mean air flows are well simulated by the standard $k-{\varepsilon}$ models, it is important to pay attention to certain discrepancies when results from the standard $k-{\varepsilon}$ models are used in design or policy decisions: The standard $k-{\varepsilon}$ model may overestimate the turbulence energy near the frontal side of buildings, may underestimate the range of high turbulence energy in urban areas, and may omit some important information (such as the reverse air flows above the building roofs). In ideal inflow conditions, the effects of the heights of buildings may be underestimated, when compared with field observations.
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Determination of Urban Surface Aerodynamic Characteristics Using Marquardt Method
Zhang, Ning,Jiang, Weimei,Gao, Zhiqiu,Hu, Fei,Peng, Zhen Techno-Press 2009 Wind and Structures, An International Journal (WAS Vol.12 No.3
Marquardt method is used to estimate the aerodynamic parameters in urban area of Beijing City, China, including displacement length (d), roughness length ($z_0$) and friction velocity (u*) and drag coefficient. The surface drag coefficient defined as the ratio between friction velocity and mean wind speed is 0.125 in our research, which is close to typical urban area value. The averaged d and $z_0$ are 1.2 m and 7.6 m. d and $z_0$ change with direction because of the surface heterogeneity over urban surface and reach their maximum values at S-SW sector, this tendency agrees with the surface rough element distribution around the observation tower.
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