Evaluation of a micro-scale wind model's performance over realistic building clusters using wind tunnel experiments
Evaluation of a micro-scale wind model's performance over realistic building clusters using wind tunnel experiments
复制标题
使用风洞实验评估微尺度风模型在真实建筑群中的性能
DOI：
10.1007/s00376-016-5273-1
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发表时间：
2016
影响因子：
5.8
通讯作者：
Fang Xiaoyi
中科院分区：
文献类型：
--
作者：
Zhang Ning;Du Yunsong;Miao Shiguang;Fang Xiaoyi
风模拟模型对复杂建筑群的模拟性能（风信息场快速分析模式WIFFA）在微尺度大气污染物扩散模式系统中的应用城市微尺度空气污染扩散模拟模型，UMAPS）进行了评估，使用各种风洞实验数据，包括CEDVAL（验证微尺度扩散模型的实验数据汇编）风洞实验数据和NJU-FZ实验数据（南京大学-方庄小区风洞实验数据）。结果表明，该风场模型能较好地再现城市建筑物引发的涡旋，也能较好地代表城市街道峡谷和建筑群内的流态。由于建筑物的形状及其分布的复杂性，通常由建筑物形状的简化和关键区域尺寸的确定引起的模拟偏差/测量差异。本文还讨论了不同情况下的计算效率。与传统的求解Navier-Stokes方程的数值模式相比，该模式具有很高的计算效率，在个人计算机上运行不到3 min就可以生成复杂街区尺度（~ 1 km ×1 km）的城市建筑物冠层的高分辨率（1-5 m）风场。
The simulation performance over complex building clusters of a wind simulation model (Wind Information Field Fast Analysis model, WIFFA) in a micro-scale air pollutant dispersion model system (Urban Microscale Air Pollution dispersion Simulation model, UMAPS) is evaluated using various wind tunnel experimental data including the CEDVAL (Compilation of Experimental Data for Validation of Micro-Scale Dispersion Models) wind tunnel experiment data and the NJU-FZ experiment data (Nanjing University-Fang Zhuang neighborhood wind tunnel experiment data). The results show that the wind model can reproduce the vortexes triggered by urban buildings well, and the flow patterns in urban street canyons and building clusters can also be represented. Due to the complex shapes of buildings and their distributions, the simulation deviations/discrepancies from the measurements are usually caused by the simplification of the building shapes and the determination of the key zone sizes. The computational efficiencies of different cases are also discussed in this paper. The model has a high computational efficiency compared to traditional numerical models that solve the Navier–Stokes equations, and can produce very high-resolution (1–5 m) wind fields of a complex neighborhood scale urban building canopy (~ 1 km ×1 km) in less than 3 min when run on a personal computer.