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Evaluation of the QUIC-URB fast response urban wind model for a cubical building array and wide building street canyon

机译:三次建筑物阵列和宽阔建筑物街道峡谷的QUIC-URB快速响应城市风模型评估

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This paper describes the QUIC-URB fast response urban wind modeling tool and evaluates it against wind tunnel data for a 7 × 11 cubical building array and wide building street canyon. QUIC-URB is based on the R?ckle diagnostic wind modeling strategy that rapidly produces spatially resolved wind fields in urban areas and can be used to drive urban dispersion models. R?ckle-type models do not solve transport equations for momentum or energy; rather, they rely heavily on empirical parameterizations and mass conservation. In the model-experiment comparisons, we test two empirical building flow parameterizations within the QUIC-URB model: our implementation of the standard R?ckle (SR) algorithms and a set of modified R?ckle (MR) algorithms. The MR model attempts to build on the strengths of the SR model and introduces additional physically based, but simple parameterizations that significantly improve the results in most regions of the flow for both test cases. The MR model produces vortices in front of buildings, on rooftops and within street canyons that have velocities that compare much more favorably to the experimental results. We expect that these improvements in the wind field will result in improved dispersion calculations in built environments.
机译:本文介绍了QUIC-URB快速响应城市风建模工具,并针对7×11立方建筑阵列和宽阔的建筑街道峡谷,根据风洞数据对其进行了评估。 QUIC-URB基于R?ckle诊断风建模策略,可快速在城市区域产生空间分辨的风场,并可用于驱动城市离散模型。 R?ckle型模型不能求解动量或能量的输运方程。相反,它们严重依赖于经验参数化和质量守恒。在模型与实验的比较中,我们在QUIC-URB模型中测试了两个经验性建筑流动参数化:我们对标准Rckle(SR)算法的实现和一组改进的Rckle(MR)算法的实现。 MR模型试图以SR模型的优势为基础,并引入其他基于物理的,但是简单的参数设置,可以显着改善两个测试用例在大多数流程区域中的结果。 MR模型会在建筑物前面,屋顶上和街道峡谷内产生涡流,涡流的速度与实验结果相比更为有利。我们期望在风场中的这些改进将导致在构建环境中改进的色散计算。

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