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Enhancements to AERMOD’s Building Downwash Algorithms based on Wind-Tunnel and Embedded-LES Modeling

机译:基于风洞和嵌入式LES建模的AERMOD建筑物冲洗算法的增强

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摘要

Knowing the fate of effluent from an industrial stack is important for assessing its impact on human health. AERMOD is one of several Gaussian plume models containing algorithms to evaluate the effect of buildings on the movement of the effluent from a stack. The goal of this study is to improve AERMOD’s ability to accurately model important and complex building downwash scenarios by incorporating knowledge gained from a recently completed series of wind tunnel studies and complementary large eddy simulations of flow and dispersion around simple structures for a variety of building dimensions, stack locations, stack heights, and wind angles. This study presents three modifications to the building downwash algorithm in AERMOD that improve the physical basis and internal consistency of the model, and one modification to AERMOD’s building pre-processor to better represent elongated buildings in oblique winds. These modifications are demonstrated to improve the ability of AERMOD to model observed ground-level concentrations in the vicinity of a building for the variety of conditions examined in the wind tunnel and numerical studies.
机译:了解工业堆中废水的命运对于评估其对人类健康的影响非常重要。 AERMOD是几种高斯羽流模型之一,其中包含用于评估建筑物对烟囱中出水运动的影响的算法。这项研究的目的是,通过结合从最近完成的一系列风洞研究中获得的知识以及针对各种建筑物尺寸的简单结构周围流动和分散的互补大涡流模拟中获得的知识,来提高AERMOD对重要而复杂的建筑物下水道情况进行准确建模的能力。 ,堆栈位置,堆栈高度和风向角。这项研究对AERMOD中的建筑物向下冲洗算法进行了三处修改,以改进模型的物理基础和内部一致性,并对AERMOD的建筑物预处理器进行了一项更改,以更好地表示斜风中的细长建筑物。这些修改被证明可以提高AERMOD对风洞和数值研究中检查到的各种条件进行建模的能力,以模拟建筑物附近观测到的地面浓度。

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