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On sensitivity of RANS simulations to uncertain turbulent inflow conditions

机译:关于RANS模拟对不确定湍流流入条件的敏感性

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摘要

The present study deals with gPC-based analysis of the sensitivity of URANS simulations to uncertain inflow conditions. The massively separated flow around a square cylinder, which is a classical test case, is selected. Three popular turbulence models are selected, i.e. standard low-Reynolds k-ε model, k-ω model and a realizable k-ε model. The turbulent viscosity ratio, which is observed to vary a lot according to different authors in this configuration, is taken as an uncertain parameter to illustrate the potential applications of the present methodology. It is found that the realizable k-ε model behaves quite stably, and predicts nearly consistent results in all simulations. In contrast, the other two models are very sensitive to random turbulent inflow condition in both cases, especially the standard k-ω model, resulting in a significant weakness of usual validation procedures for turbulence models.
机译:本研究涉及基于URANS模拟对不确定流入条件的敏感性的基于gPC的分析。选择了作为经典测试案例的围绕方形圆柱体的大量分离流。选择了三种流行的湍流模型,即标准低雷诺兹k-ε模型,k-ω模型和可实现的k-ε模型。湍流粘度比是不确定的参数,用来说明本方法的潜在应用。湍流粘度比根据不同的作者在该配置中观察到的变化很大。发现可实现的k-ε模型的行为相当稳定,并且在所有模拟中都可以预测几乎一致的结果。相反,在这两种情况下,其他两个模型对随机湍流流入条件都非常敏感,尤其是标准k-ω模型,这导致通常的湍流模型验证程序存在很大缺陷。

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