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On the Convergence and Capability of the Large-Eddy Simulation of Concentration Fluctuations in Passive Plumes for a Neutral Boundary Layer at Infinite Reynolds Number

机译:关于无限雷诺数在中性边界层无源羽毛中浓度波动的大涡流模拟的收敛与能力

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摘要

Large-eddy simulation (LES) experiments have been performed using the Parallelized LES Model (PALM). A methodology for validating and understanding LES results for plume dispersion and concentration fluctuations in an atmospheric-like flow is presented. A wide range of grid resolutions is shown to be necessary for investigating the convergence of statistical characteristics of velocity and scalar fields. For the scalar, the statistical moments up to the fourth order and the shape of the concentration probability density function (p.d.f.) are examined. The mean concentration is influenced by grid resolution, with the highest resolution simulation showing a lower mean concentration, linked to larger turbulent structures. However, a clear tendency to convergence of the concentration variance is observed at the two higher resolutions. This behaviour is explained by showing that the mechanisms driving the mean and the variance are differently influenced by the grid resolution. The analysis of skewness and kurtosis allows also the obtaining of general results on plume concentration fluctuations. Irrespective of grid resolution, a family of Gamma p.d.f.s well represents the shape of the concentration p.d.f. but only beyond the peak of the concentration fluctuation intensity. In the early plume dispersion phases, the moments of the p.d.f. are in good agreement with those generated by a fluctuating plume model. To the best of our knowledge, our study demonstrates for the first time that, if resolution and averaging time are adequate, atmospheric LES provides a trustworthy representation of the high order moments of the concentration field, up to the fourth order, for a dispersing plume.
机译:使用并行化LES模型(Palm)进行了大涡模拟(LES)实验。介绍了用于验证和理解LES的羽流分散和浓度波动的方法,如大气状流动的浓度。显示各种网格分辨率是为了调查速度和标量场的统计特征的收敛需要。对于标量,检查统计矩和浓度概率密度函数(p.d.f.)的形状。平均浓度受电网分辨率的影响,具有最高分辨率模拟,显示与较大的湍流结构相关的较低平均浓度。然而,在两个更高的分辨率下观察到浓度方差的结合倾向。通过表明驱动均值的机制和方差的机制来解释这种行为是通过网格分辨率的不同影响。偏离和峰度的分析也可以获得羽流浓度波动的一般结果。无论网格分辨率如何,伽马P.D.F.S良好地代表了浓度P.D.F.的形状。但只超出浓度波动强度的峰值。在早期的羽流色散阶段,P.D.f的瞬间。与波动模型产生的人吻合良好。据我们所知,我们的研究首次展示了,如果分辨率和平均时间足够,大气LES为分散羽流提供浓度场的高阶时刻的值得信赖的代表性。

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