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From single-scale turbulence models to multiple-scale and subgrid-scale models by Fourier transform

机译:通过傅立叶变换,从单尺度湍流模型到多尺度和亚网格尺度模型

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摘要

A theoretical method based on mathematical physics formalism that allows transposition of turbulence modeling methods from URANS (unsteady Reynolds averaged Navier–Stokes) models, to multiple-scale models and large eddy simulations (LES) is presented. The method is based on the spectral Fourier transform of the dynamic equation of the two-point fluctuating velocity correlations with an extension to the case of non-homogenous turbulence. The resulting equation describes the evolution of the spectral velocity correlation tensor in wave vector space. Then, we show that the full wave number integration of the spectral equation allows one to recover usual one-point statistical closure whereas the partial integration based on spectrum splitting gives rise to partial integrated transport models (PITM). This latter approach, depending on the type of spectral partitioning used, can yield either a statistical multiple-scale model or subfilter transport models used in LES or hybrid methods, providing some appropriate approximations are made. Closure hypotheses underlying these models are then discussed by reference to physical considerations with emphasis on identification of tensorial fluxes that represent turbulent energy transfer or dissipation. Some experiments such as the homogeneous axisymmetric contraction, the decay of isotropic turbulence, the pulsed turbulent channel flow and a wall injection induced flow are then considered as typical possible applications for illustrating the potentials of these models.
机译:提出了一种基于数学物理学形式主义的理论方法,该方法允许将湍流建模方法从URANS(非稳态雷诺平均Navier–Stokes)模型转换为多尺度模型和大涡模拟(LES)。该方法基于两点波动速度相关性动力学方程的谱傅里叶变换,并扩展到非均匀湍流的情况。结果方程描述了波矢空间中谱速度相关张量的演化。然后,我们证明了频谱方程的全波数积分可以使人们恢复通常的单点统计闭包,而基于频谱分裂的部分积分则产生了部分积分传输模型(PITM)。根据所使用的频谱划分的类型,后一种方法可以得出LES或混合方法中使用的统计多尺度模型或子滤波器传输模型,只要做出一些适当的近似即可。然后,参考物理考虑因素讨论这些模型基础的封闭假设,重点是确定代表湍流能量转移或耗散的张量通量。一些实验,例如均质轴对称收缩,各向同性湍流的衰减,脉冲湍流通道流动和壁注入诱导流动,被认为是说明这些模型潜力的典型应用。

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