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正则化格子玻尔兹曼方法的伪熵推导。

Pseudoentropic derivation of the regularized lattice Boltzmann method.

机构信息

Institute of Technology, Resource and Energy-efficient Engineering (TREE), Bonn-Rhein-Sieg University of Applied Sciences, Grantham-Allee 20, 53757 Sankt Augustin, Germany.

National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, United States.

出版信息

Phys Rev E. 2019 Aug;100(2-1):023302. doi: 10.1103/PhysRevE.100.023302.

DOI:10.1103/PhysRevE.100.023302
PMID:31574640
Abstract

The lattice Boltzmann method (LBM) facilitates efficient simulations of fluid turbulence based on advection and collision of local particle distribution functions. To ensure stable simulations on underresolved grids, the collision operator must prevent drastic deviations from local equilibrium. This can be achieved by various methods, such as the multirelaxation time, entropic, quasiequilibrium, regularized, and cumulant schemes. Complementing a part of a unified theoretical framework of these schemes, the present work presents a derivation of the regularized lattice Boltzmann method (RLBM), which follows a recently introduced entropic multirelaxation time LBM by Karlin, Bösch, and Chikatamarla (KBC). It is shown that both methods can be derived by locally maximizing a quadratic Taylor expansion of the entropy function. While KBC expands around the local equilibrium distribution, the RLBM is recovered by expanding entropy around a global equilibrium. Numerical tests were performed to elucidate the role of pseudoentropy maximization in these models. Simulations of a two-dimensional shear layer show that the RLBM successfully reproduces the largest eddies even on a 16×16 grid, while the conventional LBM becomes unstable for grid resolutions of 128×128 and lower. The RLBM suppresses spurious vortices more effectively than KBC. In contrast, simulations of the three-dimensional Taylor-Green and Kida vortices show that KBC performs better in resolving small scale vortices, outperforming the RLBM by a factor of 1.8 in terms of the effective Reynolds number.

摘要

格子玻尔兹曼方法(LBM)通过局部粒子分布函数的输运和碰撞,实现了对流体湍流的高效模拟。为了确保在欠解析网格上进行稳定的模拟,碰撞算子必须防止从局部平衡发生剧烈偏差。这可以通过各种方法来实现,例如多松弛时间、熵、拟平衡、正则化和累积量方法。本工作补充了这些方案统一理论框架的一部分,提出了正则化格子玻尔兹曼方法(RLBM)的推导,它遵循了 Karlin、Bösch 和 Chikatamarla(KBC)最近提出的具有熵多松弛时间的 LBM。结果表明,这两种方法都可以通过局部最大化熵函数的二次泰勒展开来推导。KBC 围绕局部平衡分布展开,而 RLBM 通过围绕全局平衡展开熵来恢复。进行了数值测试以阐明伪熵最大化在这些模型中的作用。二维剪切层的模拟表明,即使在 16×16 网格上,RLBM 也可以成功地再现最大的旋涡,而传统的 LBM 在网格分辨率为 128×128 及更低时变得不稳定。RLBM 比 KBC 更有效地抑制虚假涡旋。相比之下,对三维 Taylor-Green 和 Kida 涡旋的模拟表明,KBC 在分辨小尺度涡旋方面表现更好,在有效雷诺数方面比 RLBM 高出 1.8 倍。

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