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Memory-efficient Lattice Boltzmann Method for low Reynolds number flows
Computer Physics Communications ( IF 6.3 ) Pub Date : 2021-06-02 , DOI: 10.1016/j.cpc.2021.108044
Maciej Matyka , Michał Dzikowski

The Lattice Boltzmann Method algorithm is simplified by assuming constant numerical viscosity (the relaxation time is fixed at τ=1). This leads to the removal of the distribution function from the computer memory. To test the solver the Poiseuille and Driven Cavity flows are simulated and analyzed. The error of the solution decreases with the grid size L as L2. Compared to the standard algorithm, the presented formulation is simpler and shorter in implementation. It is less error-prone and needs significantly less working memory in low Reynolds number flows. Our tests showed that the algorithm is less efficient in multiphase flows. To overcome this problem, further extension and the moments-only formulation was derived, inspired by the Multi-Relaxation Time (MRT) approach for single component multiphase flows.



中文翻译:

低雷诺数流的内存高效格子玻尔兹曼方法

Lattice Boltzmann Method 算法通过假设数值粘度恒定(弛豫时间固定为 τ=1)。这导致从计算机内存中删除分布函数。为了测试求解器,我们对泊肃叶流和驱动腔流进行了模拟和分析。解的误差随着网格大小 L 的增加而减小:-2. 与标准算法相比,所提出的公式在实现上更简单、更短。它不易出错,并且在低雷诺数流中需要的工作内存显着减少。我们的测试表明该算法在多相流中效率较低。为了克服这个问题,受用于单组分多相流的多松弛时间 (MRT) 方法的启发,进一步扩展和仅矩公式被推导出来。

更新日期:2021-06-08
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