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A single-step and simplified graphics processing unit lattice Boltzmann method for high turbulent flows
International Journal for Numerical Methods in Fluids ( IF 1.7 ) Pub Date : 2021-03-04 , DOI: 10.1002/fld.4976
Arturo Delgado‐Gutiérrez 1 , Pier Marzocca 2 , Diego Cárdenas 3 , Oliver Probst 4
Affiliation  

In this work, a low-computational cost graphics processing unit (GPU) lattice Boltzmann Method, coupled with the LES Vreman turbulence model is presented. The algorithm is capable of simulating low- and high-turbulence flows. In contrast to the fractional-step presented in the Simplified Lattice Boltzmann Method, the proposed work uses a single-step approach, allowing faster computations of the macroscopic variables without losing any spatial accuracy. Inspired by a recently introduced directional interpolation method for the probability distribution functions, the macroscopic variables for different locations are computed separately, enabling an even further simplification of the steps needed to predict the following time-step. Similar to the simplified lattice Boltzmann method, this work reduces the required memory allocation by storing only the macroscopic variables. Multiple benchmark cases are presented to compare with results reported in the literature. Excellent agreement with reports in the literature are obtained, while improving the overall computational performance of the algorithm.

中文翻译:

一种用于高湍流的单步简化图形处理单元格子 Boltzmann 方法

在这项工作中,提出了一种低计算成本的图形处理单元 (GPU) 格子玻尔兹曼方法,结合 LES Vreman 湍流模型。该算法能够模拟低湍流和高湍流。与 Simplified Lattice Boltzmann Method 中提出的分数步相比,所提出的工作使用单步方法,允许在不损失任何空间精度的情况下更快地计算宏观变量。受最近引入的概率分布函数方向插值方法的启发,不同位置的宏观变量分别计算,从而进一步简化了预测后续时间步长所需的步骤。类似于简化格子玻尔兹曼方法,这项工作通过仅存储宏观变量来减少所需的内存分配。提供了多个基准案例以与文献中报告的结果进行比较。获得了与文献报道的极好一致性,同时提高了算法的整体计算性能。
更新日期:2021-03-04
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