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Hybrid lattice Boltzmann-direct simulation Monte Carlo approach for flows in three-dimensional geometries

机译:Hybrid格子Boltzmann-Direct Simulation Monte Carlo在三维几何形状中流动的方法

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We present the results of a comparative study performed with three numerical methods applied to a flow in a three-dimensional geometry characterized by weak compressibility and large rarefaction effects. The employed methods, all based on the kinetic theory of gases, are the Lattice Boltzmann Method (LBM) in a regularized formulation, the Direct Simulation Monte Carlo (DSMC) approach and a hybrid method coupling the LBM and the DSMC recently developed by Di Staso et al., in this contribution extended to the case of simulations involving many particles and three-dimensional geometries. Owing to the common kinetic nature shared by the employed methods and to their implementation in a single code infrastructure, a detailed comparison of the results can be performed on a quantitative ground. The numerical results permit to determine, for the studied flow problem, the range of applicability in terms of a geometry-based Knudsen number for the present LBM formulation. The need to employ the hybrid method is justified by the very large computational cost of the DSMC simulation. Limitations of the current hybrid method formulation in treating thermal and large compressibility effects are underlined and possible strategies to overcome them are delineated. Finally, good scalability properties of the parallel algorithms, as well as the large computational cost reduction guaranteed by the hybrid method, while providing an accurate solution, are demonstrated. (C) 2018 Elsevier Ltd. All rights reserved.
机译:我们介绍了用三维几何形状的三个数值方法进行的比较研究的结果,其特征在于弱压缩性和大稀疏效应。所有基于气体的动力学理论的所采用的方法是晶格Boltzmann方法(LBM)在正则化配方中,直接仿真蒙特卡罗(DSMC)方法和耦合LBM和最近由DI STAS开发的DSMC的混合方法等人,在这种贡献中,延伸到涉及许多粒子和三维几何形状的模拟的情况。由于采用的方法共享的常见动态性,并且在单一代码基础设施中的实现中,可以对定量地进行结果进行详细比较。对于研究的流动问题,数值结果允许确定用于本LBM制剂的基于几何形状的knudsen号的适用性范围。采用混合方法的需要是通过DSMC仿真的非常大的计算成本来典范。当前杂种方法制剂在处理热量和大压缩效应中的局限性下划线,克服它们的可能策略是划定的。最后,证明了并行算法的良好可扩展性,以及通过混合方法保证的大型计算成本降低,同时提供准确的解决方案。 (c)2018年elestvier有限公司保留所有权利。

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