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首页> 外文期刊>Advances in Engineering Software >Domain decomposition based coupling between the lattice Boltzmann method and traditional CFD methods-Part Ⅰ: Formulation and application to the 2-D Burgers' equation
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Domain decomposition based coupling between the lattice Boltzmann method and traditional CFD methods-Part Ⅰ: Formulation and application to the 2-D Burgers' equation

机译:晶格玻尔兹曼方法与传统CFD方法之间基于区域分解的耦合-第一部分:二维Burgers方程的公式化和应用

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摘要

The lattice Boltzmann method is being increasingly employed in the field of computational fluid dynamics due to its computational efficiency. Floating-point operations in the lattice Boltzmann method involve local data and therefore allow easy cache optimization and parallelization. Due to this, the cache-optimized lattice Boltzmann method has superior computational performance over traditional finite difference methods for solving unsteady flow problems. When solving steady flow problems, the explicit nature of the lattice Boltzmann discretization limits the time step size and therefore the efficiency of the lattice Boltzmann method for steady flows. To quantify the computational performance of the lattice Boltzmann method for steady flows, a comparison study between the lattice Boltzmann method (LBM) and the alternating direction implicit (ADI) method was performed using the 2-D steady Burgers' equation. The comparison study showed that the LBM performs comparatively poor on high-resolution meshes due to smaller time step sizes, while on coarser meshes where the time step size is similar for both methods, the cache-optimized LBM performance is superior. Because flow domains can be discret-ized with multiblock grids consisting of coarse and fine grid blocks, the cache-optimized LBM can be applied on the coarse grid block while the traditional implicit methods are applied on the fine grid blocks. This paper finds the coupled cache-optimized lattice Boltzmann-ADI method to be faster by a factor of 4.5 over the traditional methods while maintaining similar accuracy.
机译:格子玻尔兹曼方法由于其计算效率而越来越多地用于计算流体动力学领域。格子Boltzmann方法中的浮点运算涉及本地数据,因此可以轻松实现缓存优化和并行化。因此,与传统的有限差分方法相比,高速缓存优化的格子Boltzmann方法具有出色的计算性能,可以解决非稳态流动问题。当解决稳态流动问题时,晶格Boltzmann离散化的显式性质限制了时间步长,从而限制了稳态流动的晶格Boltzmann方法的效率。为了量化稳态流动的格子Boltzmann方法的计算性能,使用二维稳态Burgers方程对格子Boltzmann方法(LBM)和交替方向隐式(ADI)方法进行了比较研究。对比研究表明,由于时间步长较小,因此LBM在高分辨率网格上的性能相对较差,而在两种方法的时间步长相似的较粗的网格上,缓存优化的LBM性能则更好。因为可以使用由粗糙和精细网格块组成的多块网格来离散化流域,所以可以将高速缓存优化的LBM应用于粗糙网格块,而将传统的隐式方法应用于精细网格块。本文发现,结合高速缓存优化的晶格Boltzmann-ADI耦合方法比传统方法要快4.5倍,同时保持了相似的精度。

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