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Embedded Zassenhaus Expansion to Splitting Schemes: Theory and Multiphysics Applications

机译:Zassenhaus嵌入式扩展到拆分方案:理论和多物理场应用

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We present some operator splitting methods improved by the use of the Zassenhaus product and designed for applications to multiphysics problems. We treat iterative splitting methods that can be improved by means of the Zassenhaus product formula, which is a sequential splitting scheme. The main idea for reducing the computation time needed by the iterative scheme is to embed fast and cheap Zassenhaus product schemes, since the computation of the commutators involved is very cheap, since we are dealing with nilpotent matrices. We discuss the coupling ideas of iterative and sequential splitting techniques and their convergence. While the iterative splitting schemes converge slowly in their first iterative steps, we improve the initial convergence rates by embedding the Zassenhaus product formula. The applications are to multiphysics problems in fluid dynamics. We consider phase models in computational fluid dynamics and analyse how to obtain higher order operator splitting methods based on the Zassenhaus product. The computational benefits derive from the use of sparse matrices, which arise from the spatial discretisation of the underlying partial differential equations. Since the Zassenhaus formula requires nearly constant CPU time due to its sparse commutators, we have accelerated the iterative splitting schemes.
机译:我们介绍一些通过使用Zassenhaus产品而改进的,用于多物理场问题的操作员拆分方法。我们将处理迭代拆分方法,该方法可以通过Zassenhaus产品公式来改进,该公式是一种顺序拆分方案。减少迭代方案所需的计算时间的主要思想是嵌入快速且便宜的Zassenhaus乘积方案,因为所涉及的换向器的计算非常便宜,因为我们正在处理幂等矩阵。我们讨论了迭代和顺序拆分技术的耦合思想及其收敛。尽管迭代拆分方案在其最初的迭代步骤中收敛缓慢,但我们通过嵌入Zassenhaus乘积公式来提高初始收敛速度。这些应用程序适用于流体动力学中的多物理场问题。我们在计算流体动力学中考虑相模型,并分析如何基于Zassenhaus积获得更高阶的算子分裂方法。计算上的好处来自稀疏矩阵的使用,而稀疏矩阵的产生则来自基础偏微分方程的空间离散化。由于Zassenhaus公式由于其稀疏的换向器而需要几乎恒定的CPU时间,因此我们加快了迭代拆分方案。

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