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Approximate factorization for time-dependent partial differential equations

机译:与时间有关的偏微分方程的近似因式分解

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The first application of approximate factorization in the numerical solution of time-dependent partial differential equations (PDEs) can be traced back to the celebrated papers of Peaceman and Rachford and of Douglas of 1955. For linear problems, the Peaceman-Rachford-Douglas method can be derived from the Crank-Nicolson method by the approximate factorization of the system matrix in the linear system to be solved. This factorization is based on a splitting of the system matrix. In the numerical solution of time-dependent PDEs we often encounter linear systems whose system matrix has a complicated structure, but can be split into a sum of matrices with a simple structure. In such cases, it is attractive to replace the system matrix by an approximate factorization based on this splitting. This contribution surveys various possibilities for applying approximate factorization to PDEs and presents a number of new stability results for the resulting integration methods.
机译:近似因式分解在时间相关的偏微分方程(PDE)数值解中的首次应用可以追溯到1955年的Peaceman和Rachford和Douglas的著名论文。对于线性问题,Peaceman-Rachford-Douglas方法可以由Crank-Nicolson方法得出,通过求解线性系统中的系统矩阵进行近似分解。该分解基于系统矩阵的分解。在与时间有关的PDE的数值解中,我们经常遇到线性系统,其系统矩阵具有复杂的结构,但可以分解为具有简单结构的矩阵之和。在这种情况下,基于此拆分将系统矩阵替换为近似因式分解是有吸引力的。此贡献调查了将近似因式分解应用于PDE的各种可能性,并为所得积分方法提供了许多新的稳定性结果。

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