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首页> 外文期刊>Applied numerical mathematics >Splitting-methods based on Approximate Matrix Factorization and Radau-IIA formulas for the time integration of advection diffusion reaction PDEs
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Splitting-methods based on Approximate Matrix Factorization and Radau-IIA formulas for the time integration of advection diffusion reaction PDEs

机译:基于近似矩阵分解和Radau-IIA公式的对流扩散反应PDE时间积分的分裂方法

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摘要

A family of splitting methods for the time integration of evolutionary Advection Diffusion Reaction Partial Differential Equations (PDEs) semi-discretized in space by Finite Differences is obtained. The splitting is performed in the Jacobian matrix by using the Approximate Matrix Factorization (AMF) and by considering up to three inexact Newton Iterations applied to the two-stage Radau 1IA method along with a very simple predictor. The overall process allows to reduce the storage and the algebraic costs involved in the numerical solution of the multidimensional linear systems to the level of 1D-dimensional linear systems with small bandwidths. Some specific AMF-Radau methods are constructed after studying the expression for the local error in semi-linear equations, and their linear stability properties are widely studied. The wedge of stability of the methods depends on the number of splittings used for the Jacobian matrix of the spatial semidiscretized ODEs, J_h = Σ_(j=1)~d J_h, j, where h stands for the spatial grid resolution. A-stability is proven for the cases d = 1, 2, and A(0)-stability for any d ≥ 1. Numerical experiments on a 3D semi-linear advection diffusion reaction test problem and a 2D-combustion model are presented. The experiments show that the methods compare well with standard classical methods in parabolic problems and can also be successfully used for advection dominated problems when some diffusion or stiff reactions are present. In the latter case the stability imposes restrictions on the number of splitting terms (d).
机译:获得了用有限差分对空间中的半离散演化对流扩散反应偏微分方程(PDE)进行时间积分的一系列分裂方法。通过使用近似矩阵因式分解(AMF),并考虑最多三个不精确的牛顿迭代法应用于两级Radau 1IA方法以及非常简单的预测变量,可以在Jacobian矩阵中进行拆分。整个过程可以将多维线性系统数值解决方案中涉及的存储和代数成本降低到具有较小带宽的一维线性系统的水平。通过研究半线性方程局部误差的表达式,构造了一些特定的AMF-Radau方法,并对它们的线性稳定性进行了广泛的研究。这些方法的稳定性取决于用于空间半离散ODE的Jacobian矩阵的分裂数,J_h =Σ_(j = 1)〜d J_h,j,其中h表示空间网格分辨率。对于d = 1、2和任意d≥1的情况,证明了A稳定性。给出了3D半线性对流扩散反应测试问题和2D燃烧模型的数值实验。实验表明,该方法与标准经典方法在抛物线问题中具有很好的对比,当存在一些扩散或刚性反应时,也可以成功用于对流占优的问题。在后一种情况下,稳定性对分割项(d)的数量施加了限制。

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