A Diagonalization-Based Parallel-in-Time Algorithm for Crank-Nicolson’s Discretization of the Viscoelastic Equation

IF 1.2 4区 数学 Q2 MATHEMATICS, APPLIED
Fu Li, Yingxiang Xu
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引用次数: 0

Abstract

In this paper, we extend a diagonalization-based parallel-in-time (PinT) algorithm to the viscoelastic equation. The central difference method is used for spatial discretization, while for temporal discretization, we use the Crank-Nicolson scheme. Then an all-at-once system collecting all the solutions at each time level is formed and solved using a fixed point iteration preconditioned by an $α$-circulant matrix in parallel. Via a rigorous analysis, we find that the spectral radius of the iteration matrix is uniformly bounded by $α/(1 − α),$ independent of the model parameters (the damping coefficient $\varepsilon$ and the wave velocity $\sqrt{\gamma}$) and the discretization parameters (the time step $\tau$ and the spatial mesh size $h$). Unlike the classical wave equation with Dirichlet boundary condition where the upper bound $α/(1 − α)$ is very sharp, we find that the occurrence of the damping term $−\varepsilon∆y_t,$ as well as the large final time $T,$ leads to even faster convergence of the algorithm, especially when $α$ is not very small. We illustrate our theoretical findings with several numerical examples.
基于对角线化的时间并行算法,用于粘弹性方程的克兰克-尼科尔森离散化
在本文中,我们将基于对角化的实时并行(PinT)算法扩展到粘弹性方程。空间离散化采用中心差分法,时间离散化采用 Crank-Nicolson 方案。然后形成一个一次性系统,收集每个时间级别上的所有解,并使用定点迭代进行并行求解,其前提条件是一个 $α$ 循环矩阵。通过严格分析,我们发现迭代矩阵的谱半径均匀地受 $α/(1 - α) $ 约束,与模型参数(阻尼系数 $\varepsilon$ 和波速 $\sqrt{\gamma}$)和离散化参数(时间步长 $\tau$ 和空间网格大小 $h$)无关。与具有迪里希特边界条件的经典波方程不同,我们发现阻尼项 $-\varepsilon∆y_t,$ 的出现以及较大的最终时间 $T,$ 会导致算法更快地收敛,尤其是当 $α$ 不是很小的时候。我们用几个数值例子来说明我们的理论发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.60
自引率
8.30%
发文量
48
期刊介绍: The East Asian Journal on Applied Mathematics (EAJAM) aims at promoting study and research in Applied Mathematics in East Asia. It is the editorial policy of EAJAM to accept refereed papers in all active areas of Applied Mathematics and related Mathematical Sciences. Novel applications of Mathematics in real situations are especially welcome. Substantial survey papers on topics of exceptional interest will also be published occasionally.
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