Convergence analysis of an energy-stable linearized virtual element method for the strongly damped Klein-Gordon equation

IF 2.5 2区 数学 Q1 MATHEMATICS, APPLIED
Zhixin Liu , Minghui Song , Yuhang Zhang
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引用次数: 0

Abstract

In this paper, we propose and analyze an efficient, linearized, fully discrete scheme for the nonlinear, strongly damped Klein-Gordon equation on polygonal meshes. The numerical scheme uses a conforming virtual element method for spatial discretization and a modified leapfrog (central finite difference) scheme for time discretization, with the nonlinear term |u|p1u is treated semi-implicitly. We first prove that the proposed scheme is energy dissipative in the sense of discrete energy, and then the stability of the numerical solution in the H1-norm is established using mathematical induction, which plays an important role in handling the nonlinear term. By applying the boundedness of the numerical solution and the Sobolev embedding inequality, we derive the optimal H1 error estimate of order O(hk+τ2) without imposing any ratio restrictions between the time step τ and the mesh size h. Additionally, we remark that the leapfrog virtual element scheme can be applied to some more complex nonlinear damped wave equations. Finally, some numerical examples are provided to confirm the theoretical results.
强阻尼Klein-Gordon方程能量稳定线性化虚元法的收敛性分析
本文提出并分析了多边形网格上非线性强阻尼Klein-Gordon方程的一种有效的、线性化的、完全离散格式。数值格式采用一致性虚元法进行空间离散,采用改进的跳越(中心有限差分)格式进行时间离散,并对非线性项| ~ |p ~ 1u进行半隐式处理。首先证明了所提格式在离散能量意义上是能量耗散的,然后利用数学归纳法建立了数值解在h1范数下的稳定性,这对非线性项的处理起着重要作用。通过应用数值解的有界性和Sobolev嵌入不等式,我们得到了O阶(hk+τ2)的最优H1误差估计,而不需要在时间步长τ和网格尺寸h之间施加任何比例限制。此外,我们注意到跳跃虚元格式可以应用于一些更复杂的非线性阻尼波方程。最后通过数值算例对理论结果进行了验证。
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
Computers & Mathematics with Applications
Computers & Mathematics with Applications 工程技术-计算机:跨学科应用
CiteScore
5.10
自引率
10.30%
发文量
396
审稿时长
9.9 weeks
期刊介绍: Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).
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