用局部不连续伽辽金公式求解扩散方程的任意阶谱体积法

Jing An, Waixiang Cao
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引用次数: 1

摘要

本文提出并研究了两种任意阶的扩散方程谱体积格式,利用局部不连续伽辽金公式对粘性通量进行离散化。该方案的基本思想是先将扩散方程改写为等效的一阶系统,然后用SV法求解该系统。SV方案的控制体积是利用底层网格的子区间中的Gauss点或Radau点构建的,这就产生了两种SV方案,分别称为LSV和RSV方案。对基于交变通量的线性扩散方程进行了稳定性分析,建立了精确解和辅助变量的最优误差估计。此外,通过严密的数学证明,表明RSV方法在常扩散问题上与标准LDG方法是一致的。数值实验验证了这两种格式对线性和非线性扩散方程的稳定性、精度和性能。
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Any order spectral volume methods for diffusion equations using the local discontinuous Galerkin formulation
In this paper, we present and study two spectral volume (SV) schemes of arbitrary order for diffusion equations by using the local discontinuous Galerkin formulation to discretize the viscous flux. The basic idea of the scheme is to rewrite the diffusion equation into an equivalent first-order system first, and then use the SV method to solve the system. The SV scheme is designed with control volumes constructed by using the Gauss points or Radau points in subintervals of the underlying meshes, which leads to two SV schemes referred to as LSV and RSV schemes, respectively. The stability analysis for the linear diffusion equations based on alternating fluxes are provided, and optimal error estimates are established for both the exact solution and the auxiliary variable. Furthermore, a rigorous mathematical proof are given to demonstrate that the proposed RSV method is identical to the standard LDG method when applied to constant diffusion problems. Numerical experiments are presented to demonstrate the stability, accuracy and performance of the two SV schemes for both linear and nonlinear diffusion equations.
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来源期刊
CiteScore
2.70
自引率
5.30%
发文量
27
审稿时长
6-12 weeks
期刊介绍: M2AN publishes original research papers of high scientific quality in two areas: Mathematical Modelling, and Numerical Analysis. Mathematical Modelling comprises the development and study of a mathematical formulation of a problem. Numerical Analysis comprises the formulation and study of a numerical approximation or solution approach to a mathematically formulated problem. Papers should be of interest to researchers and practitioners that value both rigorous theoretical analysis and solid evidence of computational relevance.
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