线性抛物线积分微分方程的混合虚拟元素法

IF 1.3 4区 数学 Q1 MATHEMATICS International Journal of Numerical Analysis and Modeling Pub Date : 2024-06-01 DOI:10.4208/ijnam2024-1020
Meghana Suthar, Sangita Yadav
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引用次数: 0

摘要

本文针对线性抛物线积分微分方程(PIDE)的空间离散化,结合后向尤勒时间离散化方法,开发并分析了一种混合虚拟元素方案。混合 Ritz-Volterra 投影的引入极大地帮助了积分项的管理,为两个未知数 $p(x, t)$ 和 $\sigma(x, t) $ 带来了阶数为 $O(h^{k+1})$的最优收敛。此外,还为阶数为 $O(h^{k+2})$的离散解的超收敛提出了逐步分析。讨论了几个计算实验,以验证所提方案的计算效率,并支持理论结论。
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Mixed Virtual Element Method for Linear Parabolic Integro-Differential Equations
This article develops and analyses a mixed virtual element scheme for the spatial discretization of linear parabolic integro-differential equations (PIDEs) combined with backward Euler’s temporal discretization approach. The introduction of mixed Ritz-Volterra projection significantly helps in managing the integral terms, yielding optimal convergence of order $O(h^{k+1})$ for the two unknowns $p(x, t)$ and $\sigma(x, t).$ In addition, a step-by-step analysis is proposed for the super convergence of the discrete solution of order $O(h^{k+2}).$ The fully discrete case has also been analyzed and discussed to achieve $O(\tau)$ in time. Several computational experiments are discussed to validate the proposed schemes computational efficiency and support the theoretical conclusions.
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来源期刊
CiteScore
2.10
自引率
9.10%
发文量
1
审稿时长
6-12 weeks
期刊介绍: The journal is directed to the broad spectrum of researchers in numerical methods throughout science and engineering, and publishes high quality original papers in all fields of numerical analysis and mathematical modeling including: numerical differential equations, scientific computing, linear algebra, control, optimization, and related areas of engineering and scientific applications. The journal welcomes the contribution of original developments of numerical methods, mathematical analysis leading to better understanding of the existing algorithms, and applications of numerical techniques to real engineering and scientific problems. Rigorous studies of the convergence of algorithms, their accuracy and stability, and their computational complexity are appropriate for this journal. Papers addressing new numerical algorithms and techniques, demonstrating the potential of some novel ideas, describing experiments involving new models and simulations for practical problems are also suitable topics for the journal. The journal welcomes survey articles which summarize state of art knowledge and present open problems of particular numerical techniques and mathematical models.
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