非发散型椭圆型偏微分方程的计算多尺度方法

IF 1 4区 数学 Q3 MATHEMATICS, APPLIED Computational Methods in Applied Mathematics Pub Date : 2022-11-24 DOI:10.48550/arXiv.2211.13731
P. Freese, D. Gallistl, D. Peterseim, Timo Sprekeler
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引用次数: 1

摘要

摘要本文提出了一种新的计算多尺度方法,用于求解具有满足Cordes条件的异质系数的非微分形式的线性二阶椭圆型偏微分方程。该构造遵循局部正交分解(LOD)的方法,并通过在数值均匀化的精神下在精细尺度上解决局部单元问题来提供算子自适应的粗略空间。粗空间的自由度与齐次问题的非协调和混合有限元方法有关。一种示例性方法的严格误差分析表明,从发散形式的偏微分方程中已知的LOD方法的有利性质,即其超出尺度分离和周期性的适用性和准确性,对于非发散形式的问题仍然有效。
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Computational Multiscale Methods for Nondivergence-Form Elliptic Partial Differential Equations
Abstract This paper proposes novel computational multiscale methods for linear second-order elliptic partial differential equations in nondivergence form with heterogeneous coefficients satisfying a Cordes condition. The construction follows the methodology of localized orthogonal decomposition (LOD) and provides operator-adapted coarse spaces by solving localized cell problems on a fine scale in the spirit of numerical homogenization. The degrees of freedom of the coarse spaces are related to nonconforming and mixed finite element methods for homogeneous problems. The rigorous error analysis of one exemplary approach shows that the favorable properties of the LOD methodology known from divergence-form PDEs, i.e., its applicability and accuracy beyond scale separation and periodicity, remain valid for problems in nondivergence form.
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来源期刊
CiteScore
2.40
自引率
7.70%
发文量
54
期刊介绍: The highly selective international mathematical journal Computational Methods in Applied Mathematics (CMAM) considers original mathematical contributions to computational methods and numerical analysis with applications mainly related to PDEs. CMAM seeks to be interdisciplinary while retaining the common thread of numerical analysis, it is intended to be readily readable and meant for a wide circle of researchers in applied mathematics. The journal is published by De Gruyter on behalf of the Institute of Mathematics of the National Academy of Science of Belarus.
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