超越尺度分离的数值均质化

IF 16.3 1区 数学 Q1 MATHEMATICS
R. Altmann, P. Henning, D. Peterseim
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引用次数: 44

摘要

数值均匀化是求解多尺度偏微分方程的一种方法。它旨在将复杂的大规模问题简化为在某些感兴趣的目标尺度上有效的简化数值模型,从而考虑到在较小尺度上无法解决的特征的影响。均匀化数学理论中的建设性方法仅限于具有明确尺度分离的问题,而现代数值均匀化方法可以准确地处理具有连续尺度的问题。本文回顾了嵌入在历史背景下的这些方法,并为其设计和数值分析提供了统一的变分框架。除了典型的椭圆模型问题外,这里所涵盖的一类偏微分方程还包括非均匀介质中的波散射,并作为更一般的多物理场问题的模板。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Numerical homogenization beyond scale separation
Numerical homogenization is a methodology for the computational solution of multiscale partial differential equations. It aims at reducing complex large-scale problems to simplified numerical models valid on some target scale of interest, thereby accounting for the impact of features on smaller scales that are otherwise not resolved. While constructive approaches in the mathematical theory of homogenization are restricted to problems with a clear scale separation, modern numerical homogenization methods can accurately handle problems with a continuum of scales. This paper reviews such approaches embedded in a historical context and provides a unified variational framework for their design and numerical analysis. Apart from prototypical elliptic model problems, the class of partial differential equations covered here includes wave scattering in heterogeneous media and serves as a template for more general multi-physics problems.
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来源期刊
Acta Numerica
Acta Numerica MATHEMATICS-
CiteScore
26.00
自引率
0.70%
发文量
7
期刊介绍: Acta Numerica stands as the preeminent mathematics journal, ranking highest in both Impact Factor and MCQ metrics. This annual journal features a collection of review articles that showcase survey papers authored by prominent researchers in numerical analysis, scientific computing, and computational mathematics. These papers deliver comprehensive overviews of recent advances, offering state-of-the-art techniques and analyses. Encompassing the entirety of numerical analysis, the articles are crafted in an accessible style, catering to researchers at all levels and serving as valuable teaching aids for advanced instruction. The broad subject areas covered include computational methods in linear algebra, optimization, ordinary and partial differential equations, approximation theory, stochastic analysis, nonlinear dynamical systems, as well as the application of computational techniques in science and engineering. Acta Numerica also delves into the mathematical theory underpinning numerical methods, making it a versatile and authoritative resource in the field of mathematics.
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