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arXiv 1203.0803math.NAcs.NA
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有限元外微分的后验误差估计:de Rham复形

A posteriori error estimates for finite element exterior calculus: The de Rham complex

University of Kentucky(肯塔基大学);University of Illinois at Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校)

Alan Demlow, Anil N. Hirani

AI总结:

针对de Rham复形中的Hodge-Laplace问题,提出基于残差的后验误差估计,统一处理各种Hodge-Laplace问题,并考虑调和形式及其近似的影响。

摘要:

有限元外微分(FEEC)在过去十年中被发展为一个框架,通过使用微分复形来构造和分析偏微分方程的稳定且精确的数值方法。Arnold、Falk和Winther最近的工作(\cite{ArFaWi2010})包括了对Hodge-Laplace问题的有限元方法的完善理论,包括先验误差估计。本文重点发展后验误差估计,其中计算误差被离散解和问题数据的某个可计算泛函所界定。更精确地说,我们证明了Arnold-Falk-Winther混合有限元方法用于Hodge-de Rham Laplace问题的残差型后验误差估计。虽然之前的一些工作考虑了Maxwell方程和标量Laplacian混合形式的后验误差估计,但我们所采用的方法的特点是统一处理de Rham复形中出现的各种Hodge-Laplace问题,一致使用微分形式的语言和分析框架,以及发展调和形式的后验误差估计及其近似对Hodge-Laplacian数值方法的影响。

英文摘要:

Finite element exterior calculus (FEEC) has been developed over the past decade as a framework for constructing and analyzing stable and accurate numerical methods for partial differential equations by employing differential complexes. The recent work of Arnold, Falk and Winther \cite{ArFaWi2010} includes a well-developed theory of finite element methods for Hodge Laplace problems, including a priori error estimates. In this work we focus on developing a posteriori error estimates in which the computational error is bounded by some computable functional of the discrete solution and problem data. More precisely, we prove a posteriori error estimates of residual type for Arnold-Falk-Winther mixed finite element methods for Hodge-de Rham Laplace problems. While a number of previous works consider a posteriori error estimation for Maxwell's equations and mixed formulations of the scalar Laplacian, the approach we take is distinguished by unified treatment of the various Hodge Laplace problems arising in the de Rham complex, consistent use of the language and analytical framework of differential forms, and the development of a posteriori error estimates for harmonic forms and the effects of their approximation on the resulting numerical method for the Hodge Laplacian.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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