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Mathematics of Computation

Published by the American Mathematical Society since 1960 (published as Mathematical Tables and other Aids to Computation 1943-1959), Mathematics of Computation is devoted to research articles of the highest quality in computational mathematics.

ISSN 1088-6842 (online) ISSN 0025-5718 (print)

The 2020 MCQ for Mathematics of Computation is 1.78.

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Error reduction and convergence for an adaptive mixed finite element method
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by Carsten Carstensen and R. H. W. Hoppe PDF
Math. Comp. 75 (2006), 1033-1042 Request permission

Abstract:

An adaptive mixed finite element method (AMFEM) is designed to guarantee an error reduction, also known as saturation property: after each refinement step, the error for the fine mesh is strictly smaller than the error for the coarse mesh up to oscillation terms. This error reduction property is established here for the Raviart–Thomas finite element method with a reduction factor $\rho <1$ uniformly for the $L^2$ norm of the flux errors. Our result allows for linear convergence of a proper adaptive mixed finite element algorithm with respect to the number of refinement levels. The adaptive algorithm surprisingly does not require any particular mesh design, unlike the conforming finite element method. The new arguments are a discrete local efficiency and a quasi-orthogonality estimate. The proof does not rely on duality or on regularity.
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Additional Information
  • Carsten Carstensen
  • Affiliation: Department of Mathematics, Humboldt-Universität zu Berlin, D-10099 Berlin, Germany
  • R. H. W. Hoppe
  • Affiliation: Institute of Mathematics, Universität Augsburg, D-86159 Augsburg, Germany; and Department of Mathematics, University of Houston, Houston, Texas 77204-3008
  • Received by editor(s): April 11, 2004
  • Published electronically: March 13, 2006
  • © Copyright 2006 American Mathematical Society
  • Journal: Math. Comp. 75 (2006), 1033-1042
  • MSC (2000): Primary 65N30, 65N50
  • DOI: https://doi.org/10.1090/S0025-5718-06-01829-1
  • MathSciNet review: 2219017