4.5 Article

CONVERGENCE AND OPTIMALITY OF ADAPTIVE MIXED FINITE ELEMENT METHODS

Journal

MATHEMATICS OF COMPUTATION
Volume 78, Issue 265, Pages 35-53

Publisher

AMER MATHEMATICAL SOC
DOI: 10.1090/S0025-5718-08-02155-8

Keywords

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Funding

  1. NSF [0411723, 022560, DMS-0619587, DMS-0609727, NSFC-10528102]
  2. DOE [DE-FG02-04ER25620, DE-FG02-05ER25707]
  3. NIH [P41RR08605]
  4. Alexander Humboldt foundation

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The convergence and optimality of adaptive mixed finite element methods for the Poisson equation are established in this paper. The main difficulty for mixed finite element methods is the lack of minimization principle and thus the failure of orthogonality. A quasi-orthogonality property is proved using the fact that the error is orthogonal to the divergence free subspace, while the part of the error that is not divergence free can be bounded by the data oscillation using a discrete stability result. This discrete stability result is also used to get a localized discrete upper bound which is crucial for the proof of the optimality of the adaptive approximation.

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