2019
DOI: 10.48550/arxiv.1908.08013
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Adaptive Morley FEM for the von Kármán equations with optimal convergence rates

Carsten Carstensen,
Neela Nataraj

Abstract: The adaptive nonconforming Morley finite element method (FEM) approximates a regular solution to the von Kármán equations with optimal convergence rates for sufficiently fine triangulations and small bulk parameter in the Dörfler marking. This follows from the general axiomatic framework with the key arguments of stability, reduction, discrete reliability, and quasiorthogonality of an explicit residualbased error estimator. Particular attention is on the nonlinearity and the piecewise Sobolev embeddings requir… Show more

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Cited by 2 publications
(3 citation statements)
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“…This is critical in eigenvalue analysis or problems with low-order terms; for e.g. in [15,18]. The 2 orthogonality in Lemma 2.2.e also allows a direct proof of Theorem 2.3 that circumvents the a posteriori error analysis of the consistency term as part of the medius analysis [27].…”
Section: (A)mentioning
confidence: 99%
“…This is critical in eigenvalue analysis or problems with low-order terms; for e.g. in [15,18]. The 2 orthogonality in Lemma 2.2.e also allows a direct proof of Theorem 2.3 that circumvents the a posteriori error analysis of the consistency term as part of the medius analysis [27].…”
Section: (A)mentioning
confidence: 99%
“…This is critical e.g. in eigenvalue analysis or for problems with low-order terms [22,26]. The proof of the bestapproximation of Theorem 3.2 for the modified scheme (3.9), however, does not require the 2 orthogonality in (2.9).…”
Section: Companion Operatormentioning
confidence: 99%
“…On the other hand, the efficiency requires some other additional benefit of the companion operator, which actually motivated its first design in a posteriori error control. Rate-optimal adaptive nonconforming FEM are analyzed in [4,14,15,22,25,47] and the references therein. Amongst all second-order schemes, the Morley FEM appears to be the most simple and method of choice for fourth-order problems [21].…”
Section: Introductionmentioning
confidence: 99%