A posteriori error estimator based on ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
A posteriori error estimator based on gradient recovery by averaging for discontinuous Galerkin methods
Author(s) :
Creusé, Emmanuel [Auteur]
SImulations and Modeling for PArticles and Fluids [SIMPAF]
Nicaise, Serge [Auteur]
Laboratoire de Mathématiques et leurs Applications de Valenciennes - EA 4015 [LAMAV]
SImulations and Modeling for PArticles and Fluids [SIMPAF]
Nicaise, Serge [Auteur]
Laboratoire de Mathématiques et leurs Applications de Valenciennes - EA 4015 [LAMAV]
Journal title :
Journal of Computational and Applied Mathematics
Pages :
2903-2915
Publisher :
Elsevier
Publication date :
2010-09-15
ISSN :
0377-0427
English keyword(s) :
A posteriori estimator
Discontinuous Galerkin finite elements
Discontinuous Galerkin finite elements
HAL domain(s) :
Mathématiques [math]/Analyse numérique [math.NA]
English abstract : [en]
We consider some (anisotropic and piecewise constant) diffusion problems in domains of R^2, approximated by a discontinuous Galerkin method with polynomials of any fixed degree. We propose an a posteriori error estimator ...
Show more >We consider some (anisotropic and piecewise constant) diffusion problems in domains of R^2, approximated by a discontinuous Galerkin method with polynomials of any fixed degree. We propose an a posteriori error estimator based on gradient recovery by averaging. It is shown that this estimator gives rise to an upper bound where the constant is one up to some additional terms that guarantee reliability. The lower bound is also established. Moreover these additional terms are negligible when the recovered gradient is super convergent. The reliability and efficiency of the proposed estimator in confirmed by some numerical tests.Show less >
Show more >We consider some (anisotropic and piecewise constant) diffusion problems in domains of R^2, approximated by a discontinuous Galerkin method with polynomials of any fixed degree. We propose an a posteriori error estimator based on gradient recovery by averaging. It is shown that this estimator gives rise to an upper bound where the constant is one up to some additional terms that guarantee reliability. The lower bound is also established. Moreover these additional terms are negligible when the recovered gradient is super convergent. The reliability and efficiency of the proposed estimator in confirmed by some numerical tests.Show less >
Language :
Anglais
Popular science :
Non
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