Reliable anisotropic-adaptive discontinuous Galerkin method for simplified P N approximations of radiative transfer

Reliable anisotropic-adaptive discontinuous Galerkin method for simplified... In this paper we present the analysis for the error estimator for radiative transfer problems presented in Giani and Seaid (2016) where we showed the capabilities of the error estimator to accurately drive the adaptivity to resolve steep boundary layers, which are among the difficulties that most numerical methods fail to resolve accurately. We prove reliability for the error estimator in terms of a global upper bound of the error measured in the natural norm. We present a series of numerical experiments to test the efficiency of this approach within a fully automated h p -adaptive refinement algorithm. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Computational and Applied Mathematics Elsevier

Reliable anisotropic-adaptive discontinuous Galerkin method for simplified P N approximations of radiative transfer

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier B.V.
ISSN
0377-0427
eISSN
1879-1778
D.O.I.
10.1016/j.cam.2017.12.039
Publisher site
See Article on Publisher Site

Abstract

In this paper we present the analysis for the error estimator for radiative transfer problems presented in Giani and Seaid (2016) where we showed the capabilities of the error estimator to accurately drive the adaptivity to resolve steep boundary layers, which are among the difficulties that most numerical methods fail to resolve accurately. We prove reliability for the error estimator in terms of a global upper bound of the error measured in the natural norm. We present a series of numerical experiments to test the efficiency of this approach within a fully automated h p -adaptive refinement algorithm.

Journal

Journal of Computational and Applied MathematicsElsevier

Published: Aug 1, 2018

References

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