Guaranteed error bounds and local indicators for adaptive solvers using stabilised space-time IgA approximations to parabolic problems

Abstract
The paper is concerned with space–time IgA approximations to parabolic initial–boundary value problems. We deduce guaranteed and fully computable error bounds adapted to special features of such type of approximations and investigate their efficiency. The derivation of error estimates is based on the analysis of the corresponding integral identity and exploits purely functional arguments in the maximal parabolic regularity setting. The estimates are valid for any approximation from the admissible (energy) class and do not contain mesh-dependent constants. They provide computable and fully guaranteed error bounds for the norms arising in stabilised space–time approximations. Furthermore, a posterior error estimates yield efficient error indicators enhancing the performance of adaptive solvers and generate very successful mesh refinement procedures. Theoretical results are verified with a series of numerical examples, in which approximate solutions and the corresponding fluxes are recovered by IgA techniques. The numerical results confirm the high efficiency of the method in the context of the two main goals of a posteriori error analysis: estimation of global errors and mesh adaptation.
Main Authors
Format
Articles Research article
Published
2019
Series
Subjects
Publication in research information system
Publisher
Elsevier
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201909114108Käytä tätä linkitykseen.
Review status
Peer reviewed
ISSN
0898-1221
DOI
https://doi.org/10.1016/j.camwa.2019.04.009
Language
English
Published in
Computers and Mathematics with Applications
Citation
  • Langer, U., Matculevich, S., & Repin, S. (2019). Guaranteed error bounds and local indicators for adaptive solvers using stabilised space-time IgA approximations to parabolic problems. Computers and Mathematics with Applications, 78(8), 2641-2671. https://doi.org/10.1016/j.camwa.2019.04.009
License
In CopyrightOpen Access
Additional information about funding
The research is supported by the Austrian Science Fund (FWF) through the NFN S117-03 project. This support is gratefully acknowledged. Furthermore, we appreciate the technical support and advises from Dr. Angelos Mantzaflaris, the main coordinator and developer of the open-source C++ library G+Smo that was used in our implementation and numerical tests. Last but not least, the authors would like to express their thanks to the anonymous referees for their helpful hints and valuable suggestions.
Copyright© 2019 Elsevier Ltd

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