On adaptive Eulerian-Lagrangian method for linear convection-diffusion problems

Xiaozhe Hu, Young Ju Lee, Jinchao Xu, Chen Song Zhang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In this paper, we consider the adaptive Eulerian-Lagrangian method (ELM) for linear convection-diffusion problems. Unlike classical a posteriori error estimations, we estimate the temporal error along the characteristics and derive a new a posteriori error bound for ELM semi-discretization. With the help of this proposed error bound, we are able to show the optimal convergence rate of ELM for solutions with minimal regularity. Furthermore, by combining this error bound with a standard residual-type estimator for the spatial error, we obtain a posteriori error estimators for a fully discrete scheme. We present numerical tests to demonstrate the efficiency and robustness of our adaptive algorithm. © 2013 Springer Science+Business Media New York.
Original languageEnglish (US)
Pages (from-to)90-114
Number of pages25
JournalJournal of Scientific Computing
Volume58
Issue number1
DOIs
StatePublished - Jan 1 2014
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science
  • Software
  • General Engineering

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