• Media type: E-Article
  • Title: New adaptive mixed finite element method (AMFEM)
  • Contributor: Carstensen, Carsten; Rabus, Hella
  • Published: Wiley, 2008
  • Published in: PAMM, 8 (2008) 1, Seite 10049-10052
  • Language: English
  • DOI: 10.1002/pamm.200810049
  • ISSN: 1617-7061
  • Keywords: General Medicine
  • Origination:
  • Footnote:
  • Description: AbstractThe need to develop reliable and efficient adaptive algorithms using mixed finite element methods arises from various applications in fluid dynamics and computational continuum mechanics. In order to save degrees of freedom, not all but just some selected set of finite element domains are refined and hence the fundamental question of convergence requires a new mathematical argument as well as the question of optimality.We will present a new adaptive algorithm for mixed finite element methods to solve the model Poisson problem, for which optimal convergence can be proved. The a posteriori error control of mixed finite element methods dates back to Alonso (1996) Error estimators for a mixed method. and Carstensen (1997) A posteriori error estimate for the mixed finite element method. The error reduction and convergence for adaptive mixed finite element methods has already been proven by Carstensen and Hoppe (2006) Error Reduction and Convergence for an Adaptive Mixed Finite Element Method, Convergence analysis of an adaptive nonconforming finite element methods.Recently, Chen, Holst and Xu (2008) Convergence and Optimality of Adaptive Mixed Finite Element Methods. presented convergence and optimality for adaptive mixed finite element methods following arguments of Rob Stevenson for the conforming finite element method. Their algorithm reduces oscillations, before applying and a standard adaptive algorithm based on usual error estimation. The proposed algorithm does this in a natural way, by switching between the reduction of either the estimated error or oscillations. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
  • Access State: Open Access