A new equilibrated residual method improving accuracy and efficiency of flux-free error estimates

This paper presents a new methodology to compute guaranteed upper bounds for the energy norm of the error in the context of linear finite element approximations of the reaction–diffusion equation. The new approach revisits the ideas in Parés et al. (2009) [6, 4], with the goal of substantially reduc...

ver descrição completa

Detalhes bibliográficos
Autores: Parés Mariné, Núria|||0000-0002-2914-9904, Díez, Pedro|||0000-0001-6464-6407
Formato: artículo
Fecha de publicación:2017
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/99967
Acesso em linha:https://hdl.handle.net/2117/99967
https://dx.doi.org/10.1016/j.cma.2016.10.010
Access Level:acceso abierto
Palavra-chave:Numerical analysis
Exact/guaranteed/strict bounds
Fully computable a posteriori error estimation
Adaptivity
Reaction–diffusion equation
Flux-free
Equilibrated boundary tractions
Anàlisi numèrica
Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes en elements finits
Descrição
Resumo:This paper presents a new methodology to compute guaranteed upper bounds for the energy norm of the error in the context of linear finite element approximations of the reaction–diffusion equation. The new approach revisits the ideas in Parés et al. (2009) [6, 4], with the goal of substantially reducing the computational cost of the flux-free method while retaining the good quality of the bounds. The new methodology provides also a technique to compute equilibrated boundary tractions improving the quality of standard equilibration strategies. The zeroth-order equilibration conditions are imposed using an alternative less restrictive form of the first-order equilibration conditions, along with a new efficient minimization criterion. This new equilibration strategy provides much more accurate upper bounds for the energy and requires only doubling the dimension of the local linear systems of equations to be solved.