Goal-Oriented p-Adaptivity using Unconventional Error Representations for a 1D Steady State Convection-Diffusion Problem

Vincent Darrigrand, Ángel Rodríguez-Rozas, David Pardo, Ignacio Muga

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Resumen

This work proposes the use of an alternative error representation for Goal-Oriented Adaptivity (GOA) in context of steady state convection dominated diffusion problems. It introduces an arbitrary operator for the computation of the error of an alternative dual problem. From the new representation, we derive element-wise estimators to drive the adaptive algorithm. The method is applied to a one dimensional (1D) steady state convection dominated diffusion problem with homogeneous Dirichlet boundary conditions. This problem exhibits a boundary layer that produces a loss of numerical stability. The new error representation delivers sharper error bounds. When applied to a p-GOA Finite Element Method (FEM), the alternative error representation captures earlier the boundary layer, despite the existing spurious numerical oscillations.

Idioma originalInglés
Páginas (desde-hasta)848-856
Número de páginas9
PublicaciónProcedia Computer Science
Volumen108
DOI
EstadoPublicada - 2017
EventoInternational Conference on Computational Science ICCS 2017 - Zurich, Suiza
Duración: 12 jun. 201714 jun. 2017

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