Goal-Oriented Error Estimation and Adaptivity for Stochastic Collocation FEM

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Bespalov, Alex, Praetorius, Dirk, Round, Thomas, Savinov, Andrey
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866913684224212992
author Bespalov, Alex
Praetorius, Dirk
Round, Thomas
Savinov, Andrey
author_facet Bespalov, Alex
Praetorius, Dirk
Round, Thomas
Savinov, Andrey
contents We propose and analyze a general goal-oriented adaptive strategy for approximating quantities of interest (QoIs) associated with solutions to linear elliptic partial differential equations with random inputs. The QoIs are represented by bounded linear or continuously Gâteaux differentiable nonlinear goal functionals, and the approximations are computed using the sparse grid stochastic collocation finite element method (SC-FEM). The proposed adaptive strategy relies on novel reliable a posteriori estimates of the errors in approximating QoIs. One of the key features of our error estimation approach is the introduction of a correction term into the approximation of QoIs in order to compensate for the lack of (global) Galerkin orthogonality in the SC-FEM setting. Computational results generated using the proposed adaptive algorithm are presented in the paper for representative elliptic problems with affine and nonaffine parametric coefficient dependence and for a range of linear and nonlinear goal functionals.
format Preprint
id arxiv_https___arxiv_org_abs_2406_05028
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Goal-Oriented Error Estimation and Adaptivity for Stochastic Collocation FEM
Bespalov, Alex
Praetorius, Dirk
Round, Thomas
Savinov, Andrey
Numerical Analysis
We propose and analyze a general goal-oriented adaptive strategy for approximating quantities of interest (QoIs) associated with solutions to linear elliptic partial differential equations with random inputs. The QoIs are represented by bounded linear or continuously Gâteaux differentiable nonlinear goal functionals, and the approximations are computed using the sparse grid stochastic collocation finite element method (SC-FEM). The proposed adaptive strategy relies on novel reliable a posteriori estimates of the errors in approximating QoIs. One of the key features of our error estimation approach is the introduction of a correction term into the approximation of QoIs in order to compensate for the lack of (global) Galerkin orthogonality in the SC-FEM setting. Computational results generated using the proposed adaptive algorithm are presented in the paper for representative elliptic problems with affine and nonaffine parametric coefficient dependence and for a range of linear and nonlinear goal functionals.
title Goal-Oriented Error Estimation and Adaptivity for Stochastic Collocation FEM
topic Numerical Analysis
url https://arxiv.org/abs/2406.05028