Error estimation and adaptivity for stochastic collocation finite elements Part II: multilevel approximation
Abstract
A multilevel adaptive refinement strategy for solving linear elliptic partial differential equations with random data is recalled in this work. The strategy extends the a posteriori error estimation framework introduced by Guignard and Nobile in 2018 (SIAM J. Numer. Anal, 56, 3121--3143) to cover problems with a nonaffine parametric coefficient dependence. A suboptimal, but nonetheless reliable and convenient implementation of the strategy involves approximation of the decoupled PDE problems with a common finite element approximation space. Computational results obtained using such a single-level strategy are presented in part I of this work (Bespalov, Silvester and Xu, arXiv:2109.07320). Results obtained using a potentially more efficient multilevel approximation strategy, where meshes are individually tailored, are discussed herein. The codes used to generate the numerical results are available online.
Cite
@article{arxiv.2202.08902,
title = {Error estimation and adaptivity for stochastic collocation finite elements Part II: multilevel approximation},
author = {Alex Bespalov and David J. Silvester},
journal= {arXiv preprint arXiv:2202.08902},
year = {2022}
}
Comments
16 pages, 7 figures. arXiv admin note: text overlap with arXiv:2109.07320