Local Spectra of Adaptive Domain Decomposition Methods

Alexander Heinlein*, Axel Klawonn, Martin J. Kühn

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)

Abstract

For second order elliptic partial differential equations, such as diffusion or elasticity, with arbitrary and high coefficient jumps, the convergence rate of domain decomposition methods with classical coarse spaces typically deteriorates. One remedy is the use of adaptive coarse spaces, which use eigenfunctions computed from local generalized eigenvalue problems to enrich the standard coarse space; see, e.g., [19, 6, 5, 4, 22, 23, 3, 16, 17, 14, 7, 8, 24, 1, 20, 2, 13, 21, 10, 9, 11]. This typically results in a condition number estimate of the form

Original languageEnglish
Title of host publicationDomain Decomposition Methods in Science and Engineering XXV, DD 2018
EditorsRonald Haynes, Scott MacLachlan, Xiao-Chuan Cai, Laurence Halpern, Hyea Hyun Kim, Axel Klawonn, Olof Widlund
PublisherSpringer
Pages167-175
Number of pages9
ISBN (Print)9783030567491
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event25th International Conference on Domain Decomposition Methods in Science and Engineering, DD 2018 - St. John's, Canada
Duration: 23 Jul 201827 Jul 2018

Publication series

NameLecture Notes in Computational Science and Engineering
Volume138
ISSN (Print)1439-7358
ISSN (Electronic)2197-7100

Conference

Conference25th International Conference on Domain Decomposition Methods in Science and Engineering, DD 2018
Country/TerritoryCanada
CitySt. John's
Period23/07/1827/07/18

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