AuthorsA. Budisa, X. Hu, M. Kuchta, K. Mardal and L. T. Zikatanov
EditorsI. Georgiev, M. Datcheva, K. Georgiev and G. Nikolov
TitleRational approximation preconditioners for multiphysics problems
AfilliationScientific Computing
Project(s)SciML - Scientific Machine Learning, Department of Numerical Analysis and Scientific Computing, DataSim: Data-driven Algorithms for Physical Simulations
StatusPublished
Publication TypeProceedings, refereed
Year of Publication2023
Conference NameNumerical Methods and Applications (NMA 2022)
Volume13858
EditionLecture Notes in Computer Science
Pagination100-113
Date Published05/2023
Publisher Springer
Place PublishedCham
ISBN Number978-3-031-32412-3
KeywordsMultiphysics, preconditioning, Rational approximation
Abstract

We consider a class of mathematical models describing multiphysics phenomena interacting through interfaces. On such interfaces, the traces of the fields lie (approximately) in the range of a weighted sum of two fractional differential operators. We use a rational function approximation to precondition such operators. We first demonstrate the robustness of the approximation for ordinary functions given by weighted sums of fractional exponents. Additionally, we present more realistic examples utilizing the proposed preconditioning techniques in interface coupling between Darcy and Stokes equations.

URLhttps://doi.org/10.1007/978-3-031-32412-3_9
DOI10.1007/978-3-031-32412-3_9
Citation Key42935