| Authors | A. Budisa, X. Hu, M. Kuchta, K. Mardal and L. T. Zikatanov |
| Editors | I. Georgiev, M. Datcheva, K. Georgiev and G. Nikolov |
| Title | Rational approximation preconditioners for multiphysics problems |
| Afilliation | Scientific Computing |
| Project(s) | SciML - Scientific Machine Learning, Department of Numerical Analysis and Scientific Computing, DataSim: Data-driven Algorithms for Physical Simulations |
| Status | Published |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2023 |
| Conference Name | Numerical Methods and Applications (NMA 2022) |
| Volume | 13858 |
| Edition | Lecture Notes in Computer Science |
| Pagination | 100-113 |
| Date Published | 05/2023 |
| Publisher | Springer |
| Place Published | Cham |
| ISBN Number | 978-3-031-32412-3 |
| Keywords | Multiphysics, 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. |
| URL | https://doi.org/10.1007/978-3-031-32412-3_9 |
| DOI | 10.1007/978-3-031-32412-3_9 |
| Citation Key | 42935 |