4.7 Article

Unified computational framework for the efficient solution of n-field coupled problems with monolithic schemes

Journal

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2016.07.016

Keywords

Coupled problems; Monolithic solution schemes; Block preconditioners; Algebraic multigrid; High performance computing

Funding

  1. German Research Foundation (Deutsche Forschungsgemeinschaft - DFG) [TP D4, Sonderforschungsbereich Transregio 40]
  2. Bayerische Kompetenznetzwerk fur Technisch-Wissenschaftliches Hoch- und Hochstleistungsrechnen (KONWIHR)
  3. project Coupled Problems in Computational Modeling of the Respiratory System [pr32ne]

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In this paper, we propose and evaluate the performance of a unified computational framework for preconditioning systems of linear equations resulting from the solution of coupled problems with monolithic schemes. The framework is composed by promising, application-specific preconditioners presented previously in the literature with the common feature that they are able to be implemented for a generic coupled problem, involving an arbitrary number of fields, and to be used to solve a variety of applications. The first selected preconditioner is based on a generic block Gauss-Seidel iteration for uncoupling the fields, and standard algebraic multigrid (AMG) methods for solving the resulting uncoupled problems. The second preconditioner is based on the semi-implicit method for pressure-linked equations (SIMPLE) which is extended here to deal with an arbitrary number of fields, and also results in uncoupled problems that can be solved with standard AMG. Finally, a more sophisticated preconditioner is considered which enforces the coupling at all AMG levels, in contrast to the other two techniques which resolve the coupling only at the finest level. Our purpose is to show that these methods perform satisfactory in quite different scenarios apart from their original applications. To this end, we consider three very different coupled problems: thermo-structure interaction, fluid structure interaction and a complex model of the human lung. Numerical results show that these general purpose methods are efficient and scalable in this range of applications. (C) 2016 Elsevier B.V. All rights reserved.

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