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Parameter robust preconditioning by congruence for multiple-network poroelasticity

Abstract:
The mechanical behavior of a poroelastic medium permeated by multiple interacting fluid networks can be described by a system of time-dependent partial differential equations known as the multiple-network poroelasticity (MPET) equations or multiporosity/multipermeability systems. These equations generalize Biot's equations, which describe the mechanics of the one network case. The efficient numerical solution of the MPET equations is challenging, in part due to the complexity of the system and in part due to the presence of interacting parameter regimes. In this paper, we present a new strategy for efficiently and robustly solving the MPET equations numerically. In particular, we discuss an approach to formulating finite element methods and associated preconditioners for the MPET equations based on simultaneous diagonalization of the element matrices. We demonstrate the technique for the multicompartment Darcy equations, with large exchange variability, and the MPET equations for a nearly incompressible medium with large exchange variability. The approach is based on designing transformations of variables that simultaneously diagonalize (by congruence) the equations' key operators and subsequently constructing parameter-robust block diagonal preconditioners for the transformed system. The proposed approach is supported by theoretical considerations as well as by numerical results.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1137/20m1326751

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author


Publisher:
Society for Industrial and Applied Mathematics
Journal:
SIAM Journal on Scientific Computing More from this journal
Volume:
43
Issue:
4
Pages:
B984-B1007
Publication date:
2021-08-04
Acceptance date:
2021-04-14
DOI:
EISSN:
1095-7197
ISSN:
1064-8275


Language:
English
Keywords:
Pubs id:
1191734
Local pid:
pubs:1191734
Deposit date:
2021-08-20
ARK identifier:

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