Monolithic Multigrid for a Reduced-Quadrature Discretization of Poroelasticity
Abstract
Advanced finite-element discretizations and preconditioners for models of poroelasticity have attracted significant attention in recent years. The equations of poroelasticity offer significant challenges in both areas, due to the potentially strong coupling between unknowns in the system, saddle-point structure, and the need to account for wide ranges of parameter values, including limiting behavior such as incompressible elasticity. This paper was motivated by an attempt to develop monolithic multigrid preconditioners for the discretization developed in [C. Rodrigo et al., Comput. Methods App. Mech. Engrg, 341 (2018), pp. 467--484]; we show here why this is a difficult task and, as a result, we modify the discretization in [Rodrigo et al.] through the use of a reduced-quadrature approximation, yielding a more “solver-friendly” discretization. Local Fourier analysis is used to optimize parameters in the resulting monolithic multigrid method, allowing a fair comparison between the performance and costs of methods based on Vanka and Braess--Sarazin relaxation. Further, numerical results are presented to validate the local Fourier analysis predictions and demonstrate efficiency of the algorithms. Finally, a comparison to existing block-factorization preconditioners is also given.
- Authors:
-
- Tufts Univ., Medford, MA (United States)
- Memorial Univ. of Newfoundland, St. John's, NL (Canada)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); National Science Foundation (NSF)
- OSTI Identifier:
- 1883184
- Report Number(s):
- SAND2022-5421J
Journal ID: ISSN 1064-8275; 705525
- Grant/Contract Number:
- NA0003525; DMS-1620063
- Resource Type:
- Accepted Manuscript
- Journal Name:
- SIAM Journal on Scientific Computing
- Additional Journal Information:
- Journal Volume: 45; Journal Issue: 3; Journal ID: ISSN 1064-8275
- Publisher:
- Society for Industrial and Applied Mathematics (SIAM)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; Biot poroelasticity; reduced quadrature; finite elements; monolithic multigrid; local Fourier analysis
Citation Formats
Adler, James H., He, Yunhui, Hu, Xiaozhe, MacLachlan, Scott, and Ohm, Peter. Monolithic Multigrid for a Reduced-Quadrature Discretization of Poroelasticity. United States: N. p., 2022.
Web. doi:10.1137/21m1429072.
Adler, James H., He, Yunhui, Hu, Xiaozhe, MacLachlan, Scott, & Ohm, Peter. Monolithic Multigrid for a Reduced-Quadrature Discretization of Poroelasticity. United States. https://doi.org/10.1137/21m1429072
Adler, James H., He, Yunhui, Hu, Xiaozhe, MacLachlan, Scott, and Ohm, Peter. Fri .
"Monolithic Multigrid for a Reduced-Quadrature Discretization of Poroelasticity". United States. https://doi.org/10.1137/21m1429072. https://www.osti.gov/servlets/purl/1883184.
@article{osti_1883184,
title = {Monolithic Multigrid for a Reduced-Quadrature Discretization of Poroelasticity},
author = {Adler, James H. and He, Yunhui and Hu, Xiaozhe and MacLachlan, Scott and Ohm, Peter},
abstractNote = {Advanced finite-element discretizations and preconditioners for models of poroelasticity have attracted significant attention in recent years. The equations of poroelasticity offer significant challenges in both areas, due to the potentially strong coupling between unknowns in the system, saddle-point structure, and the need to account for wide ranges of parameter values, including limiting behavior such as incompressible elasticity. This paper was motivated by an attempt to develop monolithic multigrid preconditioners for the discretization developed in [C. Rodrigo et al., Comput. Methods App. Mech. Engrg, 341 (2018), pp. 467--484]; we show here why this is a difficult task and, as a result, we modify the discretization in [Rodrigo et al.] through the use of a reduced-quadrature approximation, yielding a more “solver-friendly” discretization. Local Fourier analysis is used to optimize parameters in the resulting monolithic multigrid method, allowing a fair comparison between the performance and costs of methods based on Vanka and Braess--Sarazin relaxation. Further, numerical results are presented to validate the local Fourier analysis predictions and demonstrate efficiency of the algorithms. Finally, a comparison to existing block-factorization preconditioners is also given.},
doi = {10.1137/21m1429072},
journal = {SIAM Journal on Scientific Computing},
number = 3,
volume = 45,
place = {United States},
year = {Fri Jun 24 00:00:00 EDT 2022},
month = {Fri Jun 24 00:00:00 EDT 2022}
}
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