NEW OPTIMIZED ROBIN−ROBIN DOMAIN DECOMPOSITION METHODS USING KRYLOV SOLVERS FOR THE STOKES−DARCY SYSTEM
Document Type
Article
Publication Date
1-1-2022
Abstract
In this paper, we are interested in the design of optimized Schwarz domain decomposition algorithms to accelerate the Krylov type solution for the Stokes−Darcy system. We use particular solutions of this system on a circular geometry to analyze the iteration operator mode by mode. We introduce a new optimization strategy of the so-called Robin parameters based on a specific linear relation between these parameters, using the min-max and the expectation minimization approaches. Moreover, we use a Krylov solver to deal with the iteration operator and accelerate this new optimized domain decomposition algorithm. Several numerical experiments are provided to validate the effectiveness of this new method.
Identifier
85140078467 (Scopus)
Publication Title
SIAM Journal on Scientific Computing
External Full Text Location
https://doi.org/10.1137/21M1417223
e-ISSN
10957197
ISSN
10648275
Issue
4
Volume
44
Grant
DMS-1720014
Fund Ref
National Science Foundation
Recommended Citation
Liu, Yingzhi; Boubendir, Yassine; He, Xiaoming; and He, Yinnian, "NEW OPTIMIZED ROBIN−ROBIN DOMAIN DECOMPOSITION METHODS USING KRYLOV SOLVERS FOR THE STOKES−DARCY SYSTEM" (2022). Faculty Publications. 3423.
https://digitalcommons.njit.edu/fac_pubs/3423