Scalability study of an implicit solver for coupled fluid-structure interaction problems on unstructured meshes in 3D. (March 2018)

• Record Type: Journal Article
• Authors: Kong, Fande; Cai, Xiao-Chuan
• Is Part Of: International journal of high performance computing applications. Volume 32:Number 2(2018)
• Page Start: 207
• Page End: 219
• Publication Date: 2018-03
• Subjects: Unstructured mesh -- finite element -- multilevel Schwarz preconditioner -- Newton–Krylov–Schwarz -- scalable parallel algorithm -- fluid-structure interaction; High performance computing -- Periodicals; Supercomputers -- Periodicals; 004.1105
• DOI: 10.1177/1094342016646437
• Languages: English
• ISSNs: 1094-3420

Abstract

Fluid-structure interaction (FSI) problems are computationally very challenging. In this paper we consider the monolithic approach for solving the fully coupled FSI problem. Most existing techniques, such as multigrid methods, do not work well for the coupled system since the system consists of elliptic, parabolic and hyperbolic components all together. Other approaches based on direct solvers do not scale to large numbers of processors. In this paper, we introduce a multilevel unstructured mesh Schwarz preconditioned Newton–Krylov method for the implicitly discretized, fully coupled system of partial differential equations consisting of incompressible Navier–Stokes equations for the fluid flows and the linear elasticity equation for the structure. Several meshes are required to make the solution algorithm scalable. This includes a fine mesh to guarantee the solution accuracy, and a few isogeometric coarse meshes to speed up the convergence. Special attention is paid when constructing and partitioning the preconditioning meshes so that the communication cost is minimized when the number of processor cores is large. We show numerically that the proposed algorithm is highly scalable in terms of the number of iterations and the total compute time on a supercomputer with more than 10, 000 processor cores for monolithically coupled three-dimensional FSI problems with hundreds of millions of unknowns.