Parallel Scalable Domain Decomposition Methods for Blood Flow Simulation
Thursday, August 13, 2015
10:00 am - 11:00 am
Gross Hall 330
Yuqi Wua, Dept of Applied Mathematics, University of Washington
Abstract In this work, we develop a class of parallel domain decomposition method for simulating blood flow in three-dimensional compliant arteries. We model the fluid-structure interaction problem by using a monolithically coupled system of linear elasticity equation and incompressible Navier-Stokes equations in an arbitrary Lagrangian-Eulerian framework. The monolithic fluid-structure system is discretized with a fully-implicit finite element method on unstructured moving meshes, and solved by a Newton-Krylov algorithm preconditioned with restricted additive Schwarz methods. The investigations focuses on the performance of the one-level and two-level overlapping Schwarz preconditioner for Newton-Krylov methods as well as the efficiency and parallel scalability of the algorithm for solving the complicated coupled system. Simulations based on the patient-specific pulmonary artery geometries are performed on a supercomputer. Our algorithm is shown to be scalable with thousands processors and for problems with millions of unknowns. Yuqi Wu is an Acting Assistant Professor in Applied Mathematics at the University of Washington. He received his Ph.D in Applied Mathematics from the University of Colorado. Dr. Wu¿s research focuses on numerical algorithms for partial di¿erential equations, computational fluid dynamics, parallel computing and reduced-order models.