Volume 4, Issue 5
A Scalable Domain Decomposition Method for Ultra-parallel Arterial Flow Simulations

Leopold Grinberg & George Em Karniadakis

DOI:

Commun. Comput. Phys., 4 (2008), pp. 1151-1169.

Published online: 2008-11

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  • Abstract

Ultra-parallel flow simulations on hundreds of thousands of processors require new multi-level domain decomposition methods. Here we present such a new two-level method that has features both of discontinuous and continuous Galerkin formulations. Specifically, at the coarse level the domain is subdivided into several big patches and within each patch a spectral element discretization (fine level) is employed. New interface conditions for the Navier-Stokes equations are developed to connect the patches, relaxing the C0 continuity and minimizing data transfer at the patch interface. We perform several 3D flow simulations of a benchmark problem and of arterial flows to evaluate the performance of the new method and investigate its accuracy. 

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@Article{CiCP-4-1151, author = {Leopold Grinberg and George Em Karniadakis}, title = {A Scalable Domain Decomposition Method for Ultra-parallel Arterial Flow Simulations}, journal = {Communications in Computational Physics}, year = {2008}, volume = {4}, number = {5}, pages = {1151--1169}, abstract = {

Ultra-parallel flow simulations on hundreds of thousands of processors require new multi-level domain decomposition methods. Here we present such a new two-level method that has features both of discontinuous and continuous Galerkin formulations. Specifically, at the coarse level the domain is subdivided into several big patches and within each patch a spectral element discretization (fine level) is employed. New interface conditions for the Navier-Stokes equations are developed to connect the patches, relaxing the C0 continuity and minimizing data transfer at the patch interface. We perform several 3D flow simulations of a benchmark problem and of arterial flows to evaluate the performance of the new method and investigate its accuracy. 

}, issn = {1991-7120}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/cicp/7832.html} }
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