A parallel immersed boundary method for blood-like suspension flow simulations

F. Pacull, M. Garbey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a numerically efficient implementation of the Immersed Boundary Method (IBM), originally developed by [7] to simulate fluid/elastic-structure interactions. The fluid is assumed to be incompressib0le with uniform density, viscosity, while the immersed boundaries have fixed topologies with a linear elastic behavior. Based on the finite-difference method, a major numerical advantage of the IBM is the high level of uniformity of mesh and stencil, avoiding the critical interpolation processes of the cut-cell/direct methods. The difficulty of accurately simulating interaction phenomena involving moving complex geometries can be overcome by implementing large and parallel IBMcomputations on fine grids, as described in [1]. While this paper is restricted to a two-dimensional low-Reynolds-number flow, most of the concepts introduced here should apply to three-dimensional bio-flows.We describe here the decomposition techniques applied to the IBM, in order to decrease the computational time, in the context of the parallel Matlab toolbox of [3]. Finally, we apply the method to a blood-like suspension flow test-case.

Original languageEnglish (US)
Title of host publicationParallel Computational Fluid Dynamics 2008 - Parallel Numerical Methods, Software Development and Applications
Pages153-160
Number of pages8
DOIs
StatePublished - 2011
Event20th International Series of Meetings on Parallel Computational Fluid Dynamics, CFD 2008 - Lyon, France
Duration: May 19 2008May 22 2008

Publication series

NameLecture Notes in Computational Science and Engineering
Volume74 LNCSE
ISSN (Print)1439-7358

Other

Other20th International Series of Meetings on Parallel Computational Fluid Dynamics, CFD 2008
CountryFrance
CityLyon
Period5/19/085/22/08

ASJC Scopus subject areas

  • Modeling and Simulation
  • Engineering(all)
  • Discrete Mathematics and Combinatorics
  • Control and Optimization
  • Computational Mathematics

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