Document Detail


Fast Numerical Solutions of Patient-Specific Blood Flows in 3D Arterial Systems.
MedLine Citation:
PMID:  21076685     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
The study of hemodynamics in arterial models constructed from patient-specific medical images requires the solution of the incompressible flow equations in geometries characterized by complex branching tubular structures. The main challenge with this kind of geometries is that the convergence rate of the pressure Poisson solver is dominated by the graph depth of the computational grid. This paper presents a deflated preconditioned conjugate gradients (DPCG) algorithm for accelerating the pressure Poisson solver. A subspace deflation technique is used to approximate the lowest eigenvalues along tubular domains. This methodology was tested with an idealized cylindrical model and three patient-specific models of cerebral arteries and aneurysms constructed from medical images. For these cases, the number of iterations decreased by up to a factor of 16, while the total CPU time was reduced by up to 4 times when compared with the standard PCG solver.
Authors:
Fernando Mut; Romain Aubry; Rainald Löhner; Juan R Cebral
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Publication Detail:
Type:  JOURNAL ARTICLE    
Journal Detail:
Title:  International journal for numerical methods in biomedical engineering     Volume:  26     ISSN:  2040-7947     ISO Abbreviation:  Int j numer method biomed eng     Publication Date:  2010 Jan 
Date Detail:
Created Date:  2010-11-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101530293     Medline TA:  Int j numer method biomed eng     Country:  -    
Other Details:
Languages:  ENG     Pagination:  73-85     Citation Subset:  -    
Affiliation:
Center for Computational Fluid Dynamics, George Mason University, Fairfax, VA 22030-4444. USA, fmut@gmu.edu.
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MeSH Terms
Descriptor/Qualifier:
Grant Support
ID/Acronym/Agency:
R01 NS059063-01//NINDS NIH HHS

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