UM
A parallel non-nested two-level domain decomposition method for simulating blood flows in cerebral artery of stroke patient
Chen,Rongliang1,2; Wu,Bokai1; Cheng,Zaiheng1; Shiu,Wen Shin1; Liu,Jia1; Liu,Liping3; Wang,Yongjun3; Wang,Xinhong4; Cai,Xiao Chuan5
2020-11-01
Source PublicationInternational Journal for Numerical Methods in Biomedical Engineering
ISSN2040-7939
Volume36Issue:11
AbstractNumerical simulation of blood flows in patient-specific arteries can be useful for the understanding of vascular diseases, as well as for surgery planning. In this paper, we simulate blood flows in the full cerebral artery of stroke patients. To accurately resolve the flow in this rather complex geometry with stenosis is challenging and it is also important to obtain the results in a short amount of computing time so that the simulation can be used in pre- and/or post-surgery planning. For this purpose, we introduce a highly scalable, parallel non-nested two-level domain decomposition method for the three-dimensional unsteady incompressible Navier-Stokes equations with an impedance outlet boundary condition. The problem is discretized with a stabilized finite element method on unstructured meshes in space and a fully implicit method in time, and the large nonlinear systems are solved by a preconditioned parallel Newton-Krylov method with a two-level Schwarz method. The key component of the method is a non-nested coarse problem solved using a subset of processor cores and its solution is interpolated to the fine space using radial basis functions. To validate and verify the proposed algorithm and its highly parallel implementation, we consider a case with available clinical data and show that the computed result matches with the measured data. Further numerical experiments indicate that the proposed method works well for realistic geometry and parameters of a full size cerebral artery of an adult stroke patient on a supercomputers with thousands of processor cores.
Keyworddomain decomposition method finite element on unstructured meshes full cerebral artery with stenosis fully implicit method non-nested coarse space parallel processing
DOI10.1002/cnm.3392
URLView the original
Language英语
Fulltext Access
Citation statistics
Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences,Shenzhen,China
2.Shenzhen Key Laboratory for Exascale Engineering and Scientific Computing,Shenzhen,China
3.Department of Neurology,Beijing Tiantan Hospital,Capital Medical University,Beijing,China
4.The Second Affiliated Hospital,Zhejiang University School of Medicine,Hangzhou,China
5.Department of Mathematics,University of Macau,Macao
Recommended Citation
GB/T 7714
Chen,Rongliang,Wu,Bokai,Cheng,Zaiheng,et al. A parallel non-nested two-level domain decomposition method for simulating blood flows in cerebral artery of stroke patient[J]. International Journal for Numerical Methods in Biomedical Engineering,2020,36(11).
APA Chen,Rongliang,Wu,Bokai,Cheng,Zaiheng,Shiu,Wen Shin,Liu,Jia,Liu,Liping,Wang,Yongjun,Wang,Xinhong,&Cai,Xiao Chuan.(2020).A parallel non-nested two-level domain decomposition method for simulating blood flows in cerebral artery of stroke patient.International Journal for Numerical Methods in Biomedical Engineering,36(11).
MLA Chen,Rongliang,et al."A parallel non-nested two-level domain decomposition method for simulating blood flows in cerebral artery of stroke patient".International Journal for Numerical Methods in Biomedical Engineering 36.11(2020).
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Chen,Rongliang]'s Articles
[Wu,Bokai]'s Articles
[Cheng,Zaiheng]'s Articles
Baidu academic
Similar articles in Baidu academic
[Chen,Rongliang]'s Articles
[Wu,Bokai]'s Articles
[Cheng,Zaiheng]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Chen,Rongliang]'s Articles
[Wu,Bokai]'s Articles
[Cheng,Zaiheng]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.