Simulation of the human intracranial arterial tree
High-resolution unsteady three-dimensional flow simulations in large intracranial arterial networks of a healthy subject and a patient with hydrocephalus have been performed. The large size of the computational domains requires the use of thousands of computer processors and solution of the flow equ...
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Published in | Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences Vol. 367; no. 1896; pp. 2371 - 2386 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
London
The Royal Society
13.06.2009
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Subjects | |
Online Access | Get full text |
ISSN | 1364-503X 1471-2962 |
DOI | 10.1098/rsta.2008.0307 |
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Abstract | High-resolution unsteady three-dimensional flow simulations in large intracranial arterial networks of a healthy subject and a patient with hydrocephalus have been performed. The large size of the computational domains requires the use of thousands of computer processors and solution of the flow equations with approximately one billion degrees of freedom. We have developed and implemented a two-level domain decomposition method, and a new type of outflow boundary condition to control flow rates at tens of terminal vessels of the arterial network. In this paper, we demonstrate the flow patterns in the normal and abnormal intracranial arterial networks using patient-specific data. |
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AbstractList | High-resolution unsteady three-dimensional flow simulations in large intracranial arterial networks of a healthy subject and
a patient with hydrocephalus have been performed. The large size of the computational domains requires the use of thousands
of computer processors and solution of the flow equations with approximately one billion degrees of freedom. We have developed
and implemented a two-level domain decomposition method, and a new type of outflow boundary condition to control flow rates
at tens of terminal vessels of the arterial network. In this paper, we demonstrate the flow patterns in the normal and abnormal
intracranial arterial networks using patient-specific data. High-resolution unsteady three-dimensional flow simulations in large intracranial arterial networks of a healthy subject and a patient with hydrocephalus have been performed. The large size of the computational domains requires the use of thousands of computer processors and solution of the flow equations with approximately one billion degrees of freedom. We have developed and implemented a two-level domain decomposition method, and a new type of outflow boundary condition to control flow rates at tens of terminal vessels of the arterial network. In this paper, we demonstrate the flow patterns in the normal and abnormal intracranial arterial networks using patient-specific data. High-resolution unsteady three-dimensional flow simulations in large intracranial arterial networks of a healthy subject and a patient with hydrocephalus have been performed. The large size of the computational domains requires the use of thousands of computer processors and solution of the flow equations with approximately one billion degrees of freedom. We have developed and implemented a two-level domain decomposition method, and a new type of outflow boundary condition to control flow rates at tens of terminal vessels of the arterial network. In this paper, we demonstrate the flow patterns in the normal and abnormal intracranial arterial networks using patient-specific data.High-resolution unsteady three-dimensional flow simulations in large intracranial arterial networks of a healthy subject and a patient with hydrocephalus have been performed. The large size of the computational domains requires the use of thousands of computer processors and solution of the flow equations with approximately one billion degrees of freedom. We have developed and implemented a two-level domain decomposition method, and a new type of outflow boundary condition to control flow rates at tens of terminal vessels of the arterial network. In this paper, we demonstrate the flow patterns in the normal and abnormal intracranial arterial networks using patient-specific data. |
Author | Anor, Tomer Cheever, Elizabeth Grinberg, Leopold Karniadakis, George Em Madsen, Joseph R. |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/19414460$$D View this record in MEDLINE/PubMed |
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Snippet | High-resolution unsteady three-dimensional flow simulations in large intracranial arterial networks of a healthy subject and
a patient with hydrocephalus have... High-resolution unsteady three-dimensional flow simulations in large intracranial arterial networks of a healthy subject and a patient with hydrocephalus have... |
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SubjectTerms | Arteries Arteries - anatomy & histology Arteries - physiology Blood flow Blood vessels Boundary conditions Cerebrovascular Circulation Circle Of Willis Computational Biology Computational Fluid Dynamics Flow velocity Humans Hydrocephalus Hydrodynamics Inlets Modeling Parallel Computing Simulations Three dimensional modeling |
Title | Simulation of the human intracranial arterial tree |
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