Multiscale modeling and simulation of brain blood flow

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and...

Full description

Saved in:
Bibliographic Details
Published in:Physics of fluids (1994) 2016-02, Vol.28 (2), p.021304-021304
Main Authors: Perdikaris, Paris, Grinberg, Leopold, Karniadakis, George Em
Format: Article
Language:English
Subjects:
ALGORITHMS
Award and Invited Papers
Blood flow
BRAIN
CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
Computer simulation
DISEASES
Fluid dynamics
Mathematical models
Multiscale analysis
PATIENTS
Physics
Scale models
SIMULATION
Solvers
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.
ISSN:1070-6631
1089-7666
DOI:10.1063/1.4941315