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Title: Parallel multiscale simulations of a brain aneurysm

Abstract

Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linkedmore » together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300 K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in future work.« less

Authors:
 [1];  [2]
  1. Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)
  2. Institute of Complex Systems and Institute for Advanced Simulation, Forschungszentrum Jülich, Jülich 52425 (Germany)
Publication Date:
OSTI Identifier:
22233601
Resource Type:
Journal Article
Journal Name:
Journal of Computational Physics
Additional Journal Information:
Journal Volume: 244; Other Information: Copyright (c) 2012 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0021-9991
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 97 MATHEMATICAL METHODS AND COMPUTING; BLOOD; BLOOD CIRCULATION; BRAIN; DEPOSITION; INTERFACES; MOLECULAR DYNAMICS METHOD; PARTIAL DIFFERENTIAL EQUATIONS; PARTICLES; PATHOLOGY; PATIENTS; RHEOLOGY; SIMULATION; STOCHASTIC PROCESSES; THROMBOSIS

Citation Formats

Grinberg, Leopold, Fedosov, Dmitry A., and Karniadakis, George Em, E-mail: george_karniadakis@brown.edu. Parallel multiscale simulations of a brain aneurysm. United States: N. p., 2013. Web. doi:10.1016/J.JCP.2012.08.023.
Grinberg, Leopold, Fedosov, Dmitry A., & Karniadakis, George Em, E-mail: george_karniadakis@brown.edu. Parallel multiscale simulations of a brain aneurysm. United States. https://doi.org/10.1016/J.JCP.2012.08.023
Grinberg, Leopold, Fedosov, Dmitry A., and Karniadakis, George Em, E-mail: george_karniadakis@brown.edu. 2013. "Parallel multiscale simulations of a brain aneurysm". United States. https://doi.org/10.1016/J.JCP.2012.08.023.
@article{osti_22233601,
title = {Parallel multiscale simulations of a brain aneurysm},
author = {Grinberg, Leopold and Fedosov, Dmitry A. and Karniadakis, George Em, E-mail: george_karniadakis@brown.edu},
abstractNote = {Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300 K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in future work.},
doi = {10.1016/J.JCP.2012.08.023},
url = {https://www.osti.gov/biblio/22233601}, journal = {Journal of Computational Physics},
issn = {0021-9991},
number = ,
volume = 244,
place = {United States},
year = {Mon Jul 01 00:00:00 EDT 2013},
month = {Mon Jul 01 00:00:00 EDT 2013}
}