TY - JOUR
T1 - A novel multiblock immersed boundary method for large eddy simulation of complex arterial hemodynamics
AU - Anupindi, Kameswararao
AU - Delorme, Yann
AU - Shetty, Dinesh A.
AU - Frankel, Steven H.
N1 - Funding Information:
We would like to thank Dr. Shuo Yang and Dr. Jarin Kratzberg of MED Institute, West Lafayette, IN, for reconstructing and providing us with the TAA geometry from patient-specific magnetic resonance imaging scan. This particular geometry has motivated us to develop the present novel solver and we acknowledge the same. K.A. would like to thank Dr. Robert Falgout for his suggestions and help in answering his questions related to setting up and using the hypre [13,2,9,10] software library and Prof. Charles Asbury, for his help in answering questions related to reconstructing the AAA geometry from the models used in their experiments [1] . The authors would like to acknowledge the financial support received from the collaboration between Technology Assistance Program (TAP) at Purdue University and MED Institute , West Lafayette, IN. The partial financial support received from National Institute of Health (NIH) Grant HL098353 , in carrying out this work is also acknowledged. The computational resources provided through TAP on Ohio Super Computer cluster is gratefully acknowledged.
PY - 2013/12/1
Y1 - 2013/12/1
N2 - Computational fluid dynamics (CFD) simulations are becoming a reliable tool to understand hemodynamics, disease progression in pathological blood vessels and to predict medical device performance. Immersed boundary method (IBM) emerged as an attractive methodology because of its ability to efficiently handle complex moving and rotating geometries on structured grids. However, its application to study blood flow in complex, branching, patient-specific anatomies is scarce. This is because of the dominance of grid nodes in the exterior of the fluid domain over the useful grid nodes in the interior, rendering an inevitable memory and computational overhead. In order to alleviate this problem, we propose a novel multiblock based IBM that preserves the simplicity and effectiveness of the IBM on structured Cartesian meshes and enables handling of complex, anatomical geometries at a reduced memory overhead by minimizing the grid nodes in the exterior of the fluid domain. As pathological and medical device hemodynamics often involve complex, unsteady transitional or turbulent flow fields, a scale resolving turbulence model such as large eddy simulation (LES) is used in the present work. The proposed solver (here after referred as WenoHemo), is developed by enhancing an existing in-house high-order incompressible flow solver that was previously validated for its numerics and several LES models by Shetty et al. (2010) [33]. In the present work, W e n o H e m o is systematically validated for additional numerics introduced, such as IBM and the multiblock approach, by simulating laminar flow over a sphere and laminar flow over a backward facing step respectively. Then, we validate the entire solver methodology by simulating laminar and transitional flow in abdominal aortic aneurysm (AAA). Finally, we perform blood flow simulations in the challenging clinically relevant thoracic aortic aneurysm (TAA), to gain insights into the type of fluid flow patterns that exist in pathological blood vessels. Results obtained from the TAA simulations reveal complex vortical and unsteady flow fields that need to be considered in designing and implanting medical devices such as stent grafts.
AB - Computational fluid dynamics (CFD) simulations are becoming a reliable tool to understand hemodynamics, disease progression in pathological blood vessels and to predict medical device performance. Immersed boundary method (IBM) emerged as an attractive methodology because of its ability to efficiently handle complex moving and rotating geometries on structured grids. However, its application to study blood flow in complex, branching, patient-specific anatomies is scarce. This is because of the dominance of grid nodes in the exterior of the fluid domain over the useful grid nodes in the interior, rendering an inevitable memory and computational overhead. In order to alleviate this problem, we propose a novel multiblock based IBM that preserves the simplicity and effectiveness of the IBM on structured Cartesian meshes and enables handling of complex, anatomical geometries at a reduced memory overhead by minimizing the grid nodes in the exterior of the fluid domain. As pathological and medical device hemodynamics often involve complex, unsteady transitional or turbulent flow fields, a scale resolving turbulence model such as large eddy simulation (LES) is used in the present work. The proposed solver (here after referred as WenoHemo), is developed by enhancing an existing in-house high-order incompressible flow solver that was previously validated for its numerics and several LES models by Shetty et al. (2010) [33]. In the present work, W e n o H e m o is systematically validated for additional numerics introduced, such as IBM and the multiblock approach, by simulating laminar flow over a sphere and laminar flow over a backward facing step respectively. Then, we validate the entire solver methodology by simulating laminar and transitional flow in abdominal aortic aneurysm (AAA). Finally, we perform blood flow simulations in the challenging clinically relevant thoracic aortic aneurysm (TAA), to gain insights into the type of fluid flow patterns that exist in pathological blood vessels. Results obtained from the TAA simulations reveal complex vortical and unsteady flow fields that need to be considered in designing and implanting medical devices such as stent grafts.
KW - Biomechanical flows
KW - High-order finite difference
KW - Immersed boundary method
KW - Incompressible
KW - Large eddy simulation
KW - Multiblock
KW - WENO
UR - http://www.scopus.com/inward/record.url?scp=84883514687&partnerID=8YFLogxK
U2 - 10.1016/j.jcp.2013.07.033
DO - 10.1016/j.jcp.2013.07.033
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AN - SCOPUS:84883514687
SN - 0021-9991
VL - 254
SP - 200
EP - 218
JO - Journal of Computational Physics
JF - Journal of Computational Physics
ER -