Multi-physics simulations of particle tracking in arterial geometries with a scalable moving window algorithm
- Duke university Duhram, NC
- ORNL
- Duke University
- Lawrence Livermore National Laboratory (LLNL)
In arterial systems, cancer cell trajectories determine metastatic cancer locations; similarly, particle trajectories determine drug delivery distribution. Predicting trajectories is challenging, as the dynamics are affected by local interactions with red blood cells, complex hemodynamic flow structure, and downstream factors such as stenoses or blockages. Direct simulation is not possible, as a single simulation of a large arterial domain with explicit red blood cells is currently intractable on even the largest supercomputers. To overcome this limitation, we present a multi-physics adaptive window algorithm, in which individual red blood cells are explicitly modeled in a small region of interest moving through a coupled arterial fluid domain. We describe the coupling between the window and fluid domains, including automatic insertion and deletion of explicit cells and dynamic tracking of cells of interest by the window. We show that this algorithm scales efficiently on heterogeneous architectures and enables us to perform large, highly-resolved particle-tracking simulations that would otherwise be intractable.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1607038
- Resource Relation:
- Conference: IEEE International Conference on Cluster Computing (IEEE Cluster 2019) - Albuquerque, New Mexico, United States of America - 9/23/2019 8:00:00 AM-9/26/2019 8:00:00 AM
- Country of Publication:
- United States
- Language:
- English
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