Enhancing Adaptive Physics Refinement Simulations Through the Addition of Realistic Red Blood Cell Counts

Sayan Roychowdhury, Samreen T. Mahmud, Aristotle Martin, Peter Balogh, Daniel F. Puleri, John Gounley, Erik W. Draeger, Amanda Randles

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Simulations of cancer cell transport require accurately modeling mm-scale and longer trajectories through a circulatory system containing trillions of deformable red blood cells, whose intercellular interactions require submicron fidelity. Using a hybrid CPU-GPU approach, we extend the advanced physics refinement (APR) method to couple a finely-resolved region of explicitly-modeled red blood cells to a coarsely-resolved bulk fluid domain. We further develop algorithms that: capture the dynamics at the interface of differing viscosities, maintain hematocrit within the cell-filled volume, and move the finely-resolved region and encapsulated cells while tracking an individual cancer cell. Comparison to a fully-resolved fluid-structure interaction model is presented for verification. Finally, we use the advanced APR method to simulate cancer cell transport over a mm-scale distance while maintaining a local region of RBCs, using a fraction of the computational power required to run a fully-resolved model.

Original languageEnglish
Title of host publicationProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9798400701092
DOIs
StatePublished - Nov 12 2023
Event2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023 - Denver, United States
Duration: Nov 12 2023Nov 17 2023

Publication series

NameProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023

Conference

Conference2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023
Country/TerritoryUnited States
CityDenver
Period11/12/2311/17/23

Funding

This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Research reported in this publication was supported by National Institutes of Health under Award Number U01-CA253511 and NSF Career Award 1943036. Computing support for this work came from the DOE INCITE program and the Lawrence Livermore National Laboratory (LLNL) Institutional Computing Grand Challenge program.

Keywords

  • cancer cells
  • computational fluid dynamics
  • heterogeneous architecture
  • multiphysics
  • multiscale modeling
  • red blood cells

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