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Viscous flow simulation in a stenosis model using discrete particle dynamics: a comparison between DPD and CFD

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Biomechanics and Modeling in Mechanobiology Aims and scope Submit manuscript

Abstract

Flow and stresses induced by blood flow acting on the blood cellular constituents can be represented to a certain extent by a continuum mechanics approach down to the order of the μm level. However, the molecular effects of, e.g., adhesion/aggregation bonds of blood clotting can be on the order of nm. The coupling of the disparate length and timescales between such molecular levels and macroscopic transport represents a major computational challenge. To address this challenge, a multiscale numerical approach based on discrete particle dynamics (DPD) methodology derived from molecular dynamics (MD) principles is proposed. The feasibility of the approach was firstly tested for its ability to simulate viscous flow conditions. Simulations were conducted in low Reynolds numbers flows (Re = 25–33) through constricted tubes representing blood vessels with various degrees of stenosis. Multiple discrete particles interacting with each other were simulated, with 1.24–1.36 million particles representing the flow domain and 0.4 million particles representing the vessel wall. The computation was carried out on the massive parallel supercomputer NY BlueGene/L employing NAMD-a parallel MD package for high performance computing (HPC). Typical recirculation zones were formed distal to the stenoses. The velocity profiles and recirculation zones were in excellent agreement with computational fluid dynamics (CFD) 3D Navier–Stokes viscous fluid flow simulations and with classic numerical and experimental results by YC Fung in constricted tubes. This feasibility analysis demonstrates the potential of a methodology that widely departs from a continuum approach to simulate multiscale phenomena such as flow induced blood clotting.

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Abbreviations

DPD:

Discrete particle dynamics

NAMD:

Nanoscale molecular dynamics

L-J:

Lennard-Jones

CFD:

Computational fluid dynamics

Re:

Reynolds number

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Authors and Affiliations

  1. Computational Science Center, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA

    Rui Feng & James W. Davenport

  2. School of Computer Science and Engineering, Beihang University, 100083, Beijing, China

    Rui Feng

  3. Department of Biomedical Engineering, Stony Brook University, HSC T18-030, Stony Brook, NY, 11790, USA

    Michalis Xenos, Gaurav Girdhar & Danny Bluestein

  4. Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, NY, 11973-5000, USA

    Wei Kang & James W. Davenport

  5. Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, 11790, USA

    Yuefan Deng

Authors
  1. Rui Feng
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  2. Michalis Xenos
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  3. Gaurav Girdhar
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  4. Wei Kang
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  5. James W. Davenport
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  6. Yuefan Deng
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  7. Danny Bluestein
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Correspondence to Danny Bluestein.

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Feng, R., Xenos, M., Girdhar, G. et al. Viscous flow simulation in a stenosis model using discrete particle dynamics: a comparison between DPD and CFD. Biomech Model Mechanobiol 11, 119–129 (2012). https://doi.org/10.1007/s10237-011-0297-z

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  • DOI: https://doi.org/10.1007/s10237-011-0297-z

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