Direct numerical simulation of transitional pulsatile stenotic flow using Lattice Boltzmann Method
- Published
- Accepted
- Subject Areas
- Computational Biology, Neurology, Computational Science
- Keywords
- Stenosis, transitional flow, lattice Boltzmann Method, Kolmogorov microscales
- Copyright
- © 2016 Jain
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2016. Direct numerical simulation of transitional pulsatile stenotic flow using Lattice Boltzmann Method. PeerJ PrePrints 4:e1548v3 https://doi.org/10.7287/peerj.preprints.1548v3
Abstract
The present contribution reports direct numerical simulations of pulsatile flow through a 75% eccentric stenosis using the Lattice Boltzmann Method (LBM). The stenosis was previously studied by Varghese, Frankel, and Fischer in a benchmark computation, and the goal of this work is to evaluate the LBM and the solver Musubi for transitional flows in anatomically realistic geometries. A part of the study compares the LBM simulation results against the benchmark and evaluates the efficacy of most basic LBM scheme for simulation of such flows. The novelty lies in the computation of Kolmogorov micro-scales by performing simulations that consist of up to ∼ 700 million cells. Recommendations on the choice of spatial and temporal resolutions for simulation of transitional flows in complex geometries naturally arise from the results. The LBM results show an excellent agreement with the previously published results thereby validating the method and the solver Musubi for the simulation of transitional flows. The study suggests that with a prudent calibration of the parameters, the LB method, due to its simplicity and compute efficiency has advantages for the simulation of such flows.
Author Comment
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