Parallelization of a stochastic Euler-Lagrange model applied to large scale dense bubbly flows

Journal article (2020)

Authors

S. Kamath Eindhoven University of Technology
M. V. Masterov Eindhoven University of Technology
J.T. Padding Complex Fluid Processing - Mechanical, Maritime and Materials Engineering
K. A. Buist Eindhoven University of Technology
M. W. Baltussen Eindhoven University of Technology
J. A.M. Hans Kuipers Eindhoven University of Technology
Research Group
Complex Fluid Processing (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2020 S. Kamath, M. V. Masterov, J.T. Padding, K. A. Buist, M. W. Baltussen, J. A.M. Kuipers
DOI
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https://doi.org/10.1016/j.jcpx.2020.100058
Parallelization Bubble columns Direct Simulation Monte Carlo Euler-Lagrange modelling
More Info
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Published Date

2020

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Process and Energy

Research Group

Complex Fluid Processing

Abstract

A parallel and scalable stochastic Direct Simulation Monte Carlo (DSMC) method applied to large-scale dense bubbly flows is reported in this paper. The DSMC method is applied to speed up the bubble-bubble collision handling relative to the Discrete Bubble Model proposed by Darmana et al. (2006) [1]. The DSMC algorithm has been modified and extended to account for bubble-bubble interactions arising due to uncorrelated and correlated bubble velocities. The algorithm is fully coupled with an in-house CFD code and parallelized using the MPI framework. The model is verified and validated on multiple cores with different test cases, ranging from impinging particle streams to laboratory-scale bubble columns. The parallel performance is shown using two different large scale systems: with an uniform and a non-uniform distribution of bubbles. The hydrodynamics of a pilot-scale bubble column is analyzed and the effect of the column scale is reported via the comparison of bubble columns at three different scales.