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

S. Kamath, M. V. Masterov, J. T. Padding*, K. A. Buist, M. W. Baltussen, J. A.M. Kuipers

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)
49 Downloads (Pure)


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.

Original languageEnglish
Article number100058
Number of pages29
JournalJournal of Computational Physics: X
Publication statusPublished - 2020


  • Bubble columns
  • Direct Simulation Monte Carlo
  • Euler-Lagrange modelling
  • Parallelization


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