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

doi:10.1016/j.jcpx.2020.100058

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.

Highlights

Flows are one of the more complex multi-scale multiphase flow problems which are encountered across many fields of physics and engineering
A parallel and scalable stochastic Direct Simulation Monte Carlo (DSMC) method applied to large-scale dense bubbly flows is reported in this paper
At the center of the swarm the liquid fraction is low and bubbles experience less drag. They have higher velocities compared to the bubbles at the edges. This dynamics is preserved in time and causes the entrained liquid to behave as a submerged jet which decays along the height due to the viscous forces and presence of the top wall

Summary

Introduction

Flows are one of the more complex multi-scale multiphase flow problems which are encountered across many fields of physics and engineering. Small scale physical changes in the properties of the different phases can have a huge impact on the large scale physics of systems Such flows are studied at the DNS (Direct Numerical Simulations) level for representative systems to derive closures for interactions forces used in simulations executed at larger length and time scales. Methods such as the Discrete Bubble Model (DBM) and the stochastic Euler-Lagrange (E-L) models (among which DSMC methods) are examples of classes of methods where these closures are applied.

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Conclusion