Parallelization of a stochastic Euler-Lagrange model applied to large scale dense bubbly flows
S. Kamath (Eindhoven University of Technology)
M. V. Masterov (Eindhoven University of Technology)
J. T. Padding (TU Delft - Complex Fluid Processing)
Kay A. Buist (Eindhoven University of Technology)
M. W. Baltussen (Eindhoven University of Technology)
J. A.M. Kuipers (Eindhoven University of Technology)
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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.
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