Stochastic DSMC method for dense bubbly flows: Methodology

A stochastic Direct Simulation Monte Carlo (DSMC) method has been extended for handling bubble-bubble and bubble-wall collisions. Bubbly flows are generally characterized by highly correlated velocities due to presence of the surrounding liquid. The DSMC method has been improved to account for these kind of correlated collisions along with a treatment allowing the method to be used also at relatively high volume fractions. The method is first verified with the deterministic Discrete Particle/Bubble Model (DPM/DBM) using two problem cases: (a) dry granular flow of particles through two impinging nozzles and (b) 3D periodic bubble rise for mono-disperse and poly-disperse systems. The verification parameters are the total number of prevailing collisions within the system, the collision frequencies and the time-averaged liquid velocity profiles (only for the 3D-periodic bubble rise). Subsequently the method is applied to a lab-scale bubble column and validated with the experimental data of Deen et al. (2001). A computational performance comparison with the DBM is reported for the 3D periodic bubble rise case with varying overall gas fractions. The DSMC is approximately two orders of magnitude faster than the deterministic approach for the studied dense bubbly flow cases without adverse effects on the quality of the computational results.Intensified Reaction and Separation System

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

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.Complex Fluid Processin