Abstract
In this work, an efficient model for simulating bubble dispersion and coalescence due to turbulence is developed in the Euler-Lagrange framework. The primary liquid phase is solved on the Euler grid with the RANS turbulence model. Bubble motion is computed with the force balance equations. One-way coupling between two phases is assumed and the framework is designed for the computation of disperse bubbly flows at low Eötvös number. The turbulent dispersion of the dispersed phase is reconstructed with the continuous random walk (CRW) model. Bubble-bubble collisions and coalescence are accounted for deterministically. To accelerate the time-consuming search for potential collision partners in dense bubbly flows, the sweep and prune algorithm is employed, which can be utilized in arbitrary mesh types and sizes. Validation against experiments of turbulent pipe flows demonstrates that the one-way coupled EL-CRW dispersion model can well reproduce the bubble distribution in a typical dense bubbly pipe flow. Good agreement of the bubble size distribution at the pipe outlet between the simulation and the experiment is obtained.
Highlights
Dispersed bubbly flows appear in various engineering systems including chemical, mechanical, and biological applications
Compared with discontinuous random walk (DRW) models, progress in predicting turbulent dispersion especially in non-homogeneous turbulence can be obtained with the continuous random walk (CRW) models, which produce velocity fluctuations that are continuous in time (Sommerfeld, 2001)
The bubble size was randomly chosen from the experimental probability distribution function (PDF)
Summary
Dispersed bubbly flows appear in various engineering systems including chemical, mechanical, and biological applications. The Large Eddy Simulation (LES) approach is conceptually similar to DNS but requires reduced computational effort by modeling instead of resolving the smallest length scales. Both methods still need sufficiently fine grids and the computational resources increase rapidly with Reynolds number. One focus of this paper is to apply a RANS dispersion model for modeling turbulenceinduced interaction between the elements of the Lagrange phase, a prerequisite to address turbulence-induced bubble collisions. Owing to the small time step size used in the dispersion models to capture the necessary eddy properties, the computational burden is increased further To overcome this problem, several algorithms have been proposed to accelerate the collision modeling (Shams et al, 2011; Breuer and Alletto, 2012).
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