Efficient simulation of bubble dispersion and resulting interaction
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Experimental and Computational Multiphase Flow
Efficient simulation of bubble dispersion and resulting interaction Xinghao Yang1,2 (), Mark-Patrick Mühlhausena2, Jochen Fröhlich1 1. Institute of Fluid Mechanics, TU Dresden, George-Bähr Str. 3c, 01062 Dresden, Germany 2. CoC Fluid Dynamics, Bosch Rexroth, Partensteiner Str. 23, 97816 Lohr am Main, Germany
Abstract
Keywords
In this work, an efficient model for simulating bubble dispersion and coalescence due to
Euler–Lagrange
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
one-way coupling collision detection bubble coalescence
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)
Article History
model. Bubble–bubble collisions and coalescence are accounted for deterministically. To
Received: 9 April 2020
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.
Revised: 29 June 2020 Accepted: 29 July 2020
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.
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Introduction
Dispersed bubbly flows appear in various engineering systems including chemical, mechanical, and biological applications. The modeling of bubble motion, turbulent dispersion, and interaction with other bubbles plays a significant role in the design process of industrial productions. Much work has been carried out to develop numerical methods for computing unsteady bubbly flows. The point mass approach in an Euler–Lagrange framework is promising for the large-scale industrial applications due to its flexibility and computational efficiency. Compared with the Euler–Euler representation, the Euler–Lagrange approach provides the advantage to track each numerical bubble and model the interaction between bubbles deterministically (Mattson and Mahesh, 2012). According to the review of Liao and Lucas (2010), the interaction between bubbles may be caused by several mechanisms: random motion due to turbulent fluctuations, shear flow because of gradients of the nearby fluid velocity, different rise velocities resulting from different bubble sizes, and the wake entrainment of bubbles moving in line. Compared to the turbulence induced interaction, other [email protected]
Research Article © The Author(s) 2020
mechanisms are normally of minor significance. In order to predict bubble motion due to turbulence, it is ideal to describe all the temporal a
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