RANS simulation of bubble coalescence and break-up in bubbly two-phase flows

Abstract

In bubbly flows, the bubble size distribution dictates the interfacial area available for the interphase 12 transfer processes and, therefore, understanding the behaviour and the average features of the 13 bubble population is crucial for the prediction of these kinds of flows. In this work, by means of the 14 STAR-CCM+ code, the S population balance model is coupled with an Eulerian-Eulerian two-fluid 15 approach and tested against data on upward bubbly pipe flows. The S model, based on the moments 16 of the bubble size distribution, tracks the evolution of the bubble sizes due to bubble break-up and 17 bubble coalescence. Good accuracy for the average bubble diameter, the velocity and the void 18 fraction radial profiles is achieved with a modified coalescence source. Numerical results show that 19 better predictions are obtained when these flows are considered to be coalescence dominated, but, 20 nevertheless, additional knowledge is required to progress in the development of coalescence and 21 break-up models that include all the possible responsible mechanisms. In this regard, there is a 22 requirement for experimental data that will allow validation of both the predicted bubble diameter 23 distribution and the intensity of the turbulence in the continuous phase which has a significant 24 impact on coalescence and break-up models. An advanced version of the model described, that 25 2 includes a Reynolds stress turbulence formulation and two groups of bubbles to account for the 26 opposite behaviour of spherical bubbles, which accumulate close to the pipe wall, and cap bubbles, 27 that migrate towards the pipe centre, is proposed. The Reynolds stress model is found to better 28 handle the interactions between the turbulence and the interphase forces, and the use of only two 29 bubble groups seems sufficient to describe the whole bubble spectrum and the bubbly flow regime 30 up to the transition to slug flow. 31 32

Numerical Modelling of Dispersed Water in Oil Flows Using Eulerian-Eulerian Approach and Population Balance Model

“…Tomiyama et al [67] proposed a lift model that considers the influence of droplet or bubble deformation on the magnitude and the direction of the lift force. However, considering the observed discrepancies using such an approach, the present study considers a constant lift coefficient of 0.1 which has been suggested by several authors [68][69][70].…”

Assessment of semi-mechanistic bubble departure diameter modelling for the CFD simulation of boiling flows

“…Moments of the bubble diameter distribution, which is assumed to obey to a pre-defined log-normal shape, are calculated and used to define the SMD in the flow. The one-equation version of the model is considered, which is described in more detail in [15], with source terms for breakup and coalescence defined following [25], where they were successfully validated against air-water bubbly flows. Here, a value of 1.24 is used for the critical Weber number Wecr.…”

Multi-Fluid Computational Fluid Dynamic Predictions of Turbulent Bubbly Flows Using an Elliptic-Blending Reynolds Stress Turbulence Closure

“…The liquid phase alters the motion and distribution of bubbles, which mutually impact the continuous phase flow in multiple ways (Liu and Bankoff, 1993a,b;Feng and Bolotnov, 2017). Bubble size distribution continuously evolves, driven by collision and coalescence between bubbles, which can also breakup following interactions with the continuous fluid phase (Liao et al, 2015;Colombo and Fairweather, 2016;Liu and Hibiki, 2018). Most of the time, these processes that impact the large scale fluid behavior are governed by phenomena at much smaller scales (Prince and Blanch, 1990; Legendre and Magnaudet, 1997;Martinez-Bazan et al, 1999;Lucas, 2009, 2010;Bolotnov, 2017, 2018).…”