Bubble breakup and coalescence models for bubbly flow simulation using interfacial area transport equation

Liu, Hang; Hibiki, Takashi

doi:10.1016/j.ijheatmasstransfer.2018.05.054

Cited by 12 publications

(4 citation statements)

References 52 publications

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“…Water interfacial transport data derived from standard atmospheric pressure (0.1 MPa) is used for benchmarking existing sink and source terms, except for the boiling refrigerants and SF6-ethanol, where they can be used for the simulation of high pressure [ 64 , 65 ]. It is probably due to bubbles in water are common and used everywhere.…”

Section: Evaluation Of Frequency Models and Constitutive Models For Bubble Coalescence And Breakupmentioning

confidence: 99%

Interfacial Area Transport Equation for Bubble Coalescence and Breakup: Developments and Comparisons

Chen

Wei

Ding

et al. 2021

Entropy

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Bubble coalescence and breakup play important roles in physical-chemical processes and bubbles are treated in two groups in the interfacial area transport equation (IATE). This paper presents a review of IATE for bubble coalescence and breakup to model five bubble interaction mechanisms: bubble coalescence due to random collision, bubble coalescence due to wake entrainment, bubble breakup due to turbulent impact, bubble breakup due to shearing-off, and bubble breakup due to surface instability. In bubble coalescence, bubble size, velocity and collision frequency are dominant. In bubble breakup, the influence of viscous shear, shearing-off, and surface instability are neglected, and their corresponding theory and modelling are rare in the literature. Furthermore, combining turbulent kinetic energy and inertial force together is the best choice for the bubble breakup criterion. The reviewed one-group constitutive models include the one developed by Wu et al., Ishii and Kim, Hibiki and Ishii, Yao and Morel, and Nguyen et al. To extend the IATE prediction capability beyond bubbly flow, two-group IATE is needed and its performance is strongly dependent on the channel size and geometry. Therefore, constitutive models for two-group IATE in a three-type channel (i.e., narrow confined channel, round pipe and relatively larger pipe) are summarized. Although great progress in extending the IATE beyond churn-turbulent flow to churn-annual flow was made, there are still some issues in their modelling and experiments due to the highly distorted interface measurement. Regarded as the challenges to be addressed in the further study, some limitations of IATE general applicability and the directions for future development are highlighted.

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Section: Evaluation Of Frequency Models and Constitutive Models For Bubble Coalescence And Breakupmentioning

confidence: 99%

Interfacial Area Transport Equation for Bubble Coalescence and Breakup: Developments and Comparisons

Chen

Wei

Ding

et al. 2021

Entropy

View full text Add to dashboard Cite

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“…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).…”

Section: Introductionmentioning

confidence: 99%

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

Colombo

Fairweather

2020

Front. Energy Res.

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The accurate prediction of bubbly flows is critical to many areas of nuclear reactor thermal hydraulics, mainly, but not only, in relation to the key role bubble behavior plays in boiling flows. Large scale computations of flows with hundreds of thousands of bubbles are possible at a reasonable computational cost using computational fluid dynamic, multi-fluid Eulerian-Eulerian models. The main limitation of these models is the need to entirely model interfacial transfer processes with proper closure relations. Here, the capabilities and advantages provided by a model that includes an elliptic-blending Reynolds stress turbulence closure (EB-RSM), allowing fine resolution of the velocity field in the near-wall region, are tested over a large database. This database includes mostly monodispersed bubbly flows over a wide range of operating conditions and geometrical parameters, including upward and downward pipe flows, large diameter pipes and a square duct. The model shows encouraging accuracy and robustness, with good agreement over most void fraction distributions and accurate prediction of the magnitude and position of the near-wall void fraction peak. The model does not include any wall force, avoiding all the related uncertainties, and the prediction of the void fraction peak relies on the fine resolution of the near-wall pressure gradient induced by the turbulence field. Overall, the EB-RSM allows accurate resolution of the velocity and turbulence field near the wall, and the transition to this and similar turbulence closures is of value in assisting the ongoing quest for thermal hydraulic models that are accurate and of general applicability. Additional modifications to the near-wall modeling approach, which is still based on its single-phase counterpart, may be required to deal with high void fraction conditions and, in the overall model, additional improvements to momentum and, most importantly, bubble-induced turbulence closures are desirable.

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“…These mutual interactions greatly complicate the analysis of bubbly flows and make the accurate prediction of their thermo‐fluid dynamics particularly challenging. In addition, interfacial heat and mass transfer rates are driven by the interfacial area density and the bubble size distribution in the flow 7,8 . These are in continuous evolution as a consequence of bubble‐bubble interactions that promote bubble coalescence, and bubble‐fluid interactions that can induce bubble breakup 9,10 .…”

Section: Introductionmentioning

confidence: 99%

Computational modeling of microbubble coalescence and breakup using large eddy simulation and Lagrangian tracking

et al. 2020

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The flow of dispersed microbubbles was studied with an Eulerian-Lagrangian technique using large eddy simulation to predict the continuous liquid flow and Lagrangian tracking to compute bubble trajectories. The model fully accounts for bubble coalescence and breakup and was applied to horizontal and vertical channel flows. With low levels of turbulence, gravity in horizontal, and lift in vertical, channel flows govern the bubble spatial and collision distribution. When turbulence is sufficiently high to, at least partially, oppose bubble preferential concentration, more uniform collision and coalescence distributions are found, although these remain peaked near the wall in both configurations. Almost 100% coalescence efficiency was always found, due to bubbles colliding along similar trajectories, with breakup only recorded in a flow of low surface tension refrigerant R134a. Models like this can provide the required quantitative understanding of the microbubbles complex behavior, as well as supporting the development of more macroscopic modeling closures.

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Bubble breakup and coalescence models for bubbly flow simulation using interfacial area transport equation

Cited by 12 publications

References 52 publications

Interfacial Area Transport Equation for Bubble Coalescence and Breakup: Developments and Comparisons

Interfacial Area Transport Equation for Bubble Coalescence and Breakup: Developments and Comparisons

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

Computational modeling of microbubble coalescence and breakup using large eddy simulation and Lagrangian tracking

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