Modeling and simulation of mixing in water-in-oil emulsion flow through a valve-like element using a population balance model

Favero, Jovani L.; Silva, Luiz Fernando L.R.; Lage, Paulo L.C.

doi:10.1016/j.compchemeng.2015.01.017

Cited by 20 publications

(6 citation statements)

References 68 publications

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“…(2) and (3)) and the breakage frequency models (Eqs. (7) and (8)) does not hold within the range of the parameters examined in this study; this high- a) The relative error is defined as: (X CFD -X EXP )/X EXP . Figure 7.…”

Section: Failure Of Turbulent Inertial-dominated Dropletmentioning

confidence: 86%

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Simulation of Turbulent Emulsification in a Sonolator Mixer: Interpretation of Drop Breakage Time

et al. 2019

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The simulation of dilute emulsions in a model ACIP2 Sonolator is investigated using computational fluid dynamics and population balance methods. Two breakage frequency models are used that differ in the expression of the drop breakage time. Drop breakage modeling based on homogenous isotropic turbulence (HIT) shows poor agreement of the Sauter mean diameter when compared to the experiments; simulations with the empirical model from Alopaeus et al. yield better agreement. By perturbing the classical HIT spectrum, it is shown that the breakage time in the empirical model corresponds to a non-isotropic energy spectrum. Such spectra have been observed in the non-isotropic near field in a model A Sonolator, which provides a plausible explanation of why the empirical model performs better than the HIT-based model.

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Section: Failure Of Turbulent Inertial-dominated Dropletmentioning

confidence: 86%

“…A computationally tractable approach to solve the PBE, coupled to computational fluid dynamics (CFD), is the quadrature-based moments methods (QBMM) [4]. Coupled CFD-population balance methods (PBM), solved with QBMM, have been reported by several authors [5][6][7].…”

Section: Background and Motivationmentioning

confidence: 99%

Simulation of Turbulent Emulsification in a Sonolator Mixer: Interpretation of Drop Breakage Time

et al. 2019

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“…Among the different methods available, the one most interesting for the investigation of industrial scale liquid-liquid multiphase systems, is the two-fluid model (TFM) (Drew, 1982;Drew and Passman, 2006), implicitly assuming that one of the two phases is continuous, whereas the other one is disperse. The TFM is coupled with PBM to predict the evolution of the DSD (Ramkrishna, 2000), as shown in numerous applications (Hu et al, 2015;Attarakih et al, 2015;Favero et al, 2015). Many methods have been developed to solve the PBM, such as the classes method (CM) (Kumar and Ramkrishna, 1996), the Monte Carlo method (MCM) (Lin et al, 2002;Buffo et al, 2013b;Zhang and You, 2015;Hussain et al, 2015) and the method of moments (MOM) (Hulburt and Katz, 1964).…”

Section: Introductionmentioning

confidence: 99%

Simulation of droplet breakage in turbulent liquid–liquid dispersions with CFD-PBM: Comparison of breakage kernels

Gao

Buffo

et al. 2016

Chemical Engineering Science

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“…Favero et al, 2015), this model is able to handle the intrinsic "polydispersity" of such flows in a simple manner, while allowing for the calibration of physically relevant quantities such as equilibrium sizes or relaxation times of coalescence-and break-up events. These are transport equations which take into account temporal evolution, convective transport, turbulent dispersion, as well as breakage-and coalescence processes.…”

Section: Methods and Applicationsmentioning

confidence: 99%

CFD Simulations of Multiphase Flows Containing Large Scale Interfaces and Dispersed Phases with Selected Production Technology Applications

Johansen

Meese

et al. 2015

Day 1 Tue, October 27, 2015

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Multiphase flows in oil-and gas pipelines involve a variety of different flow regimes. The different flow regimes are determined by the geometric arrangement of oil, gas and water inside the pipe, and evolve in a dynamic manner along a flowline, from bottom hole to receiving facilities. Along the path of the flow, the geometric fluid arrangements (or flow patterns), which develop dynamically, are often outside what is properly accounted for in existing 1D flow models. In such cases, more detailed multidimensional models are needed. As the industry is facing tighter operating margins and stricter regulatory frameworks, more accurate and predictive tools are needed. It is realized that CFD (Computational Fluid Dynamics) type models cannot replace 1D models in most cases, but will be an extremely valuable addition to the toolbox in cases where the 1D models may be insufficient.In the present paper a CFD method will be presented which enables such generic simulations. In this model, the physics of coexisting large scale interfaces and dispersed fields (droplets and bubbles) has been handled. Results obtained by a "Quasi-3D" implementation of the model will be shown for a number of important industrial applications. It will also be shown how such tools can also be applied to improve existing 1D frameworks, or directly to tackle multiphase production technology challenges.

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Modeling and simulation of mixing in water-in-oil emulsion flow through a valve-like element using a population balance model

Cited by 20 publications

References 68 publications

Simulation of Turbulent Emulsification in a Sonolator Mixer: Interpretation of Drop Breakage Time

Simulation of Turbulent Emulsification in a Sonolator Mixer: Interpretation of Drop Breakage Time

Simulation of droplet breakage in turbulent liquid–liquid dispersions with CFD-PBM: Comparison of breakage kernels

CFD Simulations of Multiphase Flows Containing Large Scale Interfaces and Dispersed Phases with Selected Production Technology Applications

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