Droplet coalescence and breakage in turbulent liquid–liquid dispersions is simulated by using computational fluid dynamics (CFD) and population balance modeling. The multifractal (MF) formalism that takes into account internal intermittency was here used for the first time to describe breakage and coalescence in a surfactant-free dispersion. The log-normal Extended Quadrature Method of Moments (EQMOM) was for the first time coupled with a CFD multiphase solver. To assess the accuracy of the model, predictions are compared with experiments and other models (i.e., Coulalogou and Tavlarides kernels and Quadrature Method of Moments [QMOM]). EQMOM and QMOM resulted in similar predictions, but EQMOM provides a continuous reconstruction of the droplet-size distribution. Transient predictions obtained with the MF kernels result in a better agreement with the experiments.

Droplet breakage and coalescence in liquid-liquid dispersions: Comparison of different kernels with EQMOM and QMOM / Li, Dongyue; Gao, Zhengming; Buffo, Antonio; Podgorska, Wioletta; Marchisio, Daniele. - In: AICHE JOURNAL. - ISSN 0001-1541. - STAMPA. - 63:6(2017), pp. 2293-2311. [10.1002/aic.15557]

Droplet breakage and coalescence in liquid-liquid dispersions: Comparison of different kernels with EQMOM and QMOM

BUFFO, ANTONIO;MARCHISIO, DANIELE
2017

Abstract

Droplet coalescence and breakage in turbulent liquid–liquid dispersions is simulated by using computational fluid dynamics (CFD) and population balance modeling. The multifractal (MF) formalism that takes into account internal intermittency was here used for the first time to describe breakage and coalescence in a surfactant-free dispersion. The log-normal Extended Quadrature Method of Moments (EQMOM) was for the first time coupled with a CFD multiphase solver. To assess the accuracy of the model, predictions are compared with experiments and other models (i.e., Coulalogou and Tavlarides kernels and Quadrature Method of Moments [QMOM]). EQMOM and QMOM resulted in similar predictions, but EQMOM provides a continuous reconstruction of the droplet-size distribution. Transient predictions obtained with the MF kernels result in a better agreement with the experiments.
2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2671291
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