2004
DOI: 10.1021/ie049555j
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On the Comparison between Population Balance Models for CFD Simulation of Bubble Columns

Abstract: CFD simulations of bubble columns have received much attention, and several multiphase models have been developed, tested, and validated through comparison with experimental data. It is well-known that bubble coalescence and breakup can lead to significant variations in the bubble size distribution and that, to model the evolution of the dispersed gas phase, the population balance equation has to be solved. In this work, a classes method (CM) and a method of moments (MOM) are investigated and compared. The MOM… Show more

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Cited by 125 publications
(86 citation statements)
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“…A Sauter mean diameter, d sauter can be specified to characterize the local behavior of a distribution of bubbles/droplets, 11 but the evolution of this parameter throughout the separator via a coalescence kernel is, in general, limited to dispersed volume loadings. 12 Specifically,…”
Section: Modeling Approachmentioning
confidence: 99%
“…A Sauter mean diameter, d sauter can be specified to characterize the local behavior of a distribution of bubbles/droplets, 11 but the evolution of this parameter throughout the separator via a coalescence kernel is, in general, limited to dispersed volume loadings. 12 Specifically,…”
Section: Modeling Approachmentioning
confidence: 99%
“…Detailed models using the locally polydisperse approach give more information on the secondary phase behavior (Dhanasekharan et al [20]; Venneker et al [21]). The most used methods of locally polydisperse models are the Method of Classes (CM) (Balakin et al [22]; Bannari et al [1]; Becker et al [23]; Kumar and Ramkrishna [24]; Kumar and Ramkrishna [25]; Puel et al [26]), Quadrature Method of Moments (QMOM) (McGraw [27]; Marchisio et al [28]; Marchisio et al [29]; Marchisio et al [30]; Sanyal et al [31]) and Direct Quadrature Method of Moments (DQMOM) (Silva and Lage [32]; Selma et al [33]; Marchisio and Fox [34]). The method of classes, while intuitive and accurate, is computationally intensive due to the large number of classes required to finely discretize the Number Density Function (NDF) with a large number of classes.…”
Section: Introductionmentioning
confidence: 99%
“…Marchisio and Fox (2005) showed that the PBE can be approximated to a good accuracy by as few as four moment equations in DQMOM. This is a very small number of equations when compared to the method of classes-the other method used to solve PBEs (Marchal et al, 1988;Sanyal et al, 2005;Bannari et al, 2008). This particular advantage over other PBE solution methods, along with its adaptive quadrature approach, has inspired many researchers to use DQMOM to model polydispersed flows lately (Zucca et al, 2006;Selma et al, 2010;Chan et al, 2010).…”
Section: Introductionmentioning
confidence: 99%