The generalized quadrature method of moments

Fox, Rodney O.; Laurent, Frédérique; Passalacqua, Alberto

doi:10.1016/j.jaerosci.2022.106096

Cited by 7 publications

(2 citation statements)

References 35 publications

(83 reference statements)

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“…The initial droplet diameter, d i was assumed to be uniform. Note that more advanced univariate moment inversion methods, such as EQMOM 25 and GQMOM, 26 can be used here, but that is not the focus of the current work, which will be studied in future work.…”

Section: Cfd Model and Coupling With Pbmmentioning

confidence: 99%

“…However, it cannot predict the NDF and has the problem of nonclosure issues. The quadrature-based moment method (QBMM), including the quadrature method of moments (QMOM), , extended quadrature method of moments (EQMOM), and generalized quadrature method of moments (GQMOM), is introduced to overcome these limitations. QBMM solves the transport equation of the low-order moments (usually 4 to 8 moments) and uses the moment set information to approximate the NDF by moment inversion.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Droplets Breakup Models of Emulsification Process in a Liquid–Liquid Taylor–Couette Flow

He,

Hong,

Zhang

et al. 2024

Ind. Eng. Chem. Res.

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The computational fluid dynamics and the quadrature method of moments were adopted to simulate the turbulent liquid−liquid (L-L) emulsion flow inside the Taylor−Couette (TC) flow. Various breakup kernels and daughter size distribution models were tested. Generally, we found that the breakup kernel determines the mean droplet diameter, whereas the daughter size distribution function influences the DSD shape more. The coefficients in the CT and Chen breakup kernel were adjusted using the method proposed by Ravichandar et al. ( 2022), and it was found to be unsuitable in the studied liquid systems. The MB and Lehr breakup kernels better predicted the mean droplet diameter, but they were not applicable in highly dispersed phase viscosity systems in L-L TC flow. The MB breakup kernel and the Lehr daughter size distribution function predicted the experimental DSD very well at Re = 10400. The M-shaped Lehr daughter size distribution function showed diverse characteristics under different conditions and exhibited an optimal performance within specific parameters.

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Section: Cfd Model and Coupling With Pbmmentioning

confidence: 99%