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Cited by 461Particle Dynamics in Fluid FlowsGranular flow and fluidized bedsFluid Dynamics and Mixing

Quadrature method of moments for population-balance equations

Marchisio, Daniele L., Pikturna, Jesse T., Fox, Rodney O., Vigil, R. Dennis, Barresi, Antonello A.·2003·AIChE Journal
DOI 10.1002/aic.690490517
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Abstract

Abstract Although use of computational fluid dynamics (CFD) for simulating precipitation (and particulate systems in general) is becoming a standard approach, a number of issues still need to be addressed. One major problem is the computational expense of coupling a standard discretized population balance (DPB) with a CFD code, as this approach requires the solution of an intractably large number of transport equations. In this work the quadrature method of moments (QMOM) is tested for size‐dependent growth and aggregation. The QMOM is validated by comparison with both Monte Carlo simulations and analytical solutions using several functional forms for the aggregation kernel. Moreover, model predictions are compared with a DPB to compare accuracy, computational time, and the number of scalars involved. Analysis of the relative performance of various methods for treating aggregation provides readers with useful information about the range of application and possible limitations.

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Crossref · 10.1002/aic.690490517

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35 of 35 references verified0 citation errors · 0 not checkable

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  • QMOM does not require any upper and lower limits like the CM.

    “In addition, the QMOM does not require any upper and lower limits like the CM.”

    From Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review (2022) · cites this paper as [303]

  • QMOM used by Marchisio et al. [303] to model growth of crystal size with size-independent and size-dependent growth rates using realistic aggregation kernels was validated by comparing with analytical solutions and Monte-Carlo simulations.

    “The QMOM has been used by Marchisio et al. [303] to model the growth of crystal size with size-independent and size-dependent growth rates utilizing realistic aggregation kernels. The method has been validated by comparing the results with analytical solutions [288] and with results obtained with Monte-Carlo simulations.”

    From Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review (2022) · cites this paper as [303]

  • QMOM results agree very well with analytical solutions and have nearly the same accuracy as Monte-Carlo simulations for simultaneous nucleation, growth, and aggregation, while the number of scalars and CPU time are drastically reduced.

    “It is found that the results obtained with the QMOM agree very well with the analytical solutions and they have nearly the same accuracy as those of the Monte-Carlo simulations for the case of simultaneous nucleation, growth, and aggregation. However, the number of scalars involved in the QMOM is drastically reduced, thus entailing a significant reduction of the required CPU time.”

    From Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review (2022) · cites this paper as [303]

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Authors
Marchisio, D. L., Pikturna, J. T., Fox, R. O., Vigil, R. D., & Barresi, A. A.
Affiliations
  • Iowa State University (US)
  • Politecnico di Torino (IT)
Corresponding author
Marchisio, Daniele L.
ORCID
Venue
AIChE Journal
Publisher
Wiley
Published
2003-05
Volume
49
Issue
5
Pages
1266-1276
ISSN
  • 0001-1541 (ISSN-L)
  • 1547-5905
DOI
10.1002/aic.690490517
OpenAlex
W2150452375
Cited by
461
References
35
Citations by year
2026: 22 · 2025: 17 · 2024: 15 · 2023: 15 · 2022: 22 · 2021: 18 · 2020: 13 · 2019: 40 · 2018: 17 · 2017: 27 · 2016: 36 · 2015: 25 · 2014: 21 · 2013: 22 · 2012: 20
FWCI
38.78
Type
journal article
Language
en
Open access
closed
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor, 351 d)
Locations
  • AIChE Journal (publishedVersion)
  • PORTO@Iris (submittedVersion)
  • PORTO Publications Open Repository TOrino (Politecnico di Torino) (submittedVersion)
Topics
  • Physical Sciences › Engineering › Ocean Engineering › Particle Dynamics in Fluid Flows
  • Physical Sciences › Engineering › Computational Mechanics › Granular flow and fluidized beds
  • Physical Sciences › Engineering › Biomedical Engineering › Fluid Dynamics and Mixing
Keywords
quadrature method of moments, population balance equation, aggregation, precipitation chemistry, size-dependent growth, aggregation kernel, computational fluid dynamics coupling, computational cost, particle size distribution

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