Cited by 23Fluid Dynamics and MixingMinerals Flotation and Separation TechniquesParticle Dynamics in Fluid Flows

An extended quadrature-based mass-velocity moment model for polydisperse bubbly flows

Yuan, Cansheng, Kong, Bo, Passalacqua, Alberto, Fox, Rodney O.·2014·The Canadian Journal of Chemical Engineering

Abstract

Abstract Accurately predicting polydisperse bubbly flow is a nontrivial task due to the complexity of the bubble number density function (NDF) and the strong dependence of the instantaneous bubble velocity on the bubble size and shape. To describe polydisperse bubbly flow, a joint mass‐velocity NDF is adopted in this work. In the absence of mass transfer between phases and coalescence or breakage, the bubble mass is a conserved quantity from which the bubble size and shape can be found given the liquid pressure and surface tension. Quadrature‐based moment methods (QBMM) are applied to solve numerically the kinetic equation of the joint NDF using the extended quadrature method of moments (EQMOM) coupled with an open‐source incompressible Navier–Stokes solver for the liquid phase. Transport equations for the joint mass‐velocity moments are derived from a kinetic equation for the joint NDF and closure is attained using a monokinetic NDF valid in the limit of small bubble Stokes number. The integer moments with respect to mass are used to reconstruct the continuous univariate NDF with EQMOM, while the joint mass‐velocity moments are used to determine the bubble velocity as a continuous function of the bubble mass. The model is first applied to simulate a quasi‐2‐D bubble column with different aeration profiles and a narrow bubble size distribution in order to validate the approach with experimental data from the literature. Additional cases with a wide continuous bubble size distribution are used to show the ability of the modelling approach to describe polydisperse bubbly flows.

Integrity signals

Registry

Crossref · 10.1002/cjce.22006

Cites

32 of 32 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • EQMOM implemented in OpenFOAM for a quasi 2D bubble column yields numerical results agreeing well with experimental ones in time-averaged axial liquid velocity profile and time-averaged gas volume fraction.

    “Yuan et al. [329] implemented the EQMOM in the open-source code OpenFOAM ® to simulate the fluid flow of a quasi 2D bubble column. Numerical results agree well with experimental ones, in terms of time-averaged axial liquid velocity profile and time-averaged gas volume fraction.”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Yuan, C., Kong, B., Passalacqua, A., & Fox, R. O.
Affiliations
Iowa State University (US)
Venue
The Canadian Journal of Chemical Engineering
Publisher
Wiley
Published
2014-10
Volume
92
Issue
12
Pages
2053-2066
ISSN
  • 0008-4034 (ISSN-L)
  • 1939-019X
OpenAlex
W1998655311
Cited by
23
References
32
Citations by year
2026: 1 · 2025: 1 · 2023: 1 · 2022: 1 · 2021: 1 · 2020: 3 · 2019: 6 · 2018: 2 · 2017: 1 · 2016: 4 · 2015: 2
FWCI
1.21
Type
journal article
Language
en
Open access
closed
Locations
The Canadian Journal of Chemical Engineering (publishedVersion)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Fluid Dynamics and Mixing
  • Physical Sciences › Environmental Science › Water Science and Technology › Minerals Flotation and Separation Techniques
  • Physical Sciences › Engineering › Ocean Engineering › Particle Dynamics in Fluid Flows
Keywords
quadrature-based moment methods, bubble size distribution, bubble velocity, kinetic equations, Stokes number, bubble column, two-phase flow modeling

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review