A hybrid stochastic-deconvolution model for particle-laden LES

W. Michalek, J.G.M. Kuerten, R. Liew, J.C.H. Zeegers, B.J. Geurts

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    Abstract

    We develop a hybrid model for large-eddy simulation of particle-laden turbulent flow, which is a combination of the approximate deconvolution model for the resolved scales and a stochastic model for the sub-grid scales. The stochastic model is based on a priori results of direct numerical simulation of turbulent channel flow. In order to correctly predict the flux of particles towards the walls an extra term should be included in the stochastic model, which corresponds to the term related to the well-mixed condition in Langevin models for particle dispersion in inhomogeneous turbulent flow. The model predictions are compared with results of direct numerical simulation of channel flow at a frictional Reynolds number of 950. The inclusion of the stochastic forcing is shown to yield a better agreement than without the stochastic part of the model.
    Original languageEnglish
    Title of host publication11th International Conference of Numerical Analysis and Applied Mathematics 2013
    Subtitle of host publicationICNAAM 2013
    EditorsTheodore Simos, George Psihoyios, Ch. Tsitouras
    PublisherAIP Publishing LLC
    Pages1075-1078
    Number of pages4
    ISBN (Print)978-0-7354-1184-5
    DOIs
    Publication statusPublished - 2013
    Event11th International Conference of Numerical Analysis and Applied Mathematics 2013 - Rodos Palace Hotel, Rhodes, Greece
    Duration: 21 Sep 201327 Sep 2013
    Conference number: 11
    http://history.icnaam.org/icnaam_2013/index.htm

    Publication series

    NameAIP Conference Proceedings
    PublisherAIP
    Volume1558
    ISSN (Print)0094-243X

    Conference

    Conference11th International Conference of Numerical Analysis and Applied Mathematics 2013
    Abbreviated titleICNAAM 2013
    CountryGreece
    CityRhodes
    Period21/09/1327/09/13
    Internet address

    Keywords

    • Particles
    • Dispersion
    • Turbulence
    • Large-eddy simulation

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