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    Effect of drag models on CFD–DEM predictions of bubbling fluidized beds with Geldart D particles

    Access Status
    Fulltext not available
    Authors
    Agrawal, V.
    Shinde, Yogesh
    Shah, Milin
    Utikar, Ranjeet
    Pareek, Vishnu
    Joshi, J.
    Date
    2018
    Type
    Journal Article
    
    Metadata
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    Citation
    Agrawal, V. and Shinde, Y. and Shah, M. and Utikar, R. and Pareek, V. and Joshi, J. 2018. Effect of drag models on CFD–DEM predictions of bubbling fluidized beds with Geldart D particles. Advanced Powder Technology. 29 (11): pp. 2658-2669.
    Source Title
    Advanced Powder Technology
    DOI
    10.1016/j.apt.2018.07.014
    ISSN
    0921-8831
    URI
    http://hdl.handle.net/20.500.11937/71340
    Collection
    • Curtin Research Publications
    Abstract

    © 2018 The Society of Powder Technology Japan The selection of a drag model is of critical importance for fluidized bed simulations. In this study, the effect of different drag models was investigated by conducting Computational Fluid Dynamics and Discrete Element Method (CFD–DEM) simulations of bubbling fluidized beds and comparing the results with two sets of experimental data. For the data reported by Goldschmidt et al. (2004), the Di Felice model resulted in average particle height with less than 16% discrepancy, while the other drag models resulted in significantly lower values with discrepancies between 11 and 45%. For the NETL data (Gopalan et al., 2016), all the drag models showed reasonable qualitative agreement for the radial profiles of the solid velocities; however, no single model resulted in close quantitative predictions. None of the models were found to be suitable for both data sets. The analysis suggests that the Ayeni model and Di Felice model provide better predictions than the conventionally used Gidaspow model and Syamlal–O'Brien model.

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