IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0119155.html
   My bibliography  Save this article

Numerical Analysis of Granular Flows in a Silo Bed on Flow Regime Characterization

Author

Listed:
  • Xingtuan Yang
  • Nan Gui
  • Jiyuan Tu
  • Shengyao Jiang

Abstract

The flow characteristics of a gravity-driven dense granular flow in a granular bed with a contracted drainage orifice are studied by using discrete element method and quantitative analysis. Three values of discharging rates, ranging from fast to slow dense flows, are investigated. Time variations and derivatives of mean forces and velocities, as well as their respective correlations, are analyzed to quantitatively depict the characteristics of granular flow as well as flow regime categorization. The auto-correlation functions, as well as their Fourier spectrums, are utilized to characterize the differences between the mechanisms of slow and fast granular flows. Finally, it is suggested that the flow regimes of slow and fast flows can be characterized by the kinetic and kinematic flow properties of particles.

Suggested Citation

  • Xingtuan Yang & Nan Gui & Jiyuan Tu & Shengyao Jiang, 2015. "Numerical Analysis of Granular Flows in a Silo Bed on Flow Regime Characterization," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-14, March.
  • Handle: RePEc:plo:pone00:0119155
    DOI: 10.1371/journal.pone.0119155
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0119155
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0119155&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0119155?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0119155. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.