IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v332y2018icp351-362.html
   My bibliography  Save this article

Conduction and convection heat transfer in a dense granular suspension

Author

Listed:
  • Yang, Hyunjin
  • Massoudi, Mehrdad

Abstract

Flow and heat transfer in a suspension down an inclined plane is studied; non-linear constitutive relations for the stress tensor and the heat flux vector are used. The (material) coefficients appearing in these constitutive relations are assumed to be functions of the volume fraction. Different thermal boundary conditions including radiation boundary condition at the free surface are used and a parametric study is performed to study the impact of the dimensionless numbers on the flow and heat transfer. The dimensionless forms of the governing equations are solved numerically, and velocity, volume fraction and temperature fields are obtained.

Suggested Citation

  • Yang, Hyunjin & Massoudi, Mehrdad, 2018. "Conduction and convection heat transfer in a dense granular suspension," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 351-362.
    • Handle: RePEc:eee:apmaco:v:332:y:2018:i:c:p:351-362
    DOI: 10.1016/j.amc.2018.03.056
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300318302297
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2018.03.056?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yue Hua & Jiang-Zhou Peng & Zhi-Fu Zhou & Wei-Tao Wu & Yong He & Mehrdad Massoudi, 2022. "Thermal Performance in Convection Flow of Nanofluids Using a Deep Convolutional Neural Network," Energies, MDPI, vol. 15(21), pages 1-16, November.

    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:eee:apmaco:v:332:y:2018:i:c:p:351-362. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.