IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v535y2019ics0378437119314050.html
   My bibliography  Save this article

MHD natural convection and thermal control inside a cavity with obstacles under the radiation effects

Author

Listed:
  • Usman, M.
  • Khan, Z.H.
  • Liu, M.B.

Abstract

Understanding of flow nature inside a close geometry as well as analysis of heat augmentation through fluids has been gaining a vital interest among research community due to industrial and engineering applications. Herein, a model study is conduced to investigate the heat and mass transfer of Magnetohydrodynamic (MHD) flow enclosed a square cavity with top wall is heated. Two heated and two clod square obstacles are placed inside the square cavity. Feasible nondimensional variables are introduced to transform the continuity, momentum and energy equations into nondimensional form. A finite element model is developed and applied to investigate the numerical solutions of nondimensional set of partial differential equations. In order to scrutinize the significant influence of dimensionless parameters on streamlines, isotherms and isoconcentrations simulations are executed when the bottom squares are heated. It is detected that Nusselt numbers increases as enhancing the thermal radiation parameter. Comparison of the achieved results for local and average Nusselt numbers with published results are presented, which are evident that the suggested method is well-matched to examine the solutions of such types of problems and it can be extended for solving diversified problem of physical nature having complex geometry.

Suggested Citation

  • Usman, M. & Khan, Z.H. & Liu, M.B., 2019. "MHD natural convection and thermal control inside a cavity with obstacles under the radiation effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
  • Handle: RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119314050
    DOI: 10.1016/j.physa.2019.122443
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119314050
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2019.122443?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.

    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:phsmap:v:535:y:2019:i:c:s0378437119314050. 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: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.