Publication Cover
Numerical Heat Transfer, Part A: Applications
An International Journal of Computation and Methodology
Volume 63, 2013 - Issue 6
434
Views
35
CrossRef citations to date
0
Altmetric
Original Articles

Combined Effect of Magnetic Field and Nanofluid Variable Properties on Heat Transfer Enhancement in Natural Convection

&
Pages 452-472 | Received 06 Mar 2012, Accepted 15 Sep 2012, Published online: 28 Jan 2013
 

Abstract

The current work investigated, numerically, enhancement of heat transfer in natural convection using CuO-water nanofluid in the presence of a magnetic field. The governing equations were discretized using the control volume method and solved numerically via the SIMPLE algorithm. For the case of absence of a magnetic field and for low Rayleigh number, the heat transfer was almost insensitive to the presence of nanoparticles. For moderate and high Rayleigh numbers, the presence of nanoparticles had an adverse effect on heat transfer at high volume fraction of nanoparticles. The highest reduction in heat transfer was registered for the case of Ra = 105. Contour maps are generated for the normalized Nusselt number (Nu*) to determine the optimum selection of volume fraction of nanoparticles and magnetic field that gives maximum heat transfer enhancement. The results demonstrated the effectiveness and practicality of using high values of magnetic field in enhancing heat transfer using nanofluids.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 716.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.