Publication Cover
Numerical Heat Transfer, Part A: Applications
An International Journal of Computation and Methodology
Volume 51, 2007 - Issue 3
353
Views
48
CrossRef citations to date
0
Altmetric
Original Articles

Forced-Convection Cooling Enhancement of Heated Elements in a Parallel-Plate Channels using Porous Inserts

&
Pages 293-312 | Received 21 Dec 2005, Accepted 07 Apr 2006, Published online: 13 Feb 2007
 

Abstract

A numerical investigation of the two-dimensional, laminar forced-convection cooling of heat-generating obstacles mounted on adiabatic walls in a parallel-plate channel is presented. The effect on heat transfer of insertion of a porous matrix between the blocks is considered. The Darcy-Brinkman-Forchheimer model is used to model the flow inside the porous domain. Temperature and velocity distributions in the problem domain for incompressible, laminar, and steady flow are simulated by solving governing equations numerically for appropriate boundary conditions. A computer program based on the SIMPLE algorithm is developed. The local Nusselt number at the walls of the blocks, mean Nusselt number, and maximum temperature in the blocks are examined for different Reynolds numbers, Darcy numbers, and porous-layer thicknesses. The results show that heat transfer can be enhanced by using high-thermal-conductivity porous inserts. With insertion of heated elements and porous matrix, the pressure drop increases rapidly along the channel with increase of Reynolds number.

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.