Publication Cover
Numerical Heat Transfer, Part B: Fundamentals
An International Journal of Computation and Methodology
Volume 52, 2007 - Issue 3
147
Views
12
CrossRef citations to date
0
Altmetric
Original Articles

A Comparative Study of Modeling of Radiative Heat Transfer using MOL Solution of DOM with Gray Gas, Wide-Band Correlated-k, and Spectral Line-Based Weighted Sum of Gray Gases Models

&
Pages 281-296 | Received 22 Jan 2007, Accepted 17 Mar 2007, Published online: 29 Aug 2007
 

Abstract

A radiation code based on the method of lines (MOL) solution of the discrete ordinates method (DOM) for the prediction of radiative heat transfer in nongray absorbing-emitting media was developed by incorporation of two different gas spectral radiative property models, wide-band correlated-k (WBCK) and spectral line-based weighted sum of gray gases (SLW) models. Predictive accuracy and computational efficiency of the code were assessed by applying it to one- and two-dimensional test problems and benchmarking its steady-state predictions against line-by-line (LBL) solutions and measurements available in the literature. In order to show the improvements accomplished by these two spectral models over and above the ones obtained by gray gas approximation, predictions obtained by spectral models were also compared with those of the gray gas (GG) model. Comparisons reveal that the MOL solution of the DOM with the SLW model produces the most accurate results for radiative heat fluxes and source terms, at the expense of computation time.

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 486.00 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.