A narrow band model based on the absorption coefficient and its application to the calculation of radiative transfer in two-dimensional enclosures. (November 2022)

• Record Type: Journal Article
• Authors: Fisher, Annette S.; Rani, Sarma L.
• Is Part Of: Journal of quantitative spectroscopy & radiative transfer. Volume 291(2022)
• Publication Date: 2022-11
• Subjects: Spectrum analysis -- Periodicals; Radiation -- Periodicals; Analyse spectrale -- Périodiques; Rayonnement -- Périodiques; Radiation; Spectrum analysis; Periodicals; 543.0858
• DOI: 10.1016/j.jqsrt.2022.108340
• Languages: English
• ISSNs: 0022-4073

Abstract

Highlights: An absorption-coefficient-based narrow band model is extended to 2-D non-gray enclosures. A number of 2-D non-gray cases were considered comprising CO2, H2O, or a mixture of the two gases. Presence of CO2 enhanced the accuracy of narrow band model predictions due to the higher optical thickness of CO2 relative to that of H2 O. Abstract: In a recent article (Fisher and Rani, Vol. 277, JQSRT, 2022), we presented a narrow band model (NBM) with the absorption coefficient as the fundamental radiative property and applied it to predict radiative heat transfer in one-dimensional (1-D) non-gray enclosures. In this communication, we investigate the accuracy of the NBM in computing radiative transfer in two-dimensional (2-D) non-gray enclosures. Radiative fluxes normal to walls and flux divergences computed from NBM simulations are compared with results obtained using three spectral methods: line-by-line (LBL) calculations that serve as the benchmark, wavenumber-selective line-by-line (WS-LBL) calculations, and the spectral line-based weighted sum of gray gases (SLW) method. The gaseous medium in the 2-D rectangular enclosures is non-isothermal and inhomogeneous, with the participating species consisting of CO2, or H2 O, or a mixture of CO2 and H2 O. It is seen that the presence of CO2 enhanced the accuracy of NBM predictions due to the higher optical thickness of CO2 relative to that of H2 O. The predictions of WS-LBL calculations are also in good agreement with LBL data.