Relationship between the spectral line based weighted-sum-of-gray-gases model and the full spectrum k-distribution model

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DOIResolve DOI: http://doi.org/10.1016/j.jqsrt.2014.03.013
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TypeArticle
Journal titleJournal of Quantitative Spectroscopy and Radiative Transfer
ISSN0022-4073
Volume143
Pages111120; # of pages: 10
SubjectCarbon dioxide; Frequency shift keying; Absorption cross sections; Full spectrum k distributions; Gas radiation; Global models; Numerical implementation; SLW; Weighted-sum-of-gray-gases; Weighted-sum-of-gray-gases models; Spectroscopy; absorption; accuracy assessment; gas; Gaussian method; numerical model; radiative transfer; spectrum
AbstractThe relationship between the spectral line based weighted-sum-of-gray-gases (SLW) model and the full-spectrum k-distribution (FSK) model in isothermal and homogeneous media is investigated in this paper. The SLW transfer equation can be derived from the FSK transfer equation expressed in the k-distribution function without approximation. It confirms that the SLW model is equivalent to the FSK model in the k-distribution function form. The numerical implementation of the SLW relies on a somewhat arbitrary discretization of the absorption cross section whereas the FSK model finds the spectrally integrated intensity by integration over the smoothly varying cumulative-k distribution function using a Gaussian quadrature scheme. The latter is therefore in general more efficient as a fewer number of gray gases is required to achieve a prescribed accuracy. Sample numerical calculations were conducted to demonstrate the different efficiency of these two methods. The FSK model is found more accurate than the SLW model in radiation transfer in H2O; however, the SLW model is more accurate in media containing CO2 as the only radiating gas due to its explicit treatment of 'clear gas.'. © 2014 Published by Elsevier Ltd.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC); Measurement Science and Standards (MSS-SME)
Peer reviewedYes
NPARC number21272161
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Record identifier9d2e4255-e372-4057-a4de-7dbbc5cd85b6
Record created2014-07-23
Record modified2016-05-09
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