Improved Curtis-Godson approximation method for infrared optical radiation properties prediction of high-temperature combustion system

Jinlu Li; Lu Bai; Chao Huang; Lixin Guo

doi:10.1117/12.2654783

15 December 2022 Improved Curtis-Godson approximation method for infrared optical radiation properties prediction of high-temperature combustion system

Jinlu Li, Lu Bai, Chao Huang, Lixin Guo

Author Affiliations +

Proceedings Volume 12478, Thirteenth International Conference on Information Optics and Photonics (CIOP 2022); 124782V (2022) https://doi.org/10.1117/12.2654783
Event: Thirteenth International Conference on Information Optics and Photonics (CIOP 2022), 2022, Xi'an, China

Abstract

The increasing significance of high-temperature gases in heat transfer, combustion, and rocket exhaust plume, restrictions motivate researchers to continuously seek more efficient and accurate models to explain the related physical phenomena. The traditional Curtis-Godson approximation (CGA) will lose accuracy in the presence of severely inhomogeneous participating combustion gases by ignoring the high sensitivity of the narrow-band halfwidth to gas temperature and pressure. In order to improve the accuracy of traditional CGA, this paper introduces a correction function to correct the narrow-band half-width along the line-of-sight direction of the combustion system, where the correction function is related to the thermodynamic state of the high-temperature gas. The infrared spectral transmissivities calculated by the line-by-line approach are used as the benchmark solution to evaluate the accuracy of our improved CGA. The results in this study can be used to efficiently calculate the radiative transfer of rocket exhaust plumes.

Citation Download Citation

Jinlu Li, Lu Bai, Chao Huang, and Lixin Guo "Improved Curtis-Godson approximation method for infrared optical radiation properties prediction of high-temperature combustion system", Proc. SPIE 12478, Thirteenth International Conference on Information Optics and Photonics (CIOP 2022), 124782V (15 December 2022); https://doi.org/10.1117/12.2654783

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