Abstract
A new wavenumber subinterval grouping strategy was deduced to fit multi-scale multi-group wide-band k-distribution model (MSMGWB) used to calculate remote infrared signal of 3–5-micron wave band emitted by hot combustion gas of hydrocarbon fuel. Further, to deal with influence of initialization on the grouping result and calculation accuracies of the MSMGWB model, an optimization platform was established to find best combination of grouping results and model's Gauss quadrature schemes. The optimization objective function was established based on weighted calculation errors of MSMGWB model in 18 0D cases, using calculation results of line-by-line model (LBL) as benchmark. Optimization result was evaluated using other 0D cases with and without influences of various kinds of aerosol in atmosphere. Further, evaluations were presented on calculation of remote sensing thermal images for a supersonic aircraft exhaust system and its hot jet. Results indicated that the optimized MSMGWB model has higher calculation accuracies, better compatibilities and lower computational cost compared with the previous one. Finally, the influence factors of optimization result were discussed.
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