Enhanced modeling of subgrid-scale turbulence–radiation interaction for infrared characteristics of gas jet plumes

Increasing reliability of subgrid-scale turbulence–radiation interaction (SGS-TRI) model is one of the challenges for further improving prediction accuracies of combustion gas jet infrared signal fluctuation characteristics based on large eddy simulation (LES). This work is devoted to this purpose in two aspects. First, a term describing the relationship between radiation participating components and temperature fluctuations was introduced into the current subgrid Snegirev equation. Then, the temperature variance model with a fixed coefficient was replaced with a dynamic one, combining it with a new algorithm that is more convenient in complex projects for solving the ensemble average coefficient values of various dynamic subgrid models, e.g., the dynamic Smagorinsky model. The validity of these methods was confirmed through direct numerical simulations (DNSs) for isotropic turbulence and test data for a high-temperature air jet flow. Finally, the new SGS-TRI model was combined with the multi-scale multi-group wideband (MSMGWB) k-distribution model, which performs well in radiative transfer calculations involving strongly nonisothermal and inhomogeneous media, to study the infrared characteristics of axisymmetric jet plumes. The results revealed that the TRIs account for more than one-third of the total infrared signal in the 3–5 μm band, with the SGS-TRI effect contributing more than 10%. Additionally, this influence was found to further increase with an increase in detection distances.