Radiative heat transfer (RHT) is often the dominant mode of heat transfer in flames, fires, and combustion systems and affects significantly temperature distributions directly and kinetically controlled chemical processes indirectly. Modeling RHT accurately in multidimensional flames and combustion systems is challenging mainly due to the highly spectral dependence of radiative properties of combustion products, the high computational cost of solving the radiative transfer equation (RTE), and the strong turbulence and radiation interactions (TRI). Significant progress has been made in all the three aspects in the last three decades and the state-of-the-art models and methods have been incorporated into CFD practice for modeling fires, turbulent jet flames, and turbulent combustion in combustion systems. In this article, we first discuss the coupling between RHT and combustion and the important role played by RHT in some fundamental flame phenomena. Then we discuss the state-of-the-art radiation models with a focus on RTE solvers, radiative property models and TRI. Next, we review the recent simulations of turbulent combustion systems involving these state-of-the-art radiation models. Finally, we provide concluding remarks and some potential research areas to advance RHT modeling in multiphase reacting flows.
Nomenclature, , area normal to directions x, y and z [m 2 ] non-grey stretching factor for WSGG, SLW, and FSK methods absorption cross-section of a soot primary particle [m 2 ] absorption cross-section of a soot aggregate [m 2 ] diameter [m] , , integral over a control angle of the direction cosines relative to x, y and z-axis particle size parameter [-] radiant fraction [-] array of variables defining the absorption coefficient, = { , , , } Ω solid angle [sr] Subscript Fuel direction j spectral line S soot at a given wavenumber Superscript aggregate lth direction (DOM) or lth control angle (FVM) mth direction (DOM) or mth control angle (FVM) primary particle Operators 〈 〉 Reynolds averaged quantity ′ Reynolds fluctuating quantity ̅ filtered (or resolved) quantity ′′ subgrid-scale (or residual) fluctuation Recently, quasi-MC methods [43], [44] were employed to solve RHT problems in 3D participating media, aimed at the improvement of the convergence rate, and therefore the computational efficiency. In these methods, the random numbers are replaced by low-