Mesoscopic framework for predicting the effective radiative thermal conductivity of porous media

Accurate assessment of the effective radiative thermal conductivity (ERTC) of porous media is of great significance for their applications under high-temperature conditions. Existing numerical methods face considerable challenges in predicting the ERTC of porous media due to the complex structures and numerous interfaces. In this work, a mesoscopic framework is proposed to accurately predict the ERTC of porous media. The framework first employs a random connectivity growth algorithm to generate porous structures, and then develops the lattice Boltzmann method (LBM) for radiative heat transfer in porous media. The framework can efficiently handle complex radiative transport processes and numerous interfaces. Based on this framework, the effects of key structural parameters such as the connectivity parameter, particle radius, gradient distribution and porosity on the ERTC are systematically investigated. The framework is validated against the Monte Carlo method with an average deviation of 2.29%. The results show that increasing connectivity from g = 0–1 raises the ERTC by 189%–226%, while increasing particle radius from 0.5 to 3.0 mm raises it by 89%–137%, depending on porosity. Among gradient distributions, the vertical gradient achieves the highest ERTC, the ERTC of the forward vertical configuration is 125% higher than that of the reverse configuration. This mesoscopic framework is expected to provide an effective numerical tool for predicting the ERTC of porous media.