Numerical quantification of coupling effects for radiation-conduction heat transfer in participating macroporous media: Investigation of a model geometry

Radiative-conductive heat transfer in porous media is usually investigated by decoupling the heat transfer modes and solving the volume-averaged continuum equations using effective transport properties. However, both modes are naturally coupled and coupling effects might significantly affect the results. We aim at providing quantitative understanding of the coupling effects occurring in a model geometry. This is an important first step towards improving the accuracy of heat transfer predictions in engineering applications. We developed a numerical method using a structured mesh, cell centered finite volumes and Monte Carlo ray tracing techniques in order to simulate the 3-dimensional and unsteady coupled radiative conductive heat transfer in semitransparent macroporous media. We have optimized the numerical method with regards to memory and computational requirements leading to optimal performance and allowing to perform a parameter variation study for various steady state cases. We conducted a parameter study considering different optical and thermal material properties and boundary conditions in order to quantify the coupling effect between conduction and radiation, and to demonstrate its dependencies. In terms of thermal properties, it was found that the ratio of bulk thermal conductivities is governing the coupling effect. A distinct peak at a given conductivity ratio was found. The influence of optical properties is discussed in details. It was found that a significant coupling effect exists, reaching up to 15% of the total thermal heat flux. The verified modeling framework in conjunction with our non-dimensionalization offers a tool to investigate the importance of radiation-conduction coupling in a quantitative manner. It is an important step towards understanding the detailed mechanisms of radiation and conduction coupling and provides engineering guidelines on the importance of these effects. (C) 2017 Elsevier Ltd. All rights reserved.