Thermal conductivity of composite building materials: A pore scale modeling approach

In this article the effective thermal conductivity (ETC) of a wide range of multiphase porous building materials has been estimated numerically. The numerical random generation macro-meso pores (RGMMP) method, which is based on the macroscopic statistical information, such as the porosity, volume fraction of macro-meso pores, is used here for the reconstruction of microstructures of various porous building materials. The distribution of macro-meso pores and their sizes are controlled by core distribution probability and porosity. The lattice Boltzmann method equipped with the conservation of energy and suitable boundary conditions at multiple interfaces is adopted for the numerical solution of energy transport equations through the porous media. After comparison with the benchmark of some theoretical solutions and existing experimental observations, it is employed for the estimation of ETC of different multiphase building materials. The resultant predictions through proposed model accord much better with the existing experimental data than the values obtained through traditional theoretical models. Moreover, comparison of the current reconstruction method, RGMMP, with previously proposed Quartet Structure Generation Set (QSGS) method indicated that predictions with present model is more accurate than those obtained with QSGS. Finally the method is applied for analyzing the variation of ETC with temperature and found that value of thermal conductivity rises with increase in temperature for all the mentioned building materials.