Prediction of the Effective Thermal Conductivity of Aerogel Nano-Porous Materials

Accurate prediction of the effective thermal conductivities of aerogel nano-porous materials has remained to be a challenging problem. A new method to predict their insulation performance is proposed in this paper. Firstly, a random generation-growth method, following the solid-phase growth principle, is used to reconstruct the two-dimensional open-cell mesoscopic structures. The pore size of aerogel can be controlled preliminarily and the similarity between reconstructive and real structures can be enhanced with this generation method. On the basis of the generated structure, the lattice Boltzmann method D2Q9 is adopted to predict the effective thermal conductivity. The results are agreed well with published data, which demonstrate that this method can not only guarantee the stochastic character of the aerogel structure but also is reliable for practical applications. Furthermore, the effects of porosity, ambient pressure and temperature on the heat transfer performance are investigated. There exists an optimal density making the effective thermal conductivity being minimum and the optimal density is different under various temperatures. The effective thermal conductivity decreases with the ambient pressure decrease and then remains a constant value. Finally, the contributions of gas phase, solid phase and radiative heat transfer to the effective thermal conductivity are separated by decomposition method.