Abstract

ABSTRACT Aerogel with nano-aerogel structure is regarded as advanced thermal insulation material. Therefore, the impacts of their microstructure and physical features on thermal conductivity are vital for optimizing their fabrication. An improved random growth approach was proposed in this paper to theoretically derive the effective thermal conductivity (ETC) of nano-aerogel. This model can accurately depict the random distribution versus the real microstructure. The Lattice-Boltzmann Method (LBM) was introduced into the model to investigate the nano-scale heat transmission in nano-aerogel with porous structure. The developed model provided significant advantages beyond previous approaches for nano-aerogel by altering the particle’s parameters (e.g. particle’s diameter, specific surface area, and morphological structure) to investigate their effects on thermal performance. Comparison with existing literature was made to validate the accuracy. It indicated good agreement among the modeling results, experimental data, and reference values, implying the accuracy of the modified model. It was demonstrated that the optimal model with 150 kg·m−3 in density gained the lowest effective thermal conductivity and the ideal core distribution probability (while C d = 0.01). An inner vacuum of less than 1.0 Pa was recommended for hunting for optimal adiabatic performance. Moreover, it proved that ETC decreased by increasing the specific surface area of aerogel grain at an optimal density of about 150 kg·m−3.

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