Silica aerogel is a kind of nanoporous superinsulation material. Usually some kinds of particles and fibers are added into the aerogel material to enhance its ability of restraining radiation heat transfer and improving its strength. These functional additives will combine with aerogel material to form the aerogel composite insulation material. In this paper, aiming at fully investigating the heat transfer characteristics of the composite insulation material, structure reconstruction study and numerical study were performed. The random-number-based algorithms were proposed to reconstruct the structure of particle type multiphase material and fibrous type multiphase material. Then based on the structure reconstruction study, numerical method was presented for the combined conduction and radiation heat transfer of aerogel composite insulation material. In the numerical model, discrete ordinate method was used to solve the radiative transfer equation and finite volume method was used to solve the energy equation. By using the numerical model as well as the structure reconstruction method, the insulation performance of the composite material was discussed in detail. The results showed that: (1) as the content of particle/fiber increased, the conductive thermal conductivity increased and the radiative thermal conductivity decreased, the total thermal conductivity of the material decreased firstly and then increased; (2) an optimum doping content of opacifier particles can be found with the variation of particle volume fraction which possess different values at different temperature levels; (3) particle clusters have significant effect on the heat transfer performance of the composite insulation materials. When particle volume fraction becomes to a high value, large deviation emerges between the theoretical method and numerical method due to the particle clusters in the randomly generated structures; (4) for the directionally distributed fibrous material, its conductive thermal conductivity decayed exponentially with the angle between heat flux direction and fiber orientation. A modified model was proposed for the directionally distributed fibrous material which can effectively predict its conductive thermal conductivity. (C) 2015 Elsevier Ltd. All rights reserved.