Correlation Function Approach for Estimating Thermal Conductivity in Highly Porous Fibrous Materials
Heat transport in highly porous fiber networks is analyzed via two-point correlation functions. Fibers are assumed to be long and thin to allow a large number of crossing points per fiber. The network is characterized by three parameters: the fiber aspect ratio, the porosity and the anisotropy of the structure. We show that the effective thermal conductivity of the system can be estimated from knowledge of the porosity and the correlation lengths of the correlation functions obtained from a fiber structure image. As an application, the effects of the fiber aspect ratio and the network anisotropy on the thermal conductivity is studied.