Estimation of the thermal conductivity of hemp based insulation material from 3D tomographic images

In this work, we are interested in the structural and thermal characterization of natural fiber insulation materials. The thermal performance of these materials depends on the arrangement of fibers, which is the consequence of the manufacturing process. In order to optimize these materials, thermal conductivity models can be used to correlate some relevant structural parameters with the effective thermal conductivity. However, only a few models are able to take into account the anisotropy of such material related to the fibers orientation, and these models still need realistic input data (fiber orientation distribution, porosity, etc.). The structural characteristics are here directly measured on a 3D tomographic image using advanced image analysis techniques. Critical structural parameters like porosity, pore and fiber size distribution as well as local fiber orientation distribution are measured. The results of the tested conductivity models are then compared with the conductivity tensor obtained by numerical simulation on the discretized 3D microstructure, as well as available experimental measurements. We show that 1D analytical models are generally not suitable for assessing the thermal conductivity of such anisotropic media. Yet, a few anisotropic models can still be of interest to relate some structural parameters, like the fiber orientation distribution, to the thermal properties. Finally, our results emphasize that numerical simulations on 3D realistic microstructure is a very interesting alternative to experimental measurements.