Prediction of effective thermal properties of fibrous material from 3D tomographic images

Abstract

Fibrous composites materials are commonly used for thermal insulating purpose and cover a wide range of applications, from high temperature to building insulators. Their effective thermal properties strongly depends on the fibers arrangement, i.e. fibers orientations and number of fibers contacts., which are a consequence of the manufacturing process. Furthermore, local thermal conductivity of the fiber are often anisotropic, as it is the case in natural fibers for example. Thermal optimization of such materials is a major industrial stake and it requires tools to study the complex relation between the materials microstructure and the effective properties. In this work, we make use of tridimensionnal images of the fibrous microstructure to quantify some aspects of the microstructure, like fibers local orientations. These information are then used to compute effective properties directly on an representative elementary volume (REV) of the real structure, within the framework of the volume averaging method applied.