This work presents a microstructure-informed pathway for assigning a material symmetry class to distinguish between tensor components and scalar effective thermal conductivity (ETC) values derived from directional measurements. The framework combines directional thermal measurements with three-dimensional statistical quantification of microstructural features (fibers and voids) to assess whether symmetry assumptions required for tensorial interpretation are justified. Three distinct microstructures of short carbon fiber-reinforced polyetherimide composite were analyzed, with the microstructure statistics altered by the melt extrusion additive manufacturing process parameters. The directional temperature-rise history in the material samples was measured using the Transient Plane Source sensor. The statistics obtained from 3D images of microstructural features were used to assess the material’s anisotropy class to justify the applicability of the transverse isotropic regression method for ETC. One microstructure exhibited characteristics consistent with a statistical transverse isotropy idealization, enabling inference of the ETC tensor; the others did not, and their directional ETC values are treated as test-specific parameters obtained from isotropic model fits. The results also demonstrate that microstructure parameters may strongly influence directional thermal transport. More broadly, this work highlights the need for microstructure-informed justification when interpreting directional measurements as tensor components rather than configuration-dependent scalars, underscoring a critical unresolved gap in the experimental characterization of general anisotropic ETC tensors.
Ke et al. (Thu,) studied this question.