Multiscale heat-transfer modeling and structural optimization of fiber-reinforced phenolic composites

Due to the importance of fiber-reinforced phenolic composites in thermal protection systems for near-space applications, this study develops a multiscale numerical framework to model the heat transfer mechanisms in these materials. The framework integrates micro-CT and FIB-SEM characterization with DLCA-based stochastic modeling and lattice Boltzmann simulations. It captures anisotropic conduction along fibers, phonon scattering within the solid phase, and Knudsen diffusion in nanoporous gases. The framework links structural parameters, such as particle size and porosity, to effective thermal conductivity. Parametric analysis reveals the dominant role of interparticle bonding in solid-phase conduction and shows how particle size and porosity modulate heat transfer. The model predicts a thermal conductivity of 0.013 W/(m·K) under ambient pressure conditions (50–150 °C), achieving significant reductions of 86 % and 63 % relative to boron- and silicon-modified phenolic matrices, respectively. This work establishes a reproducible structure–property relationship and provides a pathway for optimizing nanoscale structures to improve the thermal insulation performance of phenolic-based composites.