UC Davis

This paper presents a full set of numerical methods for predicting the effective thermal conductivity of natural fibrous materials accurately, which includes a random generation-growth method for generating micro morphology of natural fibrous materials based on existing statistical macroscopic geometrical characteristics and a highly efficient lattice Boltzmann algorithm for solving the energy transport equations through the fibrous material with the multiphase conjugate heat transfer effect considered. Using the present method, the effective thermal conductivity of random fibrous materials is analyzed for different parameters. The simulation results indicate that the fiber orientation angle limit will cause the material effective thermal conductivity to be anisotropic and a smaller orientation angle leads to a stronger anisotropy. The effective thermal conductivity of fibrous material increases with the fiber length and approach a stable value when the fiber tends to be infinite long. The effective thermal conductivity increases with the porosity of material at a super-linear rate and differs for different fiber location distribution functions. (c) 2006 Elsevier Masson SAS. All rights reserved.