Abstract
In this work, the effective thermal conductivity (ETC) of a composite filled with randomly distributed particles is determined using a thermal lattice Boltzmann model. The Monte Carlo random sampling is applied to generate random microstructures which are then used to evaluate the ETC in the lattice Boltzmann model (LBM). Based on the generated microstructures, the ETC of the composite is predicted by the LBM in terms of the particle volume fraction, the particle size, the particle shape and the thermal conductivity ratio between the particles and matrix. To predict ETC more accurately, the interactions between the particles and matrix are taken into account in the LBM. The predictions are compared with experimental data and those obtained by the original LBM. The comparisons show that the consideration of interactions in the LBM has a great effect on the prediction of the ETC for a particle-filled composite and can yield more accurate results.
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