Thermal Conduction in Particle Packs via Finite Elements

Conductive transport in heterogeneous materials composed of discrete particles is a fundamental problem for a number of applications. While analytical results and rigorous bounds on effective conductivity in mono-sized particle dispersions are well established in the literature, the methods used to arrive at these results often fail when the average size of particle clusters becomes large (i.e., near the percolation transition where particle contact networks dominate the bulk conductivity). Our aim is to develop general, efficient numerical methods that would allow us to explore this behavior and compare to a recent microstructural description of conduction in this regime. To this end, we present a finite element analysis approach to modeling heat transfer in granular media with the goal of predicting effective bulk thermal conductivities of particle-based heterogeneous composites. Our approach is verified against theoretical predictions for random isotropic dispersions of mono-disperse particles at various volume fractions up to close packing. Finally, we present results for the probability distribution of the effective conductivity in particle dispersions generated by Brownian dynamics, and suggest how this might be useful in developing stochastic models of effective properties based on the dynamical process involved in creating heterogeneous dispersions.