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Random packs of spheres have been used to model heterogeneous and porous material morphologies during simulations of physical processes such as burning of coal char, convective burning in porous explosives, and regression of solid rocket propellant. Sphere packs have also been used to predict thermo-mechanical properties, permeability, packing density, and dissolution characteristics of various materials. In this work, we have extended the Lubachevsky–Stillinger (LS) sphere packing algorithm to create polydisperse packs of non-spherical shapes for modeling heterogeneity in complex energetic materials such as HMX and pressed gun propellants. In the method, we represent the various particle shapes using level sets. The LS framework requires estimates of inter-particle collision times, and we predict these times by numerically solving a minimization problem. We have obtained results for dense …