Development and Analysis of a Gravity-Simulated Particle-Packing Algorithm for Modeling Optimized Rocket Propellants
University of Kansas
Electrical Engineering & Computer Science
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The random heterogeneous morphology of modern solid rocket propellant formulations has traditionally been difficult to characterize and quantify. Current computational simulations of these formulations require an accurate description of the packing arrangement in order to correctly model the complex geometric effects that stem from the random morphology. A new and novel computational packing algorithm was invented, implemented, and analyzed using various particle starting arrangements. This was intended to be fast for use in combinatorial chemistry applications and to provide a numerical representation of the material for use with other computational tools, including codes that predict combustion behavior. The packing algorithms were evaluated using homogeneous distributions of spherical particles. Both the Radial Distribution Function (RDF) and the packing fraction were used to evaluate the validity of the invented algorithm.