Abstract
Results of empirical studies of four algorithms for collision detection optimization (CDO) in a framework of event-driven simulation of mechanically alloyed materials are presented. Performance analysis is conducted in a framework of a shaker ball mill model. The results of the study provide insights on how the physical characteristics of the modeled system, such as the number of particles, the distribution of their radii and the density of packing, influence the simulation. Algorithms presented are suitable for parallelization on EREW PRAM architecture with p processors.
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Gavrilova, M.L. Empirical Studies of Optimization Techniques in the Event-Driven Simulation of Mechanically Alloyed Materials. The Journal of Supercomputing 28, 165–176 (2004). https://doi.org/10.1023/B:SUPE.0000020176.35946.9d
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DOI: https://doi.org/10.1023/B:SUPE.0000020176.35946.9d