Abstract
The paper addresses issue of efficiency of an event-driven simulation of a granular materials system. Performance of a number of techniques for collision detection optimization is analyzed in the framework of a shaker ball mill model. Dynamic computational geometry data structures are employed for this purpose. The results of the study provide insights on how the parameters of the system, such as the number of particles, the distribution of their radii and the density of packing, influence simulation efficiency. © Springer-Verlag 2002.
Cite
CITATION STYLE
Gavrilova, M., Rokne, J., Gavrilov, D., & Vinogradov, O. (2002). Optimization techniques in an event-driven simulation of a shaker ball mill. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2331 LNCS, pp. 115–124). Springer Verlag. https://doi.org/10.1007/3-540-47789-6_12
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