A Performance Analysis of Kinetic Energy Ammunition Optimisation through Evolutionary Methods

Alexandre de Assis Motta¹; Nelson Francisco Favilla Ebecken¹

¹ Federal University of Rio de Janeiro

doi:10.20906/CPS/CILAMCE2017-0051

Resumo

Kinetic energy munitions performance is usually measured by the achieved penetration when perpendicularly fired against a rolled homogeneous steel target. Much work has been done in the field but none looking into applying an evolutionary method as an optimisation tool. The problem is multi-variable with conflicting objectives, well-suited, in principle, for the application of Genetic Algorithms to improve performance. A method has been developed for such purpose but, despite the use of several penalisation strategies (including no penalisation at all), has not been able to find a unique global optimal set of parameters leading to the maximum possible penetration every time. However, results indicate that penetrations in excess of current existing munitions are possible to achieve, therefore the value of the method. This work introduces the method and presents a performance study in a high-performance, distributed memory environment.

Palavras-chave: Performance Analysis; Kinetic Energy Ammunition; Long Rod; Optimisation; Genetic Algorithms