Multi-objective Optimization of a Projectile Tip for Normal Penetration

The main purpose of the present work is multi-objective shape optimization of a projectile tip for impacting and normal penetrating. Velocity drop, weight and inner volume of projectile have been considered as three conflicting objective functions.  For this purpose, at the first step, finite element modeling was done using ABAQUS/Explicit and projectile penetration was examined in different geometric dimensions. Hammersley sequence sampling was employed for designing computer experiments. In the next step, results of the FEM were employed as raw data for MLF-type neural network training to achieve a mathematical model which is able to describe velocity drop behavior. Projectile weight and Inner volume were also expressed in explicit mathematical form using geometric relations. Obtained mathematical models were used as conflicting objective functions for multi-objective optimization of projectile tip using modified NSGA-II. Finally, it is shown that some interesting and important relationships as useful optimal design principles involved in the performance of projectile impact have been discovered by Pareto based multi-objective optimization.