Design Methods for the Lethality of Fragmentation Warhead based on a Multi-Objective Optimization Algorithm

Abstract

Abstract Fragmentation warhead is the main weapon used to damage personnel and light armored objectives, with the lethal parameters primarily consisting of the number and velocity of fragments. Increasing the lethality of fragmentation warhead is currently the most important development direction for fragmentation warhead. The formation process of natural fragment is complicated and there are several factors that affect the properties of fragment, so there are still many techniques of developing the lethality of fragmentation warhead. In this paper, our object is to focus on the optimization design for the lethality of fragmentation warhead, based on the optimal Latin hypercube test design method and the radial basis function neural network surrogate modelling, taking the number of effective fragments per unit mass and the average kinetic energy of the effective fragments as the optimization objectives, and the explosive charge, the fragment material, the overall structure and initiation method are considered, respectively. The Pareto optimal solution sets under different design variables are obtained, and the optimal matching of multiple design parameters is realized, establishing the integration design method for “explosive - material-structure” of the fragmentation warhead. The research results can provide technical support for the structural optimization design of the fragmentation warhead.