METHODOLOGY TO SELECT ROD PARAMETERS FOR MAXIMIZING DAMAGE AT HYPERVELOCITY IMPACT

Abstract

Damage assessment is essential when a threat missile payload is intercepted by a missile carrying high explosive warhead. In near miss condition, projectiles (i.e. rods, pellets or fragments) deployed by the warhead impact on a threat missile. Selecting a rod parameter is a challenging task as its effectiveness depends on impact conditions, which varies with various engagement scenarios. Extent of damage depends on target specifications, impact conditions and rod parameters. To resolve this challenge, first simulations are validated for a few experimental data. Using validated simulation model, the data is generated regarding extent of damage caused by changing rod parameters for a set of impact conditions. Then, a methodology to select optimum rod parameter is worked out. Wherein, artificial neural networks (ANN) are built using the discrete set of simulation data and then based on probability of impact conditions, Monte Carlo simulations are performed to obtain probability of successful damage cases. The proposed methodology helps in selecting an optimum rod for the given range of impact conditions.