Computer modeling for damage assessment of KE-rod warheads against ballistic missiles

Luis A Espino, University of Texas at El Paso

Abstract

Current efforts on ballistic missile systems are focused on the development of direct-impact interceptor missiles. However, high encounter velocities and the possibility of decoy systems make a direct hit extremely difficult. In order to increase the system kill probability, new systems combine guidance technology and a guided-ejection system that can fire a cluster of penetrators towards the target. This thesis investigates some of the parameters that affect the “kill” performance of the interceptor “guided projectiles”, or as commonly known in the missile industry KE-rod warheads, such as the shape, the projectile size, the number of projectiles, the ejection velocity, and the two missile terminal encounter conditions. A kinematic analysis of the two missile encounter is implemented into a computer code in Matlab™ 6.5 to determine the number the actual impacts and the descriptive characteristics of the impact for different encounter scenarios. Several numerical simulations of single projectile impacts are run using Smoothed Particles Hydrodynamics at predetermined impact parameters. Using the simulation results, a lethality index is developed to assess the damage for each impact condition. An Artificial Neural Network is developed for damage level prediction of impact conditions given by the kinematic analysis and not modeled using Smoothed Particles Hydrodynamics. Finally, the Artificial Neural Network is integrated to the kinematic analysis code to calculate the damage inflicted per encounter scenario. From the analysis of the results, conclusions and guidelines for the KE-rod warheads design are provided. ^

Subject Area

Engineering, Aerospace|Engineering, Mechanical

Recommended Citation

Espino, Luis A, "Computer modeling for damage assessment of KE-rod warheads against ballistic missiles" (2004). ETD Collection for University of Texas, El Paso. AAIEP10780.
http://digitalcommons.utep.edu/dissertations/AAIEP10780

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