Effect of fragment dispersion on damage assessment of a directional fragment generator

Abstract

Effective neutralisation of an offensive target missile can be accomplished by a defensive missile system carrying a potential kill mechanism. A directional fragment generator warhead is one of the kill mechanisms for such an application. It projects fragments in a designed beam angle. Few researchers have attempted to quantify fragment dispersion on explosion, which revealed that the fragment projection angle follows a normal distribution with wide range in standard deviation value of 0.75° and 3°. In this paper, an attempt has been made to analyse the importance of knowing the standard deviation value for assessing damage in terms of fragment hit density and kill probability. By altering the standard deviation value between 0 and 3°, the fragment spray distribution for the fragment generator warhead is generated and compared with the distribution that corresponds to a standard deviation value of 0.75°. It is observed that the hit density variation varies by −51% to 40% from the actual. On comparing the effect of standard deviation on kill probability, it is observed that it depends on the proportionate area of vulnerable component in the fragment beam. For the vulnerable area of 0.5 times (50%) of annular fragment beam area, more than or equal to eight fragments can achieve kill probability close to 1. However, for vulnerable area of 0.02 (2%) and 0.1 times (10%) of annular fragment beam area, the kill probability depends on standard deviation value.

Thickness Equivalent Method of 921A and Q235 Steel Plate Based on the Similarity of Projectile Penetration Residual Velocity

“…Projectile penetration is one of the main factors causing target damage [1][2][3]. The damage of the projectile to the structure always take the ballistic limit velocity as the criterions, which is generally obtained by engineering experience [4][5][6].…”

Influencing Factor Analysis of Interception Probability and Classification-Regression Neural Network Based Estimation

“…However, the importance weight assignment of each influencing factor in this method relies on expert experience, and thus it is highly subjective. In [13], a fault tree model was established for the key components of the intercepted target, and the influence of the placement of redundant components on the improvement of survivability is analyzed. However, the killing probability of fragments to a single key component still needs to be obtained by other methods such as simulation.…”