TY - JOUR

T1 - Armor's ballistic resistance simulation using stochastic process modeling

AU - Tahenti, Beya

AU - Coghe, Frederik

AU - Nasri, Rachid

AU - Pirlot, Marc

N1 - Publisher Copyright:
© 2017 Elsevier Ltd

PY - 2017/4/1

Y1 - 2017/4/1

N2 - For many years, ballistic performance evaluation of protection structures makes use of the estimation of the ballistic limit velocity V50, the projectile impact velocity at which there is a 50 percent probability of perforation of the assessed structure. In recent years, enhancements to risk assessment required the estimation of the entire curve of the probability of perforation. Extreme values of complete perforation (partial penetration) at low (high) impact velocity are rare events of the studied system with binary response experiments. Existing methods have comparable accuracy in estimating the V50 velocity, and use the normality assumption to estimate any percentile of interest Vx. This contribution proposes to model the projectile evolution into the target as a diffusion process using the Brownian motion process. A Chi-square and Kolmogorov–Smirnov goodness of fit test is applied to estimate the drift and diffusion coefficients of the developed stochastic differential equation based on the Monte Carlo simulated sample and the experimental one. Under the assumption of constant drift and diffusion coefficients, the estimated value of the projectile deceleration matches its analytically computed value depending on the system parameters and configuration. The established model presents a comparable predictive ability, as existing methods, of the V50 with the advantage of defining a bounded velocity interval in which the perforation probability varies from zero to one in accordance with the physical behavior of the system. Furthermore, the fitted model provides the probability perforation of the structure at any impact velocity with an estimate of its variability.

AB - For many years, ballistic performance evaluation of protection structures makes use of the estimation of the ballistic limit velocity V50, the projectile impact velocity at which there is a 50 percent probability of perforation of the assessed structure. In recent years, enhancements to risk assessment required the estimation of the entire curve of the probability of perforation. Extreme values of complete perforation (partial penetration) at low (high) impact velocity are rare events of the studied system with binary response experiments. Existing methods have comparable accuracy in estimating the V50 velocity, and use the normality assumption to estimate any percentile of interest Vx. This contribution proposes to model the projectile evolution into the target as a diffusion process using the Brownian motion process. A Chi-square and Kolmogorov–Smirnov goodness of fit test is applied to estimate the drift and diffusion coefficients of the developed stochastic differential equation based on the Monte Carlo simulated sample and the experimental one. Under the assumption of constant drift and diffusion coefficients, the estimated value of the projectile deceleration matches its analytically computed value depending on the system parameters and configuration. The established model presents a comparable predictive ability, as existing methods, of the V50 with the advantage of defining a bounded velocity interval in which the perforation probability varies from zero to one in accordance with the physical behavior of the system. Furthermore, the fitted model provides the probability perforation of the structure at any impact velocity with an estimate of its variability.

KW - Ballistic resistance

KW - Penetration process

KW - Perforation probability

KW - Projectile impact

KW - Stochastic modeling

KW - V

UR - http://www.scopus.com/inward/record.url?scp=85007099107&partnerID=8YFLogxK

U2 - 10.1016/j.ijimpeng.2016.12.009

DO - 10.1016/j.ijimpeng.2016.12.009

M3 - Article

AN - SCOPUS:85007099107

SN - 0734-743X

VL - 102

SP - 140

EP - 146

JO - International Journal of Impact Engineering

JF - International Journal of Impact Engineering

ER -