Probabilistic modeling of ballistic penetration in reinforced concrete panels.

Studying ballistic impact on reinforced concrete (RC) structures is essential for enhancing the safety and cost‐effectiveness of these structures. The depth of penetration (DOP) and residual velocity (RV) of projectiles are critical design parameters requiring precise quantification to improve the ballistic‐resistant design. Traditional empirical models are available for quantifying these parameters but are deterministic and often yield inaccurate results due to the inherent uncertainties in ballistic impacts. This paper introduces a probabilistic approach to quantify DOP and RV accurately. Bayesian inference models are developed using dimensionless explanatory functions to estimate these parameters in RC panels under hard projectile impacts, accounting for associated uncertainties. Numerical modeling is performed using LS‐Dyna, and the model is validated against experimental data from past studies. Data from refined numerical simulations, along with available experiments from the literature, are utilized to develop the probabilistic models. The findings reveal the significant influence of projectile and concrete properties, as well as the projectile's incidence angle, on DOP and RV. The probabilistic models developed are validated with previous experimental results, demonstrating their reliability and accuracy. Consequently, robust design formulae are proposed for estimating DOP and RV for RC panels under hard projectile impacts, providing a valuable tool for precise impact assessments in engineering applications. [ABSTRACT FROM AUTHOR]