Artificial Neural Network Study: Protective Textiles for Defense Applications

Kevlar is a well-known component of bulletproof vests and bulletproof facemasks. Helmets reinforced with Kevlar fabric offers 25% to 40% better fragmentation resistance than comparable steel helmets. An artificial neural network study on properties of Kevlar 29 fabric is reported in this paper. The objective is to compare physical models and artificial neural network models, since the latter have proved to be a powerful tool to model predictive non-linearities and complexities. Fragment simulation projectile data for ballistic penetration measurements at 244 m/s was used to demonstrate the modeling aspects of artificial neural networks. Predicted values gave excellent correlation with experimental values of penetration depth and dissipated energy. The results prove the superiority of neural network models used in this study over theoretical models