Preliminary Study on Quantitative Classification Method of Penetrating Projectile Safety Based on Machine Learning
Under the mechanical impact stimulation condition,such as the bullet impact,fragment impact and martyr explosion,there still exist the problems that the safety response analysis method is imperfect and the quantitative classification method is lacking.To tackle these problems,a machine learning based quantitative classification method for the penetrating projectile under the impact safety response was proposed.With the sim-ulation data of Lee-Tarver charge reactivity and historical experimental data,a mapping relation was established between the charge reactivity and the impact safety response classification for quantitative classification under the impact safety response.In addition,experiments,including the bullet impact,fragment impact and martyr ex-plosion tests,were used to verify the performance of the proposed method.The results show that the simulation results and experimental results are consistent,which verifies the effectiveness of the proposed method and can support the impact safety engineering design for penetrating projectile in the future.
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