Machine Learning-based Design of Software to Calculate the Fragmentation Power of the Combat Section of an Explosive Killing Shell

The fragmentation power is an important parameter to characterize the performance of a combatant. At present, the fragmentation power is mainly calculated by empirical formulae or simulation analysis, which has problems such as large calculation volume, slow calculation speed and low efficiency. In this paper, a machine learning-based method for calculating the lethality of explosives is proposed. On the basis of analyzing the structure and material of explosive kill combat section, combining theoretical calculation data, simulation data and experimental data, the training model of machine learning is constructed, and by introducing BP neural network algorithm, the rapid calculation of debris dynamic field characterization parameters is finally realized.