数据驱动的自然破片飞散角计算模型

A DATA-DRIVEN COMPUTATIONAL MODEL FOR NATURAL FRAGMENT SCATTERING ANGLES

  • 摘要: 为了建立适用性更广、准确性更高的破片飞散角计算公式,该文结合试验和数值模拟结果,构建了破片飞散角空间分布参数的人工神经网络(ANN)预测模型,进而建立了空间分布参数和破片飞散角沿壳体轴线方向分布的计算公式。研究结果表明:对于通常形式的自然破片战斗部,破片飞散的角度区间为−20°~15°,飞散角(绝对值)从起爆端至非起爆端呈现先减小后增大的趋势。破片飞散角随质量比的增大而增大,随端盖厚度比的增大而减小,破片向下飞散的比例随长径比的减小显著增大。该文建立的人工神经网络模型可以有效预测破片飞散角的空间分布参数,建立的破片飞散角计算公式具有良好的适用性和准确性。

     

    Abstract: To develop a more widely applicable and accurate formula for calculating fragment scattering angles, this study combines experimental and numerical simulation results to construct an artificial neural network (ANN) prediction model for the spatial distribution parameters of fragment scattering angles. Subsequently, a calculation formula for the spatial distribution parameters and the distribution of the fragment scattering angle along the casing axis is established. The results indicate that for typical cased charges, the fragment scattering angle ranges from −20°~15°, and its absolute value exhibits a trend of initially decreasing and then increasing from the detonation end to the non- detonation end. The fragment scattering angle increases with the mass ratio and decreases with the increase in end cap thickness ratio. The proportion of fragments scattering downward increases with the decrease of aspect ratios. The ANN model effectively predicts the spatial distribution parameters of fragment scattering angles, and the established calculation formula for fragment scattering angles has good applicability and accuracy.

     

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