【摘要】 在弹-引信结合状态下，意外刺激引发的引信输出压力对弹药安全性具有至关重要的影响。针对引信烤燃环境下输出压力难以表征的问题，利用应变式压杆传感器获取引信烤燃输出压力，用于引信烤燃试验，建立了引信传爆药烤燃热传导模型、Arrhenius模型和点火反应模型，分析引信烤燃响应特征及输出压力大小。基于BP神经网络反演获取引信传爆药的活化能和指前因子，利用多岛遗传算法确定引信传爆药点火反应方程状态参数。通过Workbench平台使用Fluent与LS-DYNA软件进行联合仿真，对不同升温速率下的引信烤燃响应特性进行分析，实现对引信烤燃从热反应到点火反应的全过程数值模拟预测计算。研究结果表明，加热速率越慢，点火区域越接近装药中心区域，烤燃响应反应越剧烈。更多还原

【Abstract】 To enable comprehensive prediction of typical fuze cook-off processes and address the challenge of quantifying output pressure, an advanced strain-gage pressure bar sensor was utilized for dynamic pressure acquisition during experimental investigations. A comprehensive coupled numerical framework was developed, integrating heat transfer models, Arrhenius reaction kinetics, and ignition response mechanisms, to systematically analyze the cook-off behavior and generate detailed pressure profiles of booster explosives. The kinetic parameters, such as activation energy and pre-exponential factors, were inversely determined through the application of a Back Propagation(BP) neural network. Meanwhile, the state parameters that govern the ignition reaction equation were optimized using a multi-island genetic algorithm. Coupled simulations utilizing ANSYS Fluent and LS-DYNA within the Workbench platform were performed to numerically investigate the cook-off response under different heating rates. This approach enables comprehensive full-process characterization from thermal reaction to ignition. The results indicate that slower heating rates shift the ignition zone toward the central region of the charge, thereby intensifying the severity of the reaction.更多还原