基于凝固前沿演变特征的熔铸装药成型工艺参数智能优化  

Intelligent Optimization for Forming Quality of Melt-cast Explosives Based on the Evolution Characteristics of Solidification Front

作　　者：夏焕雄 李康 高丰 刘检华[1,2] 敖晓辉 XIA Huanxiong;LI Kang;GAO Feng;LIU Jianhua;AO Xiaohui(School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China;Tangshan Research Institute,Beijing Institute of Technology,Tangshan 063015,Hebei,China)

机构地区：[1]北京理工大学机械与车辆学院,北京100081 [2]北京理工大学唐山研究院,河北唐山063015

出　　处：《兵工学报》2024年第9期2936-2950,共15页Acta Armamentarii

基　　金：国家自然科学基金项目(52105504)。

摘　　要：熔铸装药成型过程中药浆凝固前沿的轮廓特征与成型后药柱内的缩孔缩松等缺陷具有显著相关性。为改善熔铸装药成型质量,提出凝固前沿轮廓特征度量指标,探究该指标与药柱缩孔缩松体积和最大孔隙率等缺陷的相关性。通过熔铸装药温度场仿真数据集训练装药关键工艺参数与药浆二维瞬态温度场的B样条神经网络模型,进而建立工艺参数与指标参数的代理模型,再基于遗传算法以极大化凝固前沿轮廓特征度量指标为目标,对装药关键工艺参数进行优化。研究结果表明:工艺参数组由初始参数P^(0)=[100,85,0.25,0.25,90,5,0.6]^(T)优化至最佳参数P^(*)=[91.725,94.961,0.498,0.151,100,6,0.595]^(T)后,缩孔缩松体积和最大孔隙率等成型质量参数由19.832 mm^(3)和4.71%降至3.129 mm^(3)和0.66%,实现了熔铸装药成型质量的快速预测和优化;新提出的方法为熔铸装药的工艺优化提供了新思路和新策略,为高性能装药的发展贡献了解决方案,对提高生产效率、降低成本以及确保成型质量一致性具有借鉴意义。Melt-cast explosive processes present a significant correlation among the profile features of solidification front during the molding process and the shrinkage cavity and porosity defects within the grain after molding.To improve the molding quality of melt-cast explosive,an indictor representing the solidification front profile is defined,and the correlations among the indictor and the defects,such as shrinkage cavity/porosity volume and maximum porosity,of the grain,are examined.A surrogate model is developed based on a B-spline neural network model that describes the relationship between the key process parameters and the two-dimensional transient temperature field of melt-cast explosive,and the neural network is trained using a simulated dataset.The key process parameters of melt-cast explosive are then optimized using a genetic algorithm with the aim of maximizing the indicator of solidification front.The results show that the quality parameters of shrinkage cavity/porosity volume and maximum porosity of the grain decrease from 19.832 mm^(3)and 4.71%to 3.129 mm^(3)and 0.66%,respectively,as the process parameters are optimized from P^(0)=[100,85,0.25,0.25,90,5,0.6]^(T)to P^(*)=[91.725,94.961,0.498,0.151,100,6,0.595]^(T),and a fast prediction and optimization for the molding quality of melt-cast explosive are achieved.The proposed method can provide new ideas and strategies for the process optimization of melt-casting explosives and contribute the solutions for the development of high-performance melt-casting explosives,which can be referred to improving the production efficiency,reducing the costs,and ensuring the consistency of molding quality.

关 键 词：熔铸装药 凝固前沿 B样条神经网络 遗传算法 工艺参数优化 

分 类 号：TJ55[兵器科学与技术—军事化学与烟火技术]