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空爆冲击波场计算模型研究现状与展望

徐豫新1,2,3*(), 张浩宇1   

  1. (1. 北京理工大学 爆炸科学与安全防护全国重点实验室, 北京100081; 2.北京理工大学 唐山研究院,河北 唐山 063000;3.北京理工大学重庆创新中心, 重庆 401120)
  • 收稿日期:2025-04-14 修回日期:2025-07-29
  • 通讯作者: *邮箱:xuyuxin@bit.edu.cn

Research Status and Prospect of Calculation Model of Explosive Air Explosion Shock Wave Field

XU Yuxin1,2,3*(), ZHANG Haoyu1   

  1. (1. State Key Lab of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing,100081, China; 2. Tangshan Research Institute, Beijing Institute of Technology, Tangshan 063000, Hebei, China; 3. Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401120, China)
  • Received:2025-04-14 Revised:2025-07-29

摘要: 归纳炸药装药空中爆炸冲击波场计算模型的现有研究成果,深入分析现有计算模型的适用范围与不足,展望空爆冲击波场计算模型未来发展趋势,为城市、山地等复杂环境下二代、三代高能炸药爆炸冲击波场快速准确计算提供新途径。针对高能炸药空中爆炸冲击波传播规律,归纳装药形状、地形环境、大气环境等对冲击波参量影响规律研究现状与成果;分析了已有相关理论模型、经验模型、机器学习模型的适用范围、优缺点以及研究进展;探讨了神经网络等人工智能算法在爆炸冲击波场预估中的应用前景,展望了该方向后续主要发展途径;研究成果可为高能炸药空气中爆炸威力场预估及毁伤技术的发展提供支撑,也可为后续相关技术的研究提供参考。

关键词: 爆炸冲击波, 计算模型, 机器学习, 含铝炸药, 装药形状, 地形环境

Abstract: This paper summarizes the existing research achievements of the computational models for the shock wave field of air-burst explosive charges, deeply analyzes the applicable scope and shortcomings of the existing computational models, and looks forward to the future development trends of the air-burst shock wave field computational models. It provides a new approach for the rapid and accurate calculation of the shock wave field of second and third-generation high-energy explosives in complex environments such as urban and mountainous areas. Focusing on the propagation law of shock waves from high-energy explosives in the air, it summarizes the current research status and achievements on the influence laws of charge shape, terrain environment, and atmospheric environment on shock wave parameters. It also analyzes the applicable scope, advantages and disadvantages, and research progress of existing theoretical models, empirical models, and machine learning models. It discusses the application prospects of artificial intelligence algorithms such as neural networks in the prediction of explosive shock wave fields and looks forward to the main development directions in this field. This can provide support for the prediction of the power field of high-energy explosives in the air and the development of damage technology, and also offer references for subsequent related research.

Key words: explosion shock wave, calculation model, machine learning, aluminized explosives, charge shape, terrain environment

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