数据驱动在内弹道中的应用与展望  

Applications and Prospects of Data-driven Methods in Internal Ballistics

作　　者：张小兵[1] 李湉湉 ZHANG Xiaobing;LI Tiantian(School of Energy and Power Engineering,Nanjing University of Science and Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学能源与动力工程学院,江苏南京210094

出　　处：《弹道学报》2025年第1期1-8,共8页Journal of Ballistics

摘　　要：近年来,数据驱动方法受到广泛关注和研究,数据驱动为内弹道的发展提供了新的研究范式,具有广阔的应用前景和发展潜力。该文总结了近几年数据驱动方法在内弹道领域的相关研究成果,主要介绍了基于数据驱动的内弹道建模技术,以及基于数据驱动的内弹道性能优化方法。该文还讨论了相关研究所面临的挑战,并指出了未来值得进一步研究的方向。In recent years,data-driven methods have received extensive attention and research,and data-driven provides a new research paradigm for the development of internal ballistics,which has a broad application prospect and development potential.This paper summarizes the relevant research results of data-driven methods in the field of internal ballistics in recent years,and mainly introduces the data-driven internal ballistic modelling technique and the data-driven internal ballistic performance optimization method.The paper also discusses the challenges faced by the related research and points out the directions worthy of further research in the future.

关 键 词：内弹道 数据驱动 神经网络 机器学习 

分 类 号：TJ012[兵器科学与技术—兵器发射理论与技术]