期刊信息/Journal information
：中国兵工学会
：朱荣桂
：季刊
：2214-9147
：10-1165/TJ
：bgxbywk@tom.com
：010-68963060
：100089
：北京市海淀区车道沟10号（北京2431信箱）
防务技术/Journal Defence TechnologyCSCDCSTPCDSCI
本刊以反映我国兵工战线科学技术的最新成果为主要特色，主要内容为兵器科学技术基础理论研究、试验技术与研究、工程制造技术与研究等。
收录年代
Artificial intelligence-optimized gypsum-based composites for stealth technology:Integrating high strength performance and radar absorption
Sadik Alper Yildizel;Abdurrahim Toktş;Gökhan Kaplan19-35
The dynamic fragmentation of Mott ring containing defects
Liheng He;Haibo Li;Minghe Ju;Qian Li;Xiaofeng Li76-94
Polynitromethyl high-energy materials with a tricyclic furoxan-oxadiazole scaffold:Synthesis,stability,and detonation performance
Qi Xue;Lexing Xue;Panfeng Wu;Fuqiang Bi;Lianjie Zhai;Jiarong Zhang;Kaidi Yang;Junlin Zhang;Bozhou Wang138-148
Ignition and combustion characteristics of aluminum particle in high-temperature turbulent environment
Chengkun Li;Yong Tang;Gongxi Zhou;Rui Ge;Baolu Shi166-175
Crystal structure evolution and thermal stability of high explosive RDX characterized by in situ single crystal X-ray diffraction
Peilin Yang;Liyuan Wei;Jinkun Guo;Chunbo Shi;Yiru Chen;Yu Liu;Xiaoan Wei;Shiliang Huang280-287
A systematic review on advanced surface coating technologies for high-pressure piston pumps
Yifei Dong;Xiner Li;Haishan Teng;Xiaojiang Lu;Xuebo Liu;Zhichao Jiao;Yangyang Ma;Qing Zhou;Ming Yang;Xing Ran;Zhe Wang;Chengjiang Tang;Yulong Li288-309
Interactive effects of process parameters and porosity defect evaluation in thermoplastic composite resistance welding:A model-data-driven AOA-BP neural network framework
Yajie Feng;Juan Xiao;Hongjian Gu;Fang Qi;Zhiyuan Ning;Xigao Jian;Liangliang Shen;Jian Xu325-337
Study on the correlation mechanism between carbon evolution and energy release in oxygen-deficient explosives
Qin Liu;Yingliang Duan;Chao Lv;Jichao Zan;Xinping Long;Yong Han36-50
Distributed auction-based adaptive task assignment and re-assignment for multi-UAV suppressive jamming
Ruiqing Han;Tianxian Zhang;Baozhu Hu;Caipin Li176-187
MmPiFNN:A multi-mode physics-informed fuzzy neural network for passive recognition of surface ships by underwater equipment using ship radiated noise signals
Feng Liu;Zipeng Li;Kunde Yang;Fuhu Chen;Junru Yu243-266