首页|Research on simulation of gun muzzle flow field empowered by artificial intelligence

Research on simulation of gun muzzle flow field empowered by artificial intelligence

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Artificial intelligence technology is introduced into the simulation of muzzle flow field to improve its simulation efficiency in this paper.A data-physical fusion driven framework is proposed.First,the known flow field data is used to initialize the model parameters,so that the parameters to be trained are close to the optimal value.Then physical prior knowledge is introduced into the training process so that the prediction results not only meet the known flow field information but also meet the physical conser-vation laws.Through two examples,it is proved that the model under the fusion driven framework can solve the strongly nonlinear flow field problems,and has stronger generalization and expansion.The proposed model is used to solve a muzzle flow field,and the safety clearance behind the barrel side is divided.It is pointed out that the shape of the safety clearance under different launch speeds is roughly the same,and the pressure disturbance in the area within 9.2 m behind the muzzle section exceeds the safety threshold,which is a dangerous area.Comparison with the CFD results shows that the calculation efficiency of the proposed model is greatly improved under the condition of the same calculation ac-curacy.The proposed model can quickly and accurately simulate the muzzle flow field under various launch conditions.

Muzzle flow fieldArtificial intelligenceDeep learningData-physical fusion drivenShock wave

Mengdi Zhou、Linfang Qian、Congyong Cao、Guangsong Chen、Jin Kong、Ming-hao Tong

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School of Mechanical Engineering,Nanjing University of Science and Technology,Nanjing,210094,China

Northwest Institute of Mechanical and Electrical Engineering,Xianyang,712099,Shaanxi,China

School of Automation,Nanjing University of Science and Technology,Nanjing,210094,China

Natural Science Foundation of Jiangsu Province of ChinaNational Natural Science Foundation of China

BK20210347U2141246

2024

防务技术
中国兵工学会

防务技术

CSTPCD
影响因子:0.358
ISSN:2214-9147
年,卷(期):2024.32(2)
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