首页|Machine learning optimization strategy of shaped charge liner structure based on jet penetration efficiency

Machine learning optimization strategy of shaped charge liner structure based on jet penetration efficiency

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Shaped charge liner(SCL)has been extensively applied in oil recovery and defense industries.Achieving superior penetration capability through optimizing SCL structures presents a substantial challenge due to intricate rate-dependent processes involving detonation-driven liner collapse,high-speed jet stretching,and penetration.This study introduces an innovative optimization strategy for SCL structures that em-ploys jet penetration efficiency as the primary objective function.The strategy combines experimentally validated finite element method with machine learning(FEM-ML).We propose a novel jet penetration efficiency index derived from enhanced cutoff velocity and shape characteristics of the jet via machine learning.This index effectively evaluates the jet penetration performance.Furthermore,a multi-model fusion based on a machine learning optimization method,called XGBOOST-MFO,is put forward to optimize SCL structure over a large input space.The strategy's feasibility is demonstrated through the optimization of copper SCL implemented via the FEM-ML strategy.Finally,this strategy is extended to optimize the structure of the recently emerging CrMnFeCoNi high-entropy alloy conical liners and hemispherical copper liners.Therefore,the strategy can provide helpful guidance for the engineering design of SCL.

Jet penetration efficiencyShaped charge linerFEM-MLXGBOOSTMFOHigh-entropy alloy

Ziqi Zhao、Tong Li、Donglin Sheng、Jian Chen、Amin Yan、Yan Chen、Haiying Wang、Xiaowei Chen、Lanhong Dai

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State Key Laboratory of Nonlinear Mechanics,Institute of Mechanics,Chinese Academy of Sciences,Beijing 100190,China

School of Future Technology,University of Chinese Academy of Sciences,Beijing 100049 China

School of Engineering Science,University of Chinese Academy of Sciences,Beijing 100049,China

State Key Laboratory of Explosion Science and Technology,Beijing Institute of Technology,Beijing 100081,China

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NSFC Basic Science Center ProgramNSFCNSFCKey Research Program of the Chinese Academy of SciencesNational Key Research and Development Program of Chinaopening project of State Key Laboratory of Explosion Science and Technologyopening project of State Key Laboratory of Explosion Science and Technology

11988102U214120412172367ZDRW-CN-2021-2-32022YFC3320504-02KFJJ21-01KFJJ18-14 M

2024

10.1016/j.dt.2024.04.006

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)：2024.39(9)