静力学
驾驶舱
射弹
计算
模拟
航程(航空)
工程类
结构工程
边值问题
优化设计
航空航天工程
汽车工程
机械工程
计算机科学
材料科学
数学
物理
经典力学
机器学习
数学分析
冶金
算法
作者
Bo Cui,Yongjie Zhang,Hao Dong,Zhiwen Li,Tao Jin,Haitao Wang
标识
DOI:10.1080/13588265.2023.2230645
摘要
AbstractAbstractCockpit bulletproof floor and subfloor of the helicopter were modelled in a simplified manner, and the display dynamics analysis was combined with the statics analysis to investigate the responses of the composite bulletproof floor and determine its boundary support reaction force. Numerical simulations of projectiles with various velocities and incidence angles impacting on the target plate were investigated. The floor support reaction force was loaded on the subfloor, and the response of the subfloor under the impact of projectile was studied indirectly using the statics analysis tool. Moreover, the optimisation strategy was conducted based on the above strategy. The design variables of the subfloor were analysed using the defined correlation, the mass condition, the strength condition and the correlation ratio equations to reasonably reduce the range of design variables. Different optimisation strategies were adopted to enhance the ballistic performance of the subfloor. A combined patch-MOGA-AMO optimisation strategy was developed to achieve high-efficiency and high-quality optimisation, which had a proper computation speed and achieved suitable optimisation results.Keywords: Bulletproof floorsubflooroptimization methodMOGAhelicopter Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China (Grant Nos. 11972301, 11201375, 11972300), the Natural Science Foundation of Shaanxi Province (Grant No. 2018JQ1071), State Key Laboratory of Structural Analysis for Industrial Equipment (China) (Grant No. GZ18107) and the Fundamental Research Funds for the Central Universities of China (Grant No. G2019KY05203).
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