Novel Four-Cell Lenticular Honeycomb Deployable Boom with Enhanced Stiffness

被引:13
|
作者
Yang, Hui [1 ]
Fan, Shuoshuo [1 ]
Wang, Yan [2 ]
Shi, Chuang [3 ]
机构
[1] Anhui Univ, Coll Elect Engn & Automat, Hefei 230601, Peoples R China
[2] Yanshan Univ, Coll Mech Engn, Qinhuangdao 066004, Hebei, Peoples R China
[3] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin 150001, Peoples R China
基金
中国国家自然科学基金;
关键词
deployable structures; four-cell lenticular honeycomb boom; coiling dynamics; optimization; composite material; DYNAMIC-ANALYSIS; DESIGN; OPTIMIZATION;
D O I
10.3390/ma15010306
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Composite thin-walled booms can easily be folded and self-deployed by releasing stored strain energy. Thus, such booms can be used to deploy antennas, solar sails, and optical telescopes. In the present work, a new four-cell lenticular honeycomb deployable (FLHD) boom is proposed, and the relevant parameters are optimized. Coiling dynamics analysis of the FLHD boom under a pure bending load is performed using nonlinear explicit dynamics analysis, and the coiling simulation is divided into three consecutive steps, namely, the flattening step, the holding step, and the hub coiling step. An optimal design method for the coiling of the FLHD boom is developed based on a back propagation neural network (BPNN). A full factorial design of the experimental method is applied to create 36 sample points, and surrogate models of the coiling peak moment (M-peak) and maximum principal stress (S-max) are established using the BPNN. Fatigue cracks caused by stress concentration are avoided by setting S-max to a specific constraint and the wrapping M-peak and mass of the FLHD boom as objectives. Non-dominated sorting genetic algorithm-II is used for optimization via ISIGHT software.
引用
收藏
页数:14
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