Yang Hui, Fan Shuoshuo, Wang Yan, Shi Chuang
College of Electrical Engineering and Automation, Anhui University, Hefei 230601, China.
College of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, China.
Materials (Basel). 2022 Jan 1;15(1):306. doi: 10.3390/ma15010306.
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 () and maximum principal stress () are established using the BPNN. Fatigue cracks caused by stress concentration are avoided by setting to a specific constraint and the wrapping and mass of the FLHD boom as objectives. Non-dominated sorting genetic algorithm-II is used for optimization via ISIGHT software.
复合薄壁梁可以通过释放储存的应变能轻松折叠并自行展开。因此，这种梁可用于展开天线、太阳帆和光学望远镜。在本工作中，提出了一种新型四单元双凸透镜蜂窝可展开（FLHD）梁，并对相关参数进行了优化。使用非线性显式动力学分析对纯弯曲载荷下的FLHD梁进行卷绕动力学分析，卷绕模拟分为三个连续步骤，即展平步骤、保持步骤和轮毂卷绕步骤。基于反向传播神经网络（BPNN）开发了一种FLHD梁卷绕的优化设计方法。应用全因子实验设计方法创建36个样本点，并使用BPNN建立卷绕峰值弯矩（）和最大主应力（）的代理模型。通过将设置为特定约束条件，并将FLHD梁的包裹物和质量作为目标，避免了应力集中引起的疲劳裂纹。通过ISIGHT软件使用非支配排序遗传算法-II进行优化。
