Novel Four-Cell Lenticular Honeycomb Deployable Boom with Enhanced Stiffness

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 p...

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Bibliographic Details
Main Authors: Hui Yang, Shuoshuo Fan, Yan Wang, Chuang Shi
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Materials
Subjects:
Online Access:https://www.mdpi.com/1996-1944/15/1/306
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Summary: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 (<i>M<sub>peak</sub></i>) and maximum principal stress (<i>S<sub>max</sub></i>) are established using the BPNN. Fatigue cracks caused by stress concentration are avoided by setting <i>S<sub>max</sub></i> to a specific constraint and the wrapping <i>M<sub>peak</sub></i> and mass of the FLHD boom as objectives. Non-dominated sorting genetic algorithm-II is used for optimization via ISIGHT software.
ISSN:1996-1944