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Structural and Multidisciplinary Optimization

, Volume 59, Issue 4, pp 1371–1383 | Cite as

Wrapping dynamic analysis and optimization of deployable composite triangular rollable and collapsible booms

  • Hui Yang
  • Lian Liu
  • Hongwei GuoEmail author
  • Fengshuai Lu
  • Yongbin Liu
Industrial Application
  • 88 Downloads

Abstract

Deployable composite triangle rollable and collapsible (TRAC) booms can be flattened and wrapped elastically, and then can be self-deployed by releasing stored strain energy around a hub. Composite ultra-thin TRAC booms have a higher potential application value for driving larger membrane antenna and solar sails. Wrapping and fully deploying status modal analysis are performed using nonlinear explicit dynamics analysis. The wrapping simulation is divided into three consecutive steps: flattening, end clamping, and wrapping around the hub. An optimal design method for the wrapping of the TRAC boom is presented based on the response surface theory. Then, sample points are created based on a three-level full factorial design of the experimental method. Surrogate models of the wrapping peak moment, maximum stress, and fully deploying fundamental frequency are constructed using quadratic polynomials. To enhance using times, the maximum stress is set as a constraint. Considering the high deploying stability and sufficient driving moment, the wrapping peak moment and deploying fundamental frequency are set as objectives to obtain the optimal design. Furthermore, a parametric study of the geometric parameters is performed to determine the effect on the wrapping behaviors and fully deploying stability.

Keywords

Wrapping Thin-walled composites TRAC boom Optimization FEM analysis 

Notes

Acknowledgements

The authors are grateful to Ph.D. student Sicong Wang for making available the server for the numerical analysis.

Funding information

This study was supported by the Joint Funds of the National Natural Science Foundation of China (Grant No. U1637207), National Natural Science Foundation of China (Grant No. 51605001), Key Funds of the National Natural Science Foundation of China (Grant No. 51835002), and Anhui University Research Foundation for Doctor (Grant No. J01003222).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Hui Yang
    • 1
  • Lian Liu
    • 1
  • Hongwei Guo
    • 2
    Email author
  • Fengshuai Lu
    • 1
  • Yongbin Liu
    • 1
  1. 1.College of Electrical Engineering and AutomationAnhui UniversityHefeiChina
  2. 2.China State Key Laboratory of Robotics and SystemHarbin Institute of TechnologyHarbinChina

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