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Acta Aeronautica et Astronautica Sinica ›› 2024, Vol. 45 ›› Issue (5): 529715-529715.doi: 10.7527/S1000-6893.2023.29715

• Articles • Previous Articles     Next Articles

Lightweight design of space trusses considering joint parameterization

Ruitong ZHANG1, Lei WANG2(), Jiajia LIU1,3, Jihong ZHU1   

  1. 1.State IJR Center of Aerospace Design and Additive Manufacturing,Northwestern Polytechnical University,Xi’an 710072,China
    2.China Academy of Launch Vehicle Technology,Beijing 100076,China
    3.Beijing Aerospace Systems Engineering Research Institute,Beijing 100076,China
  • Received:2023-09-10 Revised:2023-10-12 Accepted:2023-10-24 Online:2024-03-15 Published:2023-12-01
  • Contact: Lei WANG E-mail:supersonic0105@163.com
  • Supported by:
    National Key Research and Development Program of China(2022YFB3402200);National Natural Science Foundation of China(92271205)

Abstract:

A layout optimization method of connecting beams considering joints parametric modeling is proposed. The parametric modeling process is based on axis angle and size. The geometric characteristics of the tubular joints are determined by the mutual position and size of the connected beams. The parametric modeling of the joint finite element model is realized by converting the mutual position into the axis angle of the joints and the size into the joint head and branch pipe size. The spatial position of the joint structure can be determined by the axis intersection transformed from the spatial positions of the connected beams. In conclusion, the finite element model of the joint can be embedded, and the finite element model of the whole trusses structure can be established. The Bayesian method based on Gaussian process is used to optimize the layout of the trusses connecting beams, and the manufacturing difficulty is considered and the concrete design scheme is given. Numerical examples show that the optimization method can effectively improve the natural frequency of the structure.

Key words: layout optimization, joint design, trusses, new spacecraft, Bayesian method

CLC Number: