COMPOSITES SCIENCE AND ENGINEERING ›› 2024, Vol. 0 ›› Issue (2): 102-108.DOI: 10.19936/j.cnki.2096-8000.20240228.015

• APPLICATION RESEARCH • Previous Articles     Next Articles

Multi-objective optimization design of energy absorption characteristics of composite origami tubes

ZHOU Zhengyan1, LI Xiang1*, ZHU Lu2, SUN Yepei1   

  1. 1. School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China;
    2. Shanghai Institute of Aerospace Systems Engineering, Shanghai 201108, China
  • Received:2023-01-13 Online:2024-02-28 Published:2024-04-22

Abstract: Thin-walled structures are widely used in energy-absorbing devices. Traditional straight-tube carbon fiber resin-reinforced composite (CFRP) thin-walled structures always exhibit problems of high peak force and large fluctuations in force-displacement curves when they are crushed. However, the energy-absorbing device must ensure gradual and controlled energy absorption and avoid possible excessive peak forces. Therefore, the CFRP thin-walled tube structure needs to be further improved as an energy-absorbing device. Compared with the traditional straight tube structure, the CFRP origami tube has better energy absorption characteristics due to its unique structural form. The energy absorption characteristics of origami tubes under axial load were studied through numerical simulation, and the nonlinear mapping relationship between the energy absorption characteristics indexes of the tubes and their geometric parameters was obtained. A multi-objective structural optimization design model considering maximization of total energy absorption and minimization of peak force was established, and the NSGA-Ⅱ genetic algorithm was used to solve the problem and the results were analyzed. The optimized design of the origami tube increases the total energy absorption by 144.9% and reduces the peak force by 46.5% while maintaining the same mass, which is significantly improved compared with the original structure.

Key words: composite materials, origami tube, energy absorption, surrogate model, multi-objective optimization

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