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- Title
Optimal design of variable gradient tube under axial dynamic crushing based on hybrid TSSA–GRNN method.
- Authors
Wang, Weiwei; Dai, Shijuan; Zhao, Wanzhong; Wang, Chunyan
- Abstract
Cross-section shape and thickness distribution are essential to the dynamic crashing behaviors of thin-walled tubes. Therefore, this paper designs a novel functional gradient tube with three variable wall thicknesses along the axial direction. The best regular hexagon (RH) cross-section shape is predetermined by comparing with different cross-section tubes. On this basis, six circular fillets are added to each corner of the RH cross-section tube to reduce its stress concentration. Furthermore, to obtain the surrogate models more accurately and effectively, a hybrid TSSA–GRNN method is proposed by combing the adaptive t-distribution sparrow search algorithm (TSSA) and the generalized regression neural network (GRNN). Multi-objective optimization of the variable gradient tube is conducted by integrating the hybrid TSSA–GRNN method and the non-dominated sorting genetic algorithm (NSGA-II). The results show that the energy absorption, crashworthiness, and lightweight of the optimal variable gradient regular hexagon (VG-RH) tube are better than those obtained by the initial counterpart. The VG-RH tube can be recommended as a good absorber in engineering applications.
- Publication
Structural & Multidisciplinary Optimization, 2022, Vol 65, Issue 1, p1
- ISSN
1615-147X
- Publication type
Article
- DOI
10.1007/s00158-021-03105-9