Robust topology optimization for thermoelastic hierarchical structures with hybrid uncertainty

被引:3
|
作者
Jiang, H. X. [1 ]
Wei, B. L. [1 ,2 ]
Zhou, E. L. [1 ]
Wu, Yi [1 ]
Li, X. K. [1 ]
机构
[1] Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Peoples R China
[2] SAIC GM Wuling Automobile Co Ltd, Technol Dev Ctr, Liuzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
BESO; hierarchical structure; hybrid uncertainty; perturbation analysis; robust topology optimization; thermoelastic structure; CONCURRENT DESIGN; INTERVAL; HOMOGENIZATION; COMPOSITES; STIFFNESS; SYSTEMS; FIELDS;
D O I
10.1080/01495739.2021.1999877
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper presents a robust topology optimization (RTO) framework for thermoelastic hierarchical structures with hybrid uncertainty. Firstly, the thermoelastic concurrent optimization model is established and the uncertainties with interval random parameters are integrated into the thermoelastic hierarchical structure. Then, a reliable and cost-effective hybrid uncertainty perturbation analysis method (HUPAM) is derived for a quick estimate of the robust objective function subject to the mechanical and thermal loads. Finally, by calculating the design variables sensitivities of macroscale and microscale, the robust topological design can be generated efficiently. To obtain clear and optimal topologies for both macro- and micro- structures, the bi-directional evolutionary structural optimization (BESO) method is adopted. Some 2D and 3D numerical examples are presented to demonstrate the influences of the hybrid uncertainties on the final designs. The results also show that the proposed method can effectively improve the thermoelastic structural performance when it comes to uncertainties.
引用
收藏
页码:1458 / 1478
页数:21
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