Abstract
Objectives Stiffened panels are widely used as thin-walled load-bearing components, and the design space can be significantly increased when the stiffened path is curvilinear. Due to the functional requirements of structures, there are a large number of thin-walled structures with cutouts in the structural design of aviation, aerospace, shipbuilding and other fields, which leads to a significant reduction in the bearing capacity of the structure. Although the curved stiffening method has great potential in improving the load-bearing performance of the open structure, the sharp increase of design variables becomes a challenge to structural optimization. Methods The data-driven deep learning method is used to optimize the design of hierarchical stiffened thin-walled structures with cutout reinforced by curvilinear stiffeners. For the structure with cutouts, the hierarchical curvilinearly stiffened method is designed, and the image representation method of structural parameters is proposed. The deep learning network model for structural response feature learning is established to realize the structural optimization design under data-driven. Results The results show that compared with the classical surrogate models constructed by structural numerical parameters, the prediction accuracy of the proposed structural feature learning model based on image recognition is improved by about twice. In the optimization design of the structure based on the learning model, the bearing capacity of hierarchical orthogonal stiffened structure increased by 10.78%, and the bearing capacity of hierarchical curvilinearly stiffened structure increased by 18.19%. Conclusions The results show that the deep learning based structural optimization method is more effective for the hierarchical stiffened structure with large number of design variables and dynamic changes in the number of design variables. Compared with the traditional straightly stiffened panels, the curvilinearly stiffened panel is more effective to strengthen the bearing capacity of thin-walled structures with cutouts.
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