Optimization and experimental research on treelike joints based on generative design and powder bed fusion

Abstract

Optimization and intelligent construction are of particular interest and important to improve the traditional design and manufacturing methods of cast steel joints. The optimal design, intelligent construction, and experimental research of treelike joints are conducted is this study based on generative design and laser power bed fusion (L-PBF) technology. First, the principle of generative design is comprehensively discussed in accordance of the Audze space-filling criteria. This method is applied to the optimal design of the treelike cast steel joint for Jinming Campus Museum of Henan University. Second, static behaviors of the generative design joints are compared with those of other joints obtained via parametric design through ANSYS version 2022R1 (64-bit) software. Finally, instead of traditional casting, all joints are produced using the L-PBF technology, and the manufactured 316L stainless steel joints are subjected to experimental research and finite element analysis. Results showed the minimum mass, optimal static behaviors, and evenly distributed stress of the generative design joint, thereby indicating that the generative design can effectively optimize treelike cast steel joints. The failure mode of 316Lstainless steel joints obtained via the L-PBF technology is similar to that of traditional cast steel joints but with higher yield load and ultimate bearing capacity. Therefore, employing the generative design and L-PBF technology in the optimization and intelligent construction of cast steel joints is effective and feasible.