Additive manufacturing-driven topological design considering overhang and connectivity constraints induced by closed cavity

Hexin Jiang, Zhicheng He, Quan Bing Eric Li, Chao Jiang, Dong Mi

Research output: Contribution to journalArticlepeer-review

Abstract

Closed cavity is a common design feature in topology optimization, but quite unfavorable for fabrication, even for highly flexible powder-based additive manufacturing (AM) technology. This is due to the fact that the temporary support material and unmelted powder inside the closed cavity are impossible to remove without damaging the optimized structure, yet would degrade design performance if left in the structure. Thus, this paper presents an AM-driven topological design method to solve the fabrication issues caused by closed cavities, while reducing the effect of manufacturing constraints on design freedom. Specifically, a sequential strategy integrated with self-support topology and connectivity design is developed to tackle the unprintable overhang features and trapped powder problem, rather than directly restricting the generation of closed cavities. Firstly, the closed cavities in the optimized structure are identified by introducing a connected component labeling algorithm, and then the overhang features and connectivity can be evaluated. The self-support topology is achieved by eliminating the overhang elements based on the proposed hybrid modification scheme. On the other hand, the connectivity design is formulated as finding the optimal paths connecting the closed cavities to the structural outside, in which the elements on the paths are deleted as the channels for removing residual powder. To illustrate the effectiveness of the proposed method, multiple 3D numerical examples and manufacturing experiments are conducted. The outcomes consistently demonstrate the advantage of the sequential strategy in achieving printable structures while minimizing any potential performance degradation.Please check and confirm the author names and initials are correct. Also, kindly confirm the details in the metadata are correct.No problem.
Original languageEnglish
Article number118
JournalStructural and Multidisciplinary Optimization
Volume67
DOIs
Publication statusPublished - 6 Jul 2024

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