Infill Optimization for Additive Manufacturing-Approaching Bone-Like Porous Structures
Porous structures such as trabecular bone are widely seen in nature. These structures are lightweight and exhibit strong mechanical properties. In this paper, we present a method to generate bone-like porous structures as lightweight infill for additive manufacturing. Our method builds upon and exte...
Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 24(2018), 2 vom: 04. Feb., Seite 1127-1140 |
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Weitere Verfasser: | , , |
Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2018
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Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics |
Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
Zusammenfassung: | Porous structures such as trabecular bone are widely seen in nature. These structures are lightweight and exhibit strong mechanical properties. In this paper, we present a method to generate bone-like porous structures as lightweight infill for additive manufacturing. Our method builds upon and extends voxel-wise topology optimization. In particular, for the purpose of generating sparse yet stable structures distributed in the interior of a given shape, we propose upper bounds on the localized material volume in the proximity of each voxel in the design domain. We then aggregate the local per-voxel constraints by their p-norm into an equivalent global constraint, in order to facilitate an efficient optimization process. Implemented on a high-resolution topology optimization framework, our results demonstrate mechanically optimized, detailed porous structures which mimic those found in nature. We further show variants of the optimized structures subject to different design specifications, and we analyze the optimality and robustness of the obtained structures |
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Beschreibung: | Date Completed 28.01.2019 Date Revised 28.01.2019 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
ISSN: | 1941-0506 |
DOI: | 10.1109/TVCG.2017.2655523 |