Subdivision surface mid-surface reconstruction of topology optimization results and thin-walled shapes using surface skeletons

Denk M, Rother K, Paetzold K (2021)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2021

Publisher: Cambridge University Press

Book Volume: 1

Pages Range: 2771-2780

Conference Proceedings Title: Proceedings of the Design Society

Event location: Gothenburg SE

DOI: 10.1017/pds.2021.538

Open Access Link: https://doi.org/10.1017/pds.2021.538

Abstract

Polygon meshes and particularly triangulated meshes can be used to describe the shape of different types of geometry such as bicycles, bridges, or runways. In engineering, such polygon meshes can occur as finite element meshes, resulting from topology optimization or laser scanning. This article presents an automated parameterization of polygon meshes into a parametric representation using subdivision surfaces, especially in topology optimization. Therefore, we perform surface skeletonization on a volumetric grid supported by the Euclidian distance transformation and topology preserving and shape-preserving criterion. Based on that surface skeleton, an automated conversation into a Subdivision Surface Control grid is established. The final mid-surface-like parametrization is quite flexible and can be changed by variating the control gird or the local thickness.

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APA:

Denk, M., Rother, K., & Paetzold, K. (2021). Subdivision surface mid-surface reconstruction of topology optimization results and thin-walled shapes using surface skeletons. In Cambridge University Press (Eds.), Proceedings of the Design Society (pp. 2771-2780). Gothenburg, SE: Cambridge University Press.

MLA:

Denk, Martin, Klemens Rother, and Kristin Paetzold. "Subdivision surface mid-surface reconstruction of topology optimization results and thin-walled shapes using surface skeletons." Proceedings of the 23rd International Conference on Engineering Design, ICED 2021, Gothenburg Ed. Cambridge University Press, Cambridge University Press, 2021. 2771-2780.

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