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Toward Automated Topology Optimization: Identification of Non-Design Features of CAD Models Using Graph Neural Networks

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Standard

Toward Automated Topology Optimization: Identification of Non-Design Features of CAD Models Using Graph Neural Networks. / Jasinski, Michael; Schöfer, Fabian; Seibel, Arthur.
Industrializing Additive Manufacturing: Proceedings of AMPA2023. ed. / Christoph Klahn; Mirko Meboldt; Julian Ferchow. Cham: Springer International Publishing AG, 2024. p. 267-279 (Springer Tracts in Additive Manufacturing).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Harvard

Jasinski, M, Schöfer, F & Seibel, A 2024, Toward Automated Topology Optimization: Identification of Non-Design Features of CAD Models Using Graph Neural Networks. in C Klahn, M Meboldt & J Ferchow (eds), Industrializing Additive Manufacturing: Proceedings of AMPA2023. Springer Tracts in Additive Manufacturing, Springer International Publishing AG, Cham, pp. 267-279, 3th International Conference on Additive Manufacturing in Products and Applications - AMPA 2023, Zürich, Switzerland, 12.09.23. https://doi.org/10.1007/978-3-031-42983-5_19

APA

Jasinski, M., Schöfer, F., & Seibel, A. (2024). Toward Automated Topology Optimization: Identification of Non-Design Features of CAD Models Using Graph Neural Networks. In C. Klahn, M. Meboldt, & J. Ferchow (Eds.), Industrializing Additive Manufacturing: Proceedings of AMPA2023 (pp. 267-279). (Springer Tracts in Additive Manufacturing). Springer International Publishing AG. https://doi.org/10.1007/978-3-031-42983-5_19

Vancouver

Jasinski M, Schöfer F, Seibel A. Toward Automated Topology Optimization: Identification of Non-Design Features of CAD Models Using Graph Neural Networks. In Klahn C, Meboldt M, Ferchow J, editors, Industrializing Additive Manufacturing: Proceedings of AMPA2023. Cham: Springer International Publishing AG. 2024. p. 267-279. (Springer Tracts in Additive Manufacturing). doi: 10.1007/978-3-031-42983-5_19

Bibtex

@inbook{e5f9cdeb7fb4429184011b7bcdf3e611,
title = "Toward Automated Topology Optimization: Identification of Non-Design Features of CAD Models Using Graph Neural Networks",
abstract = "This paper presents an automated identification of non-design features of CAD models for topology optimization using learning-based segmentation. The CAD files are taken from a large database of industry-relevant components. Based on the geometry and topology of the components, a graph structure is created and processed by a deep neural network. The results show good match with real cases and can be continuously improved by training with additional data.",
keywords = "Engineering, Design Automation, Topology Optimization, Graph Neural Networks",
author = "Michael Jasinski and Fabian Sch{\"o}fer and Arthur Seibel",
note = "{\textcopyright} 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG; 3th International Conference on Additive Manufacturing in Products and Applications - AMPA 2023, AMPA 2023 ; Conference date: 12-09-2023 Through 14-09-2023",
year = "2024",
doi = "10.1007/978-3-031-42983-5_19",
language = "English",
isbn = "978-3-031-42982-8",
series = "Springer Tracts in Additive Manufacturing",
publisher = "Springer International Publishing AG",
pages = "267--279",
editor = "Christoph Klahn and Mirko Meboldt and Julian Ferchow",
booktitle = "Industrializing Additive Manufacturing",
address = "Switzerland",
url = "https://ampa.ethz.ch/",

}

RIS

TY - CHAP

T1 - Toward Automated Topology Optimization

T2 - 3th International Conference on Additive Manufacturing in Products and Applications - AMPA 2023

AU - Jasinski, Michael

AU - Schöfer, Fabian

AU - Seibel, Arthur

N1 - Conference code: 3

PY - 2024

Y1 - 2024

N2 - This paper presents an automated identification of non-design features of CAD models for topology optimization using learning-based segmentation. The CAD files are taken from a large database of industry-relevant components. Based on the geometry and topology of the components, a graph structure is created and processed by a deep neural network. The results show good match with real cases and can be continuously improved by training with additional data.

AB - This paper presents an automated identification of non-design features of CAD models for topology optimization using learning-based segmentation. The CAD files are taken from a large database of industry-relevant components. Based on the geometry and topology of the components, a graph structure is created and processed by a deep neural network. The results show good match with real cases and can be continuously improved by training with additional data.

KW - Engineering

KW - Design Automation

KW - Topology Optimization

KW - Graph Neural Networks

UR - https://www.mendeley.com/catalogue/8f45c01f-21f5-3101-8f2f-0377a38446d7/

U2 - 10.1007/978-3-031-42983-5_19

DO - 10.1007/978-3-031-42983-5_19

M3 - Article in conference proceedings

SN - 978-3-031-42982-8

T3 - Springer Tracts in Additive Manufacturing

SP - 267

EP - 279

BT - Industrializing Additive Manufacturing

A2 - Klahn, Christoph

A2 - Meboldt, Mirko

A2 - Ferchow, Julian

PB - Springer International Publishing AG

CY - Cham

Y2 - 12 September 2023 through 14 September 2023

ER -

Other publications by the same author(s)

Additive Manufacturing of Soft Robots

Weigand, F. & Seibel, A., 2023, Innovative Product Development by Additive Manufacturing 2021. Lachmayer, R., Bode, B. & Kaierle, S. (eds.). Cham: Springer International Publishing AG, p. 101-112 12 p.

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

A generalized α-level decomposition concept for numerical fuzzy calculus

Seibel, A. & Schlattmann, J., 10.2015, Proceedings of the 16th World Congress of the International Fuzzy Systems Association (IFSA) and 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT) 2015. Alonso, J. M., Reformat, M. & Bustince, H. (eds.). Atlantis Press, p. 137-140 4 p. (Advances in Intelligent Systems Research; vol. 89).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Aufbau und Organisation von Entwicklungsprojekten

Schlattmann, J. & Seibel, A., 2023, (Accepted/In press) 2. Aufl. ed. Berlin, Heidelberg: Springer. (Springer Reference Technik)

Research output: Books and anthologies › Book

Automated Design of 3D-Printed Silicone Parts: A Case Study on Hand Rehabilitation Gloves for Stroke Patients

Weigand, F., Föllmer, J. & Seibel, A., 2024, Industrializing Additive Manufacturing: Proceedings of AMPA2023. Klahn, C., Meboldt, M. & Ferchow, J. (eds.). Cham: Springer International Publishing AG, p. 213-224 12 p. (Springer Tracts in Additive Manufacturing).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Case study: The development of a multi-material heat sink by Additive Manufacturing using Aerosint technology

Li, X. & Seibel, A., 2023, In: Metal Additive Manufacturing . 9, 1, p. 183-188 6 p.

Research output: Journal contributions › Journal articles › Research

DOI