Investigation of the potential of topology optimization in additive manufacturing using the example of components subject to bending stress

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Jantos, D.R.; Röttger, A.; Junker, P.: Investigation of the potential of topology optimization in additive manufacturing using the example of components subject to bending stress. In: Materials Science and Engineering Technology = Materialwissenschaft und Werkstofftechnik 53 (2022), Nr. 10, S. 1298-1310. DOI: https://doi.org/10.1002/mawe.202200013

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/14008

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Sum total of downloads: 47




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Abstract: 
In this application-oriented work, we examine the performance of topology-optimized structures as compared to the reference I-beam. We make use of the thermodynamic topology optimization based on a linear elastic compliance minimization, i. e. minimization of the elastic strain energy of the whole structure. We investigate, how the optimization of the rather theoretical strain energy influences the efficiency of more practical measurements, i. e. the force-displacement response at the loading points and the maximum tolerable force. For this purpose, starting from a cuboid design space with the boundary conditions of a 3-point and 4-point bending stress, the geometry with constant volume was optimized. The topology-optimized bending beams were subsequently produced by stereolithography and mechanically tested with respect to the previously defined boundary conditions. In order to avoid a falsification of results due to internal sample defects, all samples were previously examined with the aid of computer tomography with regard to the defects in the volume. As a general result, the topology-optimized bending beams can bear a higher load in the experiment, which shows the usefulness of the coupling of additive manufacturing and topology optimization methods without any special constraints or enhancements regarding the manufacturing process within the optimization.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2022
Appears in Collections:Fakultät für Maschinenbau

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1 image of flag of Germany Germany 23 48.94%
2 image of flag of United States United States 13 27.66%
3 image of flag of No geo information available No geo information available 2 4.26%
4 image of flag of Indonesia Indonesia 2 4.26%
5 image of flag of United Kingdom United Kingdom 2 4.26%
6 image of flag of Portugal Portugal 1 2.13%
7 image of flag of Netherlands Netherlands 1 2.13%
8 image of flag of India India 1 2.13%
9 image of flag of Europe Europe 1 2.13%
10 image of flag of Czech Republic Czech Republic 1 2.13%

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