Topology optimization for additive manufacturing of CFRP structures

Xu, Y; Feng, Z; Gao, Y; Wu, C; Fang, J; Sun, G; Qiu, N; Steven, GP; Li, Q

Topology optimization for additive manufacturing of CFRP structures

Xu, Y Feng, Z Gao, Y Wu, C Fang, J

Sun, G Qiu, N Steven, GP Li, Q

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Publisher:: PERGAMON-ELSEVIER SCIENCE LTD
Publication Type:: Journal Article
Citation:: International Journal of Mechanical Sciences, 2024, 269
Issue Date:: 2024-05-01

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Field	Value	Language
dc.contributor.author	Xu, Y
dc.contributor.author	Feng, Z
dc.contributor.author	Gao, Y
dc.contributor.author	Wu, C
dc.contributor.author	Fang, J https://orcid.org/0000-0003-0119-6108
dc.contributor.author	Sun, G
dc.contributor.author	Qiu, N
dc.contributor.author	Steven, GP
dc.contributor.author	Li, Q
dc.date.accessioned	2025-01-06T04:28:48Z
dc.date.available	2025-01-06T04:28:48Z
dc.date.issued	2024-05-01
dc.identifier.citation	International Journal of Mechanical Sciences, 2024, 269
dc.identifier.issn	0020-7403
dc.identifier.issn	1879-2162
dc.identifier.uri	http://hdl.handle.net/10453/183025
dc.description.abstract	Combining design optimization and additive manufacturing (AM) enables the full exploitation of the potential for heightening the performance of carbon fiber reinforced plastic (CFRP) structures. This study simultaneously conducts topology optimization and fiber path design by employing the radial basis function (RBF) based level set function (LSF). Fiber paths are determined instinctively for the inherent advantages of the LSF, and fiber orientations are parameterized accordingly. Manufacturing drawbacks such as gaps and overlaps can be avoided by introducing a fast-marching method. To verify the effectiveness of the optimization method, three groups of optimized and empirical designs are fabricated by the AM technique, respectively, and the experimental tests are further carried out. Finite element (FE) models are also reconstructed based on the printing schemes, and then the FE simulation is validated by the experimental tests. With the proposed optimization method, stiffnesses for all three groups of the optimal samples are significantly improved compared with the empirical counterparts. The FE modeling technique is capable of reproducing the experimental results. This study paves a new way to develop an integrated framework of optimization, additive manufacturing, experimentation, and validation to deliver high-performance CFRP structures.
dc.language	English
dc.publisher	PERGAMON-ELSEVIER SCIENCE LTD
dc.relation	http://purl.org/au-research/grants/arc/DP190103752
dc.relation.ispartof	International Journal of Mechanical Sciences
dc.relation.isbasedon	10.1016/j.ijmecsci.2024.108967
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0905 Civil Engineering, 0910 Manufacturing Engineering, 0913 Mechanical Engineering
dc.subject.classification	Mechanical Engineering & Transports
dc.subject.classification	40 Engineering
dc.title	Topology optimization for additive manufacturing of CFRP structures
dc.type	Journal Article
utslib.citation.volume	269
utslib.for	0905 Civil Engineering
utslib.for	0910 Manufacturing Engineering
utslib.for	0913 Mechanical Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
utslib.copyright.status	in_progress	*
dc.date.updated	2025-01-06T04:28:46Z
pubs.publication-status	Published
pubs.volume	269

Abstract:

Combining design optimization and additive manufacturing (AM) enables the full exploitation of the potential for heightening the performance of carbon fiber reinforced plastic (CFRP) structures. This study simultaneously conducts topology optimization and fiber path design by employing the radial basis function (RBF) based level set function (LSF). Fiber paths are determined instinctively for the inherent advantages of the LSF, and fiber orientations are parameterized accordingly. Manufacturing drawbacks such as gaps and overlaps can be avoided by introducing a fast-marching method. To verify the effectiveness of the optimization method, three groups of optimized and empirical designs are fabricated by the AM technique, respectively, and the experimental tests are further carried out. Finite element (FE) models are also reconstructed based on the printing schemes, and then the FE simulation is validated by the experimental tests. With the proposed optimization method, stiffnesses for all three groups of the optimal samples are significantly improved compared with the empirical counterparts. The FE modeling technique is capable of reproducing the experimental results. This study paves a new way to develop an integrated framework of optimization, additive manufacturing, experimentation, and validation to deliver high-performance CFRP structures.

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http://hdl.handle.net/10453/183025