Zhang, K., O Brádaigh, C. orcid.org/0000-0002-8048-4222 and Yang, D. (2025) High-performance curved sections in 3D printed continuous carbon fibre reinforced thermoplastic composites using aligned fibre deposition. Composites Science and Technology. 111460. ISSN: 0266-3538
Abstract
This paper presents high-performance curved sections in 3D printed continuous carbon fibre reinforced thermoplastic composites using an aligned fibre deposition (AFD) method on a 6-axis robotic arm. 3D printed curved composite beams using both AFD and conventional methods are mechanically tested under four-point bending and scanned by X-ray computed microtomography (μCT) to characterise the fibre distribution and develop image-based finite element models. Compared to conventional printing method using a commercial nozzle, the proposed AFD method significantly improves the fibre alignment and reduces void content in the printed composites, and the curved beam strength is calculated as 204.2 N and 224.5 N for the cases of 7 mm and 15 mm radius of curvature, achieving an improvement of 34.0% and 45.3%, respectively. The modelling produces excellently matched stiffness with the experimental measurement, providing useful insights into the stress and strain distributions. The combination of experimental data and modelling results shows that the alignment of fibres in the curved composite beams plays a key role in improving mechanical performance and determining the final failure mode.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2025 The Authors. Published by Elsevier Ltd. This is an open access article distributed under the terms of the Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | 3D printing; continuous carbon fibre reinforced thermoplastic; fibre misalignment; curved beam; image-based modelling |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) |
| Date Deposited: | 27 Nov 2025 14:12 |
| Last Modified: | 27 Nov 2025 14:12 |
| Status: | Published online |
| Publisher: | Elsevier |
| Refereed: | Yes |
| Identification Number: | 10.1016/j.compscitech.2025.111460 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:234868 |
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