Additive manufacturing of flexible strain sensors based on smart composites for structural health monitoring with high accuracy and fidelity

Ahmed, S, Bodaghi, M ORCID: https://orcid.org/0000-0002-0707-944X, Nauman, S and Muhammad Khan, Z, 2023. Additive manufacturing of flexible strain sensors based on smart composites for structural health monitoring with high accuracy and fidelity. Advanced Engineering Materials, 25 (22): 2300763. ISSN 1438-1656

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Abstract

This research introduces a novel flexible spherical carbon nanoparticle-based polyurethane conductive ink, which is employed to fabricate strain sensors by a lab-developed direct ink writing/3D printing system. Rheological tests are performed, and sensors are pasted on glass fiber-reinforced plastic specimens to study strain gauge behaviors under quasistatic loading. The gauge factor in tensile loading is found to be layer width dependent as decreasing the strain gauge's layer width increases the sensitivity of the strain sensor. A maximum gauge factor of 34 is achieved using a layer width of 0.2 mm, 17 times greater than commercially available metal foil strain gauges. The four-point bend tests are performed under tension/compression to assess the sensor's strain-sensing and damage-monitoring ability. Fractographic analysis is coupled with strain monitoring using the developed sensor, which confirms that the failure progresses from intralaminar failure modes such as ply splitting in tension. At the same time, delamination leads to kink band formation under compression and the eventual failure of load-bearing fibers. The developed sensor exhibits repeatable performance with low hysteresis and integrated nonlinearity errors for up to 1000 cycles. The developed sensors could be effectively employed for online in situ structural health monitoring of aerospace structures under static and dynamic loading.

Item Type:	Journal article
Publication Title:	Advanced Engineering Materials
Creators:	Ahmed, S., Bodaghi, M., Nauman, S. and Muhammad Khan, Z.
Publisher:	Wiley
Date:	November 2023
Volume:	25
Number:	22
ISSN:	1438-1656
Identifiers:	Number Type 10.1002/adem.202300763 DOI 1843871 Other
Rights:	© 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Divisions:	Schools > School of Science and Technology
Record created by:	Jeremy Silvester
Date Added:	13 Dec 2023 10:02
Last Modified:	13 Dec 2023 10:02
URI:	https://irep.ntu.ac.uk/id/eprint/50535

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