Visual impact damage monitoring enhancement of curved composite panels using thin-ply hybrid composite sensors

Journal Article (2025)
Author(s)

A. Tabatabaeian (University of Glasgow)

R. Mohammadi (TU Delft - Materials and Environment)

Philip Harrison (University of Glasgow)

M. Fotouhi (TU Delft - Materials and Environment)

Research Group
Materials and Environment
DOI related publication
https://doi.org/10.1177/00219983251329096
More Info
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Publication Year
2025
Language
English
Research Group
Materials and Environment
Issue number
18
Volume number
59
Pages (from-to)
2171-2187
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Abstract

The wide application of curved composite profiles across various industries raises questions about transferring findings from standardised tests to curved structures. Particularly for low-velocity impacts, understanding the deformation and damage behaviour of curved structures is crucial to achieve their lightweight potential. Carbon fibre reinforced polymer (CFRP) composites often show no surface visible damage after low-energy impacts, but barely visible impact damage (BVID) can compromise load-bearing capacity under continuous loads. This study aims to evaluate the effectiveness of self-reporting thin-ply hybrid composites as coating layers for structural health monitoring in curved panels, focusing specifically on enhancing the visual detection of BVID. Quasi-isotropic curved composite panels made from IM7 carbon/8552 epoxy were first manufactured, and their mechanical response under quasi-static indentation was analysed and compared to flat panels. Next, a hybrid composite—comprising a layer of unidirectional S-glass/epoxy and thin-ply YS-90A carbon/epoxy—was applied to the outer surfaces of the curved panels. To simulate a real-world application, the curved panels were designed with dimensions similar to those of composite hydrogen storage tanks. The results indicate that the hybrid composite sensors functioned satisfactorily and provided direct correlations between visible surface damage on the surface and BVID. The visual inspection results are connected to data obtained from the load-displacement graphs, enabling a thorough analysis of sensor performance in visualising different stages of BVID.