Evidence map›Paper›PMID 39204864›Full record

ArticleSensors (Basel, Switzerland)2024

Characterisation and Application of Bio-Inspired Hybrid Composite Sensors for Detecting Barely Visible Damage under Out-of-Plane Loadings.

Ali Tabatabaeian, Reza Mohammadi, Philip Harrison, Mohammad Fotouhi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ali TabatabaeianJames Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK.
Reza MohammadiFaculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 CN Delft, The Netherlands.
Philip HarrisonJames Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK.
Mohammad FotouhiFaculty of Civil Engineering and Geosciences, Delft University of Technology, 2628 CN Delft, The Netherlands.

Funding

EPSRC EP/V009451/1
6 · The paper itself

Abstract

Traditional inspection methods often fall short in detecting defects or damage in fibre-reinforced polymer (FRP) composite structures, which can compromise their performance and safety over time. A prime example is barely visible impact damage (BVID) caused by out-of-plane loadings such as indentation and low-velocity impact that can considerably reduce the residual strength. Therefore, developing advanced visual inspection techniques is essential for early detection of defects, enabling proactive maintenance and extending the lifespan of composite structures. This study explores the viability of using novel bio-inspired hybrid composite sensors for detecting BVID in laminated FRP composite structures. Drawing inspiration from the colour-changing mechanisms found in nature, hybrid composite sensors composed of thin-ply glass and carbon layers are designed and attached to the surface of laminated FRP composites exposed to transverse loading. A comprehensive experimental characterisation, including quasi-static indentation and low-velocity impact tests alongside non-destructive evaluations such as ultrasonic C-scan and visual inspection, is conducted to assess the sensors' efficacy in detecting BVID. Moreover, a comparison between the two transverse loading types, static indentation and low-velocity impact, is presented. The results suggest that integrating sensors into composite structures has a minimal effect on mechanical properties such as structural stiffness and energy absorption, while substantially improving damage visibility. Additionally, the influence of fibre orientation of the sensing layer on sensor performance is evaluated, and correlations between internal and surface damage are demonstrated.

Indexed as

barely visible impact damagebio-inspired mechanochromic compositeshybrid composite sensorvisual inspection

Identifiers

PMID39204864
PMCPMC11358944

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.