On the Optimal Design of Smart Composite Sensors for Impact Damage Detection

Tabatabaeian, A., Fotouhi, S. , Harrison, P. and Fotouhi, M. (2022) On the Optimal Design of Smart Composite Sensors for Impact Damage Detection. In: 20th European Conference on Composite Materials (ECCM20), Lausanne, Switzerland, 26-30 Jun 2022, ISBN 9782970161400 (doi: 10.5075/epfl-298799_978-2-9701614-0-0)

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Abstract

This paper aims to study the feasibility of smart thin-ply hybrid glass/carbon sensors in quasi-static impact damage detection and analyse different design strategies to achieve an optimal sensor performance. A set of carbon fibre reinforced polymer (CFRP) specimens was manufactured, and the hybrid sensing layers were attached and evaluated. New architectures of hybrid sensing layers are proposed using woven prepregs and introducing pre-cuts to increase stress concentration. The sensors are used under indentation to detect the damage. Outcomes established key design insights, which will be used further in developing the self-sensing technology and may result in more sustainable composite structures that are light-weight, easy to inspect and last longer.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Fotouhi, Dr Sakineh and Fotouhi, Dr Mohammad and Harrison, Dr Philip and Tabatabaeian, Mr Ali
Authors: Tabatabaeian, A., Fotouhi, S., Harrison, P., and Fotouhi, M.
College/School:College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
ISBN:9782970161400
Copyright Holders:Copyright © 2022 Tabatabaeian et al.
First Published:First published in Proceedings of the 20th European Conference on Composite Materials (ECCM20)
Publisher Policy:Reproduced under a Creative Commons License
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
310254Novel architectures for visibility and tolerance of impact damage in composites (VIDCOM)Mohammad FotouhiEngineering and Physical Sciences Research Council (EPSRC)EP/V009451/1ENG - Autonomous Systems & Connectivity