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Detection of barely visible impact damage using a smart hybrid composite surface layer

Fotouhi, Mohammad; Xia Pui, Wei; Fotouhi, Sakineh; Jalalvand, Meisam; Wisnom, Michael R

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Authors

Mohammad Fotouhi

Wei Xia Pui

Sakineh Fotouhi

Meisam Jalalvand

Michael R Wisnom



Abstract

An important and yet unsolved limitation of existing composite laminates is their susceptibility to impact damage. The ability to visually detect damage from impact events is a common concern for carbon/epoxy composite laminates, particularly because composite materials can sustain impact damage in forms such as delamination and backside fiber breakage that is not directly visible at the site of the impact. Barely visible impact damage (BVID) has a significant effect on the mechanical performance of laminates, especially the compressive strength which may decrease by up to 60% compared with an undamaged laminate. As a result, very large design margins and more technical maintenance and inspection procedures are required compared to metallic structures.
Self-sensing composites are emerging technologies that can indicate their own physical conditions such as stress, strain or temperature as well as deformation and damage. In recent published studies a purpose-designed, thin interlayer glass/carbon-epoxy hybrid composite sensor concept is presented that was used to indicate the overload of a structure by exhibiting a change in their appearance when loaded in tension over a predefined strain value.
The idea of this research is to introduce novel hybrid composites with self-sensing ability to indicate BVID. This is in contrast to the use of embedded or attached sensors, which are more costly and less durable than the structural material.

Presentation Conference Type Conference Abstract
Conference Name 23rd International Conference on Composite Materials (ICCM23)
Start Date Jul 30, 2023
End Date Aug 4, 2023
Acceptance Date Feb 8, 2021
Deposit Date Sep 6, 2024
Publicly Available Date Sep 6, 2024
Peer Reviewed Peer Reviewed
Public URL https://uwe-repository.worktribe.com/output/12843274

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