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Dr. Sherif Araby Gouda :: Publications:

Title:
Investigation on graphene addition on the quasi-static and dynamic responses of carbon fibre-reinforced metal laminates
Authors: Shuo Wang, Meng Cao, Hongqian Xue, Sherif Araby, Fethi Abbassi, Yanli He, Weiguo Su, Qingshi Meng
Year: 2022
Keywords: Not Available
Journal: Thin-Walled Structures
Volume: 174
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

In this paper, graphene nanoplatelets (GnPs) were used with carbon fibre/epoxy composite to enhance the mechanical performance of fibre metal laminates (FMLs). The designed FMLs are composed of thin aluminium alloy layers alternating with carbon-fibre epoxy/GnP composite plies with a chemical treatment performed on the aluminium laminate to promote adhesion strength with the epoxy composite. Two different configurations of FMLs were investigated (i) composite plies with unidirectional carbon fibres (U-FMLs) and (ii) composite plies with plain carbon woven (W-FMLs). Samples were tested under dynamic loading (Charpy impact) and quasi-static loading (three-point flexure). The experimental results showed that FMLs with 0.3 wt% GnPs logged the best impact performance; the impact strength of W-FMLs and U-FMLs are respectively 18.2% and 25.2% higher than FMLs without GnPs. FMLs with 0.5 wt% GnPs recorded the highest enhancement in flexural strength, fracture strain and flexural modulus recording increments 23.1%, 19.3% and 48% for the W-FMLs, and 60.3%, 34.5% and 61.4% for the U-FMLs, respectively. Also, an in-depth microscopic analysis was conducted to understand the reinforcing mechanism of GnPs into FMLs. Moreover, a numerical model of a three-point flexural test was developed to show the ability of numerical tools to predict material behaviour at optimized costs. Johnson–Cook and Hashin damage models were used respectively for aluminium alloy and carbon fibre epoxy/GnP composite to accurately predict their deformation and damage modes.

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