Mechanical Prediction of Graphene-Based Polymer Nanocomposites for Energy-Efficient and Safe Vehicles

Elmarakbi, Ahmed and Azoti, Wiyao (2018) Mechanical Prediction of Graphene-Based Polymer Nanocomposites for Energy-Efficient and Safe Vehicles. In: Experimental Characterization, Predictive Mechanical and Thermal Modeling of Nanostructures and their Polymer Composites. Micro and Nano Technologies . Elsevier, pp. 159-177. ISBN 978-0-323-48061-1

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Official URL: http://dx.doi.org/10.1016/B978-0-323-48061-1.00004...

Abstract

This work investigates efficient ways of lightweighting vehicles structures based on Graphene-related materials (GRMs). An integration of Graphene as polymer reinforcements within composite materials for energy-efficient and safe vehicles (EESVs) is addressed with respect to some technological challenges, for instance, the lack of constitutive material models for high-performance structural applications. Therefore, accurate material models need to be developed to support simulation of structural design for these vehicles. A multiscale modeling of Graphene-reinforced polymer composite is elaborated, and using the Mori-Tanaka micromechanics scheme, the effective nonlinear behavior is predicted for various microparameters such as the aspect ratio and volume fractions. The results show an enhancement of the equivalent macro-stress-strain response when the aspect ratio is low corresponding to platelets-like inclusions. Also, the volume fraction is seen to have a good improvement on the composite response. The results highlight the effect of Graphene platelets versus carbon and glass fibers in the design of lightweight structures with enhanced mechanical responses and by consequence a CO2 emissions reduction.

Item Type: Book Section
Subjects: F200 Materials Science
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: Becky Skoyles
Date Deposited: 05 Oct 2018 09:27
Last Modified: 05 Oct 2018 09:27
URI: http://nrl.northumbria.ac.uk/id/eprint/36073

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