The rheological properties of fresh cement paste with different content of graphene nanoplatelets (GNPs), different shear rate cycles and resting time was investigated. The rheological data were fitted by the Bingham model, Modified Bingham model, Herschel-Bulkley model and Casson model to estimate the yield stress and plastic viscosity, and to see trend of the flow curves. The effectiveness of these rheological models was expressed by the standard error. Test results showed that yield stress and plastic viscosity increased with the increase in the content of graphene in the cement based composite and resting time while the values of these parameters decreased for higher shear rate cycle. In comparison to control sample, the GNP cement based composite showed 30% increase in load carrying capacity and 73% increase in overall failure strain. Piezo-resistive characteristics of GNP were employed to evaluate the self-sensing composite material. It was found that, at maximum compressive load, the electrical resistivity value reduced by 42% and hence GNP cement based composite can be used to detect the damages in concrete. Finally, the practical application of this composite material was evaluated by testing full length reinforced concrete beam. It was found that graphene-cement composite specimen successfully predicted the response against cracks propagation and hence can be used as self-sensing composite material.
- Graphene nanoplatelets
- Rheological properties
- Structural health monitoring
ASJC Scopus subject areas
- Geography, Planning and Development
- Renewable Energy, Sustainability and the Environment
- Management, Monitoring, Policy and Law