Electrical measurements of carbon nanotube multiscale GFRPs have been carried out for the monitoring of low velocity impact dynamics. To achieve that purpose, several plates have been fed by a power supply and a high frequency acquisition system has been used. Electrical measurements show that there is an initial decrease of electrical resistance due to plate compression, followed by an increase due to tunneling effect of carbon nanotubes. Finally, the effect of mechanical rebound is correlated to drop rise cycles of the electrical resistance. The sensitivity of the measured signals is also correlated with the impact energy and the electrodes disposition. Thus, the proposed method proves the validity and applicability of carbon nanotubes to characterize the low-velocity impact dynamics of a composite laminate.

Monitoring of impact dynamics on carbon nanotube multiscale glass fiber composites by means of electrical measurements

SBARUFATTI, CLAUDIO;SCACCABAROZZI, DIEGO;CINQUEMANI, SIMONE;
2017-01-01

Abstract

Electrical measurements of carbon nanotube multiscale GFRPs have been carried out for the monitoring of low velocity impact dynamics. To achieve that purpose, several plates have been fed by a power supply and a high frequency acquisition system has been used. Electrical measurements show that there is an initial decrease of electrical resistance due to plate compression, followed by an increase due to tunneling effect of carbon nanotubes. Finally, the effect of mechanical rebound is correlated to drop rise cycles of the electrical resistance. The sensitivity of the measured signals is also correlated with the impact energy and the electrodes disposition. Thus, the proposed method proves the validity and applicability of carbon nanotubes to characterize the low-velocity impact dynamics of a composite laminate.
2017
Proceedings of SPIE - The International Society for Optical Engineering
9781510608252
Carbon nanotubes; Electrical conductivity; GFRP; Impact dynamics; SHM; Electronic, Optical and Magnetic Materials; Condensed Matter Physics; Computer Science Applications1707 Computer Vision and Pattern Recognition; Applied Mathematics; Electrical and Electronic Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1029723
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