Self-sensing road pavements can autonomously monitor their stress/strain and damage states without the need for embedded sensors. This kind of multifunctional pavements could be used for the realisation of autonomous structural health monitoring (SHM) systems. Moreover, it would permit to collect important traffic data for traffic-monitoring analysis and the development of Vehicle to Infrastructure Communication (V2I) tools, hence contributing to the digitalisation of the transport sector. The sensing mechanism is based on the piezoresistive effect, consisting of a change in the electrical response of the road material when subjected to stress/strain or damage. This paper aims to investigate the piezoresistive behavior of conductive asphalt mixtures with electric arc furnace slag (EAFS) and graphene nanoplatelets (GNPs) for self-sensing application. The results showed that asphalt mixtures with EAFS as fine aggregate and 7 wt% of GNPs exhibited excellent self-sensing properties for both traffic monitoring and SHM systems.
Self-sensing road pavements can autonomously monitor their stress/strain and damage states without the need for embedded sensors. This kind of multifunctional pavements could be used for the realisation of autonomous structural health monitoring (SHM) systems. Moreover, it would permit to collect important traffic data for traffic-monitoring analysis and the development of Vehicle to Infrastructure Communication (V2I) tools, hence contributing to the digitalisation of the transport sector. The sensing mechanism is based on the piezoresistive effect, consisting of a change in the electrical response of the road material when subjected to stress/strain or damage. This paper aims to investigate the piezoresistive behavior of conductive asphalt mixtures with electric arc furnace slag (EAFS) and graphene nanoplatelets (GNPs) for self-sensing application. The results showed that asphalt mixtures with EAFS as fine aggregate and 7 wt% of GNPs exhibited excellent self-sensing properties for both traffic monitoring and SHM systems. Read More
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