Investigation of carbon nanotube and energy levels effects on Self-sensing Concrete Sensor Performance in Dynamic Loading Pattern

Today, the construction and development of low cost and smart concrete pavement is considered. Smart concrete pavement provides the ability to measure of load and damage detection at the same time when it withstands under the traffic loading. concrete sensor which is manufactured by mixing conductive fibers (such as carbon nanotubes (CNTs)) with concrete can measure the moving vehicle loads or detect damage propagation by variation in electrical response from two heads of sensor. Two main factors affecting the performance of concrete sensors are the amount of CNTs and their dispersion quality in the mixture with regard to the combined effects of the surfactant composition and content and of the CNTs dispersed with different level of energy. in this research different concrete sensors containing different amounts of CNTs (0.1,0.125,0.15,0.2) percent of cement weight with different levels of dispersion energy levels (one hour of ultrasonic bath, two hours of ultrasonic bath and one hour of ultrasonic bath with 90 minutes of probe ultrasonic) are manufactured. The goal of this study is to evaluate the effects of the main parameters affecting concrete sensor performance using various criteria in dynamic loading regime such as sensitivity of the sensor (Se), standard deviation of the prediction error, repeatability, cross-correlation and hysteresis (SSE). the results shows that, the higher energy levels in dispersion of CNTs in aqua phase lead to proper dispersion in cement phase and this parameter is more effective than the amount of CNTs to improve the concrete sensor performance. Also, in a constant energy level, with an increase in carbon nanotubes, sensor performance improves.