A study of the main factors affecting the performance of self-sensing concrete

Abstract

Concrete sensors, which are manufactured by mixing conductive fibres (such as carbon nanotubes (CNTs)) with concrete, are one of the most significant and economical types of sensor. Two main factors affecting the performance of concrete sensors are the amount of CNTs and the quality of their dispersion in the mixture with regard to the combined effects of the surfactant composition and CNTs dispersed with different levels of energy. The goal of this research was to evaluate the effects of the main parameters affecting concrete sensor performance using various criteria (sensitivity of the sensor, standard deviation of the prediction error, repeatability, cross-correlation and hysteresis) in both static and dynamic loading regimes. Dynamic criteria such as sensitivity, internal repeatability, cross-correlation and hysteresis showed that the energy levels for the dispersion of CNTs have a greater effect on improving sensor performance than the amount of CNTs. On the contrary, the repeatability indicated that the amount of CNTs has a greater effect on sensor performance than the dispersion quality (energy level) of the CNTs. On the whole, the sensor produced with 0·15 wt% (by weight of cement) CNTs, superplasticiser and sodium dodecyl sulfate as a surfactant using the maximum energy level (ultrasonic bath for 2 h and 90 min of probe's ultrasonication) offered the best performance both in the static and dynamic load regimes.