The study investigates the capabilities of various configurations of self-sensory carbon-based textiles to detect and distinguish between the severity of water infiltration through cracked zones along textile reinforced concrete (TRC) elements. The investigation aims to explore whether an optimal smart textile configuration can improve the structural performance while providing sensitive sensory capabilities. Such an investigation is needed for the development of intelligent TRC structures. Specifically, the study experimentally investigates the effect of two types of bindings and the effect of coating on the mutual structural-sensory performances. The sensory concept is based on changes of the electrical mechanism of two adjacent carbon rovings due to infiltration of water through cracked zones. Eight TRC beam samples were cast and mechanically loaded up to cracking. The cracked zones were monitored, and each zone was separately examined by performing a wetting event. It is demonstrated that the type of binding and coating, which significantly affect the structural response, reflect and affect the measured electrical signal. It is found that there is a tradeoff mechanism between the structural response and the sensory capabilities. While specific textile configuration improves the structural performance, it may reduce its sensory capability to distinguish between the magnitude of water infiltration.
Mesoscale numerical modeling and characterization of the effect of reinforcement textile on the elevated temperature and tensile behaviour of carbon textile-reinforced concrete composite
