Life cycle monitoring of structural health of civil constructions is crucial to guarantee users' safety. An optimal structural health monitoring system allows to automatically detect, locate, and quantify any damage in structural elements, thus anticipating major risks of local or global failures. Critical issues affecting traditional monitoring systems are sensors' placement, hardware durability, and long-term reliability of the measurements. Indeed, sensors' deployment is crucial for an effective investigation of the static and dynamic characteristics of the structural system, whereby durability and long-term stability of sensing systems are necessary for long-term monitoring. A very attractive solution to some of these challenges is developing sensors made of the same, or similar, material of the structure being monitored, allowing a spatially distributed and long-term reliable monitoring system, by the use of self-sensing construction materials. Within this context, the authors have recently proposed new "smart clay bricks" that are strain-sensing clay bricks aimed at embedding intelligent monitoring capabilities within structural masonry buildings. While previous work focused on smart bricks doped with titanium dioxide and using embedded point electrodes, this work proposes an enhanced version of smart bricks based on the addition of conductive micro stainless steel fibers that possess higher electrical conductivity and a more suitable fiber-like aspect ratio for the intended application, as well as plate copper electrodes deployed on top and bottom surfaces of the bricks. The paper thus presents preparation and experimental characterization of the new smart bricks. The influence of different amounts of fibers is investigated, allowing the identification of their optimal content to maximize the gauge factor of the bricks. Both electrical and electromechanical experimental tests were performed. Overall, the presented results demonstrate that the new smart bricks proposed in this paper possess enhanced strain-sensing capabilities and could be effectively utilized as sensors within structural masonry buildings. © 2018 Antonella D'Alessandro et al.
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