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Interest in self-sensing structural materials has grown in recent years due to their potential to enable continuous low-cost monitoring of next-generation smart-structures. The development of cement-based smart sensors appears particularly well suited for structural health monitoring due to their numerous possible field applications, ease of use, and long-term stability. Additionally, cement-based sensors offer a unique opportunity for monitoring of civil concrete structures because of their compatibility with new and existing infrastructure. In this paper, we propose the use of a computationally efficient resistor mesh model to detect, localize and quantify damage in structures constructed from conductive cement composites. The proposed approach is experimentally validated on non-reinforced and reinforced specimens made of nanocomposite cement paste doped with multi-walled carbon nanotubes under a variety of static loads and damage conditions. Results show that the proposed approach is capable of leveraging the strain-sensing and damagesensitive properties of conductive cement composites for real-time distributed structural health monitoring of smart concrete structures, using simple and inexpensive electrical hardware and with very limited computational effort. AbstractInterest in self-sensing structural materials has grown in recent years due to their potential to enable continuous low-cost monitoring of next-generation smart-structures. The development of cement-based smart sensors appears particularly well suited for structural health monitoring due to their numerous possible field applications, ease of use, and long-term stability. Additionally, cement-based sensors offer a unique opportunity for monitoring of civil concrete structures because of their compatibility with new and existing infrastructure. In this paper, we propose the use of a computationally efficient resistor mesh model to detect, localize and quantify damage in structures constructed from conductive cement composites. The proposed approach is experimentally validated on non-reinforced and reinforced specimens made of nanocomposite cement paste doped with multi-walled carbon nanotubes under a variety of static loads and damage conditions. Results show that the proposed approach is capable of leveraging the strain-sensing and damage-sensitive properties of conductive cement composites for real-time distributed structural health monitoring of smart concrete structures, using simple and inexpensive electrical hardware and with very limited computational effort.

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The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix mterials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNT contents. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both quasi-static and sine-sweep dynamic uni-axial compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications.

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The paper presents a study on the use of cement-based sensors doped with carbon nanotubes as embedded smart sensors for static and dynamic strain monitoring of reinforced concrete (RC) elements. Such novel sensors can be used for the monitoring of civil infrastructures. Because they are fabricated from a structural material and are easy to utilize, these sensors can be integrated into structural elements for monitoring of different types of constructions during their service life. Despite the scientific attention that such sensors have received in recent years, further research is needed to understand (i) the repeatability and accuracy of sensors' behavior over a meaningful number of sensors, (ii) testing configurations and calibration methods, and (iii) the sensors' ability to provide static and dynamic strain measurements when actually embedded in RC elements. To address these research needs, this paper presents a preliminary characterization of the self-sensing capabilities and the dynamic properties of a meaningful number of cement-based sensors and studies their application as embedded sensors in a full-scale RC beam. Results from electrical and electromechanical tests conducted on small and full-scale specimens using different electrical measurement methods confirm that smart cement-based sensors show promise for both static and vibration-based structural health monitoring applications of concrete elements but that calibration of each sensor seems to be necessary.

Smart composite nanostructured materials represent one of the fastest-growing areas of interest among scientists in recent years and, in particular, Carbon NanoTube (CNT) cement-based composites are attracting more and more attention. These composites exhibit self-sensing capabilities providing measurable variations of their electrical properties under the application of mechanical deformations. Together with this exceptional property, the similarity and compatibility between these composites and structural concrete suggest the possibility of developing distributed embedded strain-sensing systems with substantial improvements in the cost-effectiveness in applications to large-scale concrete structures. In order to design and optimize CNT reinforced cement based dynamic sensors, it is fundamental to develop theoretical models capable of simulating the relationship between dynamic mechanical strains and the effective electrical conductivity. This paper presents an electromechanical modeling of the Direct Current (DC) electrical resistance of CNT reinforced cement paste sensors based on a piezoelectric/piezoresistive lumped circuit. The model represents an enhanced version and a generalization of another model previously proposed by the authors. Previously published experimental results have been used as validation benchmark. In particular, experimental tests concerning the characterization of the step response under unloaded conditions, steady state response under harmonic loadings and sweep analyses are considered. The results demonstrate that the newly proposed model is superior in comparison to the previous one in reproducing the dynamic response of the sensors when subjected to harmonic mechanical loads. Overall, an excellent agreement between theoretical predictions and experimental results is achieved.