Micromechanics modeling of the uniaxial strain-sensing property of carbon nanotube cement-matrix composites for SHM applications

García‐Macías, Enrique; D’Alessandro, Antonella; Castro-Triguero, Rafael; Pérez-Mira, Domingo; Ubertini, Filippo

doi:10.1016/j.compstruct.2016.12.014

Cited by 153 publications

(72 citation statements)

References 93 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The conductive pathways can be formed by connecting the MWCNTs directly (Case #1). In addition, although the MWCNTs are not directly in contact with each other, the electrons can be transferred due to a tunneling effect when they become closer from the external compressive load (Case #2), as reported by García-Macías et al [15,16]. The cut-off distance between MWCNTs for the tunneling effect was suggested to be 0.5 nm [23].…”

Section: Test Results and Discussionmentioning

confidence: 92%

Electrical Properties of Cement-Based Composites with Carbon Nanotubes, Graphene, and Graphite Nanofibers

Yoo

You

Lee

2017

Sensors

142

View full text Add to dashboard Cite

This study was conducted to evaluate the effect of the carbon-based nanomaterial type on the electrical properties of cement paste. Three different nanomaterials, multi-walled carbon nanotubes (MWCNTs), graphite nanofibers (GNFs), and graphene (G), were incorporated into the cement paste at a volume fraction of 1%. The self-sensing capacity of the cement composites was also investigated by comparing the compressive stress/strain behaviors by evaluating the fractional change of resistivity (FCR). The electrical resistivity of the plain cement paste was slightly reduced by adding 1 vol % GNFs and G, whereas a significant decrease of the resistivity was achieved by adding 1 vol % MWCNTs. At an identical volume fraction of 1%, the composites with MWCNTs provided the best self-sensing capacity with insignificant noise, followed by the composites containing GNFs and G. Therefore, the addition of MWCNTs was considered to be the most effective to improve the self-sensing capacity of the cement paste. Finally, the composites with 1 vol % MWCNTs exhibited a gauge factor of 113.2, which is much higher than commercially available strain gauges.

show abstract

Section: Test Results and Discussionmentioning

confidence: 92%

Electrical Properties of Cement-Based Composites with Carbon Nanotubes, Graphene, and Graphite Nanofibers

Yoo

You

Lee

2017

Sensors

142

View full text Add to dashboard Cite

show abstract

“…This scatter in the GF values can be attributed to the proximity of the 1% MWCNTs mix with the percolation threshold. Previous theoretical work by the authors [35,36] demonstrated that the GF is maximum, close to the percolation threshold [24], but is also very sensitive to small changes in the materials' parameters and to small changes in the nanofiller dispersion quality. Figures 8 and 9 also show an acceptable linearity of the outputs of the sensors, especially at higher frequencies, even if some samples exhibited an increasing frequency response function and others a decreasing frequency response function.…”

Section: Electromechanicalmentioning

confidence: 99%

Static and Dynamic Strain Monitoring of Reinforced Concrete Components through Embedded Carbon Nanotube Cement-Based Sensors

D’Alessandro

Ubertini

García‐Macías

et al. 2017

Shock and Vibration

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…This decrease in resistance stems from the reduction in the average 335 distance among MWCNTs, therefore decreasing the resistance of the conductive networks through the quantum tunneling effect. This same theoretical approach applies in tension, where the difference in gauge factors is small enough that a common gauge 340 factor can be assumed [39]. For concrete specimens in tension, this theoretical approach governs until the opening of micro-cracks starts to control the conductive networks, however, for simplicity microcracks are not modeled in this work.…”

Section: Strain Sensing Characterizationmentioning

confidence: 99%

Damage detection, localization and quantification in conductive smart concrete structures using a resistor mesh model

Downey

D’Alessandro

Baquera

et al. 2017

Engineering Structures

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Micromechanics modeling of the uniaxial strain-sensing property of carbon nanotube cement-matrix composites for SHM applications

Cited by 153 publications

References 93 publications

Electrical Properties of Cement-Based Composites with Carbon Nanotubes, Graphene, and Graphite Nanofibers

Electrical Properties of Cement-Based Composites with Carbon Nanotubes, Graphene, and Graphite Nanofibers

Static and Dynamic Strain Monitoring of Reinforced Concrete Components through Embedded Carbon Nanotube Cement-Based Sensors

Damage detection, localization and quantification in conductive smart concrete structures using a resistor mesh model

Contact Info

Product

Resources

About