Research on the Relationship between the Loading and the Conductivity of Smart Asphalt Concrete

Zhu, Feng; Cheung, Lam Wah; Dong, Zejiao

doi:10.1061/41047(354)24

Cited by 3 publications

(3 citation statements)

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“…The correlation in Figure 8 indicates that the FCR initially increases beyond 100% as compressive load is applied to the mixture. This happens due to the effect of compressive load on the irregularities in the mixture that causes an abrupt increase in +FCR, 33 and then starts increasing negatively as −FCR. The compressive load brings the dispersed CF and TA particles nearer to each other, and develops strong conductive network or negative piezo‐resistivity 51 .…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, the authors used CF to make the concrete a smart and better structural material owing to its higher conductivity and reinforcing effect. 33 To reduce the cost associated with expensive CF, researchers considered the combination of CF and GP to impart costeffective conductivity in asphalt concrete. 34,35 However, many researchers observed that the combination of CF and GP also affects some of the mechanical properties of asphalt concrete because of higher amounts of GP.…”

Section: Introductionmentioning

confidence: 99%

“…It has been observed that adding higher amount of GP to increase the conductivity has a negative impact on the structural performance of asphalt concrete. Therefore, the authors used CF to make the concrete a smart and better structural material owing to its higher conductivity and reinforcing effect 33 . To reduce the cost associated with expensive CF, researchers considered the combination of CF and GP to impart cost‐effective conductivity in asphalt concrete 34,35 .…”

Section: Introductionmentioning

confidence: 99%

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Self‐stress and deformation sensing of electrically conductive asphalt concrete incorporating carbon fiber and iron tailings

Ullah

Wan

Yang

et al. 2022

Structural Contr & Hlth

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Summary Asphalt road gradually deteriorates in serviceability with insignificant damage. The deterioration begins with microcracks and continues until structural failure. To facilitate early damage prediction, this study proposes a structural self‐sensing technique based on the piezo‐resistive behavior of conductive asphalt concrete. To this end, conventional asphalt mixtures were modified into self‐sensing mixtures by adding conductive carbon fiber (CF) and iron tailings aggregates (TA) as alternatives for natural aggregates (NA). The self‐sensing response was evaluated by correlating fractional changes in electrical resistance (FCR) with the deformation of mixture within and beyond the elastic regime in response to varying stress amplitudes under fatigue cyclic compressive loading. From the results, it can be seen that the mixture exhibits sufficient mechanical strength and low resistivity to achieve a self‐sensing response. Furthermore, the self‐sensing response varies significantly with the stress amplitude. The mixture exhibits sufficient sensitivity to the compaction and deformation within the elastic regime by reversibly decreasing its electrical resistance at low‐stress, manifested as increase in negative (−) FCR. The −FCR reversibly decreases, reflecting initiation of microcracks due to increased deformation within the elastic regime at medium‐stress. However, irreversible FCR is observed at high‐stress due to increase in deformation beyond the elastic regime, which leads to fracture. After fracture, the mixture does not show sensitivity to stress and deformation owing to the cracking of internal conductive network. In conclusion, the mixture provides early damage prediction as sensitive damage sensor in the elastic regime and enables real‐time structural health monitoring (SHM) of asphalt pavements.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Self‐stress and deformation sensing of electrically conductive asphalt concrete incorporating carbon fiber and iron tailings

Ullah

Wan

Yang

et al. 2022

Structural Contr & Hlth

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Compositions of Self-Sensing Concrete

Han

Yu²,

Ou³

2014

Self-Sensing Concrete in Smart Structures

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Self-Monitoring of Damage Evolution in Asphalt Concrete Based on Electrical Resistance Change Method

Zhang

Ullah

Zhou

et al. 2022

Journal of Testing and Evaluation

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Asphalt pavements expose early damage during their service life. The early damage grows internally until it accumulates and transforms into macro-damage that leads to structural failure. To promote real-time monitoring of internal damage evolution in asphalt pavements, this study proposes an electrical resistance change (ERC) method that exploits the piezoresistive properties of conductive asphalt concrete as a nondestructive testing technique capable of detecting microstructural defects. For this purpose, the traditional asphalt mixtures were first made electrically conductive by adding carbon fibers and iron tailing aggregates as conductive aggregates to satisfy the piezoresistivity requirements. Secondly, piezoresistivity experiments were performed by applying cyclic tensile force in fatigue and progressively increasing mode. The self-monitoring ability of damage evolution was assessed based on the correlation between the fractional change in electrical resistance (FCR), displacement, and damage degree for each mode of the force application. It was observed that under fatigue mode, the FCR and displacement increase upon loading and decrease reversibly upon unloading in each cycle. Compared with the displacement, the FCR exhibits partial reversibility upon unloading, indicating damage initiation in each cycle. The damage grows with the number of loading cycles until it accumulates in the elastic regime and gradually affects the load-carrying capacity of the mixture. Under a progressively increasing mode, the mixture exhibits a good correlation between the FCR and force in the elastic regime, ensuring real-time monitoring of internal micro-damage. However, the FCR develops a nonlinear correlation with the force in the inelastic regime that reflects damage to the conductive network and eventually structural failure. In summary, the ERC method provides real-time monitoring of microstructural defects that manifest as early damage and gradually transform into macro-damage under repeated traffic loads.

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Research on the Relationship between the Loading and the Conductivity of Smart Asphalt Concrete

Cited by 3 publications

References 0 publications

Self‐stress and deformation sensing of electrically conductive asphalt concrete incorporating carbon fiber and iron tailings

Self‐stress and deformation sensing of electrically conductive asphalt concrete incorporating carbon fiber and iron tailings

Compositions of Self-Sensing Concrete

Self-Monitoring of Damage Evolution in Asphalt Concrete Based on Electrical Resistance Change Method

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