Piezoresistive behavior of electric arc furnace slag and graphene nanoplatelets asphalt mixtures for self-sensing pavements

Gulisano, Federico; Buasiri, Thanyarat; Apaza, Freddy Richard Apaza; Ćwirzeń, Andrzej; Gallego, Juan

doi:10.1016/j.autcon.2022.104534

Cited by 23 publications

(12 citation statements)

References 48 publications

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“…For example, steel slag, due to its granular shape, does not necessitate any specific dispersion technique and can be treated as a natural aggregate in an asphalt mixture. Although this is a huge advantage for its employment, it should be noted that the use of only steel slag hardly permits the activation of a self-sensing function; thus, a combination with conductive nanoparticles is often necessary [67]. Steel fibers are typically mixed with bitumen before the incorporation of aggregates [43,68], without any specific modifications in the fabrication phase.…”

Section: Dispersion Techniquesmentioning

confidence: 99%

Development of Self-Sensing Asphalt Pavements: Review and Perspectives

Gulisano,

Jimenez-Bermejo,

Castano-Solís

et al. 2024

Sensors

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The digitalization of the road transport sector necessitates the exploration of new sensing technologies that are cost-effective, high-performing, and durable. Traditional sensing systems suffer from limitations, including incompatibility with asphalt mixtures and low durability. To address these challenges, the development of self-sensing asphalt pavements has emerged as a promising solution. These pavements are composed of stimuli-responsive materials capable of exhibiting changes in their electrical properties in response to external stimuli such as strain, damage, temperature, and humidity. Self-sensing asphalt pavements have numerous applications, including in relation to structural health monitoring (SHM), traffic monitoring, Digital Twins (DT), and Vehicle-to-Infrastructure Communication (V2I) tools. This paper serves as a foundation for the advancement of self-sensing asphalt pavements by providing a comprehensive review of the underlying principles, the composition of asphalt-based self-sensing materials, laboratory assessment techniques, and the full-scale implementation of this innovative technology.

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Section: Dispersion Techniquesmentioning

confidence: 99%

Development of Self-Sensing Asphalt Pavements: Review and Perspectives

Gulisano,

Jimenez-Bermejo,

Castano-Solís

et al. 2024

Sensors

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“…Fine aggregates (0/4 mm) and filler were composed of Electrical Arc Furnace Slag (EAFS) with a specific gravity of 3.78 g/cm 3 . Previous research has indicated that incorporating fine EAFS in the mixture can lower the electrical resistance of the mastic phase [13].…”

Section: Raw Materialsmentioning

confidence: 99%

“…To address these issues, the use of self-sensing asphalt-based materials represents a potential solution for pavement health monitoring operations [10]. These materials, designed by dispersing conductive carbon-based materials throughout the insulating asphalt pavement [11], exhibit changes in their electrical resistance when subjected to external stimuli such as stress, strain, or damage (known as the piezoresistive effect) [12,13]. By measuring the electrical response of the pavement, real-time reliable data about the strain conditions of asphalt pavements can be obtained.…”

Section: Introductionmentioning

confidence: 99%

Non-destructive testing methods for road pavement health monitoring: electromechanical assessment of self-sensing asphalt materials

Gulisano,

Apaza Apaza,

Gálvez-Pérez

et al. 2023

Earth Resources and Environmental Remote Sensing/Gis Applications XIV

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Nowadays, the use of Non-destructive Testing Methods (NDTs) has been consolidated for the Structural Health Monitoring (SHM) of road pavements and the continuous and rapid assessment of transport infrastructures. These methods are crucial to support Public Authorities and infrastructure managers in the decision-making processes, for programming more effective maintenance actions. Pavement instrumentation with different kinds of embedded sensors is generally employed to acquire long-term monitoring data. However, several limitations of intrusive sensors are related to the risk of premature damage and deterioration. Amongst the most recent advances in NDT methods, the use of asphalt-based self-sensing materials has progressively emerged as a promising technique for the ground-based health monitoring of road pavements. These kinds of stimuli-responsive materials can be designed by dispersing conductive carbon-based nanomaterials throughout the host-insulating asphalt pavement. More specifically, the proposed NDT sensing methodology is based on the piezoresistive effect, consisting of a change in the electrical response of the pavement when subjected to strain or damage. Real-time reliable data about the structural health condition of road pavements can be therefore obtained by measuring the electrical response of the pavement, implementing a sensing procedure. This research aims at assessing the strain and load sensing response of piezoresistive asphalt mixtures. To this purpose, electromechanical laboratory tests were conducted to evaluate the electrical response of asphalt mixtures under dynamic loading. A tailored digital signal processing and machine learning algorithms were also developed to analyze the electrical signal generated by the material and provide insightful information about its structural behavior.

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“…To establish the sensing capability, various conductive fillers, including steel fibers [ 5 , 6 , 7 , 8 ], micro- and nanocarbon fibers [ 9 , 10 , 11 , 12 ], carbon black structures [ 13 , 14 , 15 , 16 ], carbon nanotubes [ 17 , 18 , 19 , 20 , 21 ], graphene nanoplatelets [ 22 , 23 , 24 , 25 , 26 , 27 ], steel fibers [ 28 , 29 ], and hybrid conductive fillers [ 30 , 31 , 32 , 33 ], are incorporated into cementitious composites. However, carbon-based functional materials vastly increase cementitious composite piezoresistivity and enhance mechanical characteristics [ 34 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

Performance of Self-Sensing Cement-Stabilized Sand under Various Loading Conditions

Roshan,

Abedi,

Gomes Correia

et al. 2024

Sensors

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Numerous elements, such as the composition and characteristics of carbon nanomaterials, the composition and characteristics of the matrix material, moisture levels, temperature, and loading circumstances, influence the piezoresistive behavior of self-sensing cementitious composites. While some past research has explored the impact of some of these factors on the performance of self-sensing cementitious composites, additional investigations need to be conducted to delve into how loading conditions affect the sensitivity of self-sensing cement-stabilized composites. Therefore, this study explores the influences of various loading conditions (i.e., location of loading regarding the location of recording electrodes, and loading level) on the electromechanical performance of self-sensing cement-stabilized sand. To this end, firstly, the evaluation of the percolation threshold based on 10% cement-stabilized sand specimens containing various multiwall carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) was performed. Then, 10% cement-stabilized sand containing 4% MWCNTs/GNPs was tested under various cyclic compressive stresses. The results suggested that the distance between the loading area and the electrode location used for recording the electrical resistance significantly impacted the sensitivity of cement-stabilized sand. Optimal sensitivity was achieved when the electrodes were positioned directly beneath the loading area. Moreover, the study showed that the stress sensitivity of self-sensing cement-stabilized sand increased proportionally with the stress level. An examination through scanning electron microscopy (SEM) demonstrated that the loading condition influences the bridging characteristics of carbon nanomaterials in cement-stabilized sand, leading to diverse electromechanical behaviors emerging based on the loading condition. This study underscores the importance of considering specific parameters when designing self-sensing cement-stabilized sand for application in practical field use.

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Piezoresistive behavior of electric arc furnace slag and graphene nanoplatelets asphalt mixtures for self-sensing pavements

Cited by 23 publications

References 48 publications

Development of Self-Sensing Asphalt Pavements: Review and Perspectives

Development of Self-Sensing Asphalt Pavements: Review and Perspectives

Non-destructive testing methods for road pavement health monitoring: electromechanical assessment of self-sensing asphalt materials

Performance of Self-Sensing Cement-Stabilized Sand under Various Loading Conditions

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