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Monitoring Road Infrastructures with Self-sensing Asphalt Pavements

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European Workshop on Structural Health Monitoring (EWSHM 2022)

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 253))

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Abstract

Structural health monitoring (SHM) of road pavements is an essential task, which can help the decision-making process for timely maintenance actions. Embedded sensors are typically used to collect long-term monitoring data. However, the main drawbacks of intrusive sensors concern the risk of premature damage and the incompatibility of the sensors with the host material. Self-sensing asphalt mixtures can be used to overcome these limitations. These kinds of smart materials can autonomously monitor their strain and damage states without the need for embedded sensors. The sensing mechanism is based on the piezoresistive effect, consisting of a change in the electrical conductivity of the material when subjected to external loading. To endow the asphalt mixture with piezoresistive function, a proper amount of conductive additive should be incorporated without compromising the mechanical performance of the pavement.

The present work aims to design piezoresistive asphalt mixtures for the development of SHM and traffic management systems. Multi-walled carbon nanotubes (MWNTs) and graphene nanoplatelets (GNPs) were added to the asphalt mixture with this purpose, and the piezoresistive response was tested at laboratory scale. The results show that piezoresistive asphalt mixtures have excellent self-sensing properties and can be effectively used for SHM, traffic detection and weigh-in-motion applications.

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Correspondence to Federico Gulisano .

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Gulisano, F., Buasiri, T., Cwirzen, A., Gallego, J. (2023). Monitoring Road Infrastructures with Self-sensing Asphalt Pavements. In: Rizzo, P., Milazzo, A. (eds) European Workshop on Structural Health Monitoring. EWSHM 2022. Lecture Notes in Civil Engineering, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-031-07254-3_79

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  • DOI: https://doi.org/10.1007/978-3-031-07254-3_79

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-07253-6

  • Online ISBN: 978-3-031-07254-3

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