The increase in in asphalt pavement temperatures due to solar energy absorption contributes to the urban heat island effect (UHI) and causes deformation and accelerated aging of their materials. Volumetric heat capacity (Cv), thermal conductivity (λ), surface albedo, and emissivity are the thermophysical properties that control these thermal variations. A new method is presented for determining Cv and λ parameters using in-situ thermal measurements and numerical models solving the heat conservation equation. This approach has the advantage of easily determining the variations of these properties over time, that is necessary to estimate the age-related performance of the asphalt layers. The method was used to characterize the intermediate layers temperature of the pavement in a smart parking structure at the University of Palermo, Italy. The numerical model calibrated with the parameters assessed by the proposed method can predict the temperature variations of the studied pavement layers with great accuracy.

Mantalovas, K., Buscemi, A., Graziano, F., Celauro, C. (2025). Modelling the thermophysical properties of pavement layers using real-time sensor-collected data. ROAD MATERIALS AND PAVEMENT DESIGN, 1-16 [10.1080/14680629.2025.2483475].

Modelling the thermophysical properties of pavement layers using real-time sensor-collected data

Mantalovas, Konstantinos;Buscemi, Alessandro;Graziano, Francesco;Celauro, Clara
2025-01-01

Abstract

The increase in in asphalt pavement temperatures due to solar energy absorption contributes to the urban heat island effect (UHI) and causes deformation and accelerated aging of their materials. Volumetric heat capacity (Cv), thermal conductivity (λ), surface albedo, and emissivity are the thermophysical properties that control these thermal variations. A new method is presented for determining Cv and λ parameters using in-situ thermal measurements and numerical models solving the heat conservation equation. This approach has the advantage of easily determining the variations of these properties over time, that is necessary to estimate the age-related performance of the asphalt layers. The method was used to characterize the intermediate layers temperature of the pavement in a smart parking structure at the University of Palermo, Italy. The numerical model calibrated with the parameters assessed by the proposed method can predict the temperature variations of the studied pavement layers with great accuracy.
2025
Mantalovas, K., Buscemi, A., Graziano, F., Celauro, C. (2025). Modelling the thermophysical properties of pavement layers using real-time sensor-collected data. ROAD MATERIALS AND PAVEMENT DESIGN, 1-16 [10.1080/14680629.2025.2483475].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/676065
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