Towards road pavement response under moving loads

Abstract

The road network is one of the major assets in our countries. A proper management is essential to guarantee an adequate quality of life and economic growth. This paper presents the effort undertaken for monitoring of a road section with embedded strain gauges. The experimental site is located in Corbas (close to Lyon, France). A 5 cm-thick wearing course made of BBSG (French acronym for “Béton Bitumineux Semi Grenu”) was placed over a pre-existing road covering an area of 6.4 m × 30 m. The pavement was instrumented with six asphalt strain gauges connected to a data acquisition system called PEGASE. An experimental lab campaign was necessary for the assessment of the exact road stratification. The measurement sessions in the trial section were performed with a known loading truck at different temperatures, speeds, and trajectories. Results show a high sensibility of the measurements to the above-mentioned parameters. The mechanical behaviour of the pavement was assessed in the Viscoroute^© software by using both an elastic and a viscoelastic approach. It emerged that the traditional pavement design approach has some limits in predicting the pavement behaviour at high temperature. Indeed in these conditions, a viscoelastic model that takes into account the mechanic contribution of the interfaces seems to be more appropriate. This research is fruit of a collaboration between Eiffage (European, leader in construction and concessions), LPICM (Laboratoire de physique des interfaces et des couches minces), IFSTTAR (Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux), and the University of Nottingham in the framework of the network-wide-training programme of SMARTI ETN (launched in 2017 under the Marie Sklodowska Curie Research Fellowship programme, MSCA).

Keywords:

• health monitoring
• road pavement
• instrumentation
• strain sensors

Acknowledgements

The research presented in this paper was carried out as part of the H2020-MSCA-ETN-2016.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This project has received funding from the European Union’s H2020 Programme for research, technological development and demonstration under grant agreement number 721493.