Assessing and predicting fatigue damage of road pavement using embedded sensors and deflection measurements: a full scale test

Regular and long-term infrastructures monitoring is fundamental for asset management, as it provides information on the actual mechanical conditions and triggers maintenance actions. Several tools are currently used for this purpose, such as embedded sensing devices, deflection measurements and visual inspections. In this paper, we analyse data from a full-scale experiment performed on the accelerated pavement testing (APT) facility of the Université Gustave Eiffel (formerly Ifsttar) during the BioRepavation project. Dvnifferent monitoring data are recorded and compared: strains from asphalt strain gauges (ASGs), deflections from Benkelman beam and Falling Weigh Deflectometer (FWD) and crack development survey. Deflections measurements at the end of the fatigue test were used to inverse calculate the layer moduli of pavement. Based on this model, numerical strains are calculated and compared with sensor measurements. The analyses conducted proved that instrumentation embedded ASGs and temperature probes can be used valuably to assess pavement fatigue.