OVERSIGHT: Geotechnologies for early damage detection in reinforced concrete pavements and bridge decks
Convocatoria: Proyectos de Generación de Conocimiento 2022.
Financiación: Financiado por MICIU/AEI/10.13039/501100011033 y por FEDER, UE.
Referencia: PID2022-138526OB-I00.
Summary:
In Transport Infrastructures (TI), many structures are made of Reinforced Concrete (RC), being rigid pavements and bridge decks those requiring more periodic maintenance and servicing activities. Most degradation processes relevant to this material are related to an increased level of material moisture (e.g. corrosion). Projections of climate change are therefore fundamental to be considered in the new models governing the lifecycle assessment of RC structures. Overall, innovative approaches for RC-TI maintenance and safety are urgently needed, as the basis of any efficient repair activity should be a detailed damage diagnosis. Nevertheless, it is difficult to obtain the required information for the damage emanates from inside the structure (e.g. the initiation of the corrosion process cannot be detected by traditional visual inspections). Early damage detection reduces costs and ensures safety and reliability, thus fostering the prolonged use of the TI. Thus, proper condition monitoring using smart technologies enables more in-depth knowledge about the actual demands, responses and capacities of the structures. The gain in knowledge leads to an improved assessment of the actual safety level and improves the rationalization of decision-making concerning measures or interventions.
The general objective of OVERSIGHT aimed to develop an innovative and competitive solution to provide an early warning of RC deterioration in rigid pavements and bridge decks. New procedures and deep-learning algorithms based on CNN (Convolutional Neural Networks) will be developed for the automatic detection of subsurface and surface defects from GPR (Ground-Penetrating Radar) and LiDAR (Laser Imaging Detection and Ranging) data. Confidence condition maps and damage indicators will be then provided, thus aiding valuable information models (Open GIS and IFC models) and Augmented Reality visualization tools for onsite damage visualization to support decision-making oriented to prevent safety risks/collapse, aiming to improve sustainability and resilience of transport against climate change impacts, aging, errors during construction and lack of maintenance.
