Grant: Discovery Grants Program - Individual

Pavements are essential transportation infrastructures that greatly contribute to the economic growth of a country. In Canada, the length of the road network exceeds 1,000,000 km including more than 30,000 km of highway and about 90% of all goods are transported using this network. Canadian roads are subjected to a harsh northern climate that greatly accelerates the development of various pavement distresses, such as the apparition of cracks or potholes. These distresses impact the safety of drivers and the performance and the durability of the pavement structures. Consequently, road agencies and municipalities are condemned to spend huge amounts of money in reparation and maintenance to extend the service life of their road pavements. Preventive maintenance operations such as crack sealing or rut filling can contribute to considerably cut these costs and increase the lifespan of pavements. Though, this strategy is only efficient if damages are detected and fixed before failures occur in the pavement. In recent years, the road industry has increasingly looked to optimize the lifecycle and the maintenance costs of pavement infrastructures by developing innovative road condition monitoring (RCM). However, recent publications have shown serious limitations regarding the development of an RCM system that could provide live monitoring of pavement condition remotely, which is critical for the future large-scale implementation of such a system. The proposed research program is focused on the development of RCM tools based on smart sensors networks (SSN) embedded in pavements that would help road agencies to better monitor their infrastructures, increase the safety of drivers and the durability of pavements, and contribute to the efforts towards smarter and greener pavement structures in Canada. The long-term objective of this research program is to achieve an autonomous, smart and pavement-integrated solution to monitor remotely and in real time the mechanical condition of pavement structures. The main research hypothesis of this proposal is that the integration of SSN in pavements can provide in the long-term data to assess the mechanical condition of the structure. Thus, on the shorter term, this 5-year program will be limited to laboratory and numerical investigations to reach the three following specific objectives: ?O1 - Quantify the effects of embedded SSN on the pavement behaviour and performance; ?O2 - Explore the potential of embedded SSN to detect and differentiate various pavement distresses; ?O3 - Evaluate the influence of environmental conditions on the durability of embedded SSN.