Sustainable Road Infrastructures Using Smart Materials, NDT, and FEM-Based Crack Prediction

Abstract

Smart cities need roads with high levels of sustainability. This goal can be reached using different approaches, such as smart materials, Non-Destructive Test (NDT)-based monitoring systems, and Finite Element Method (FEM)-based damage prediction models. The pieces of information provided using the above-mentioned approaches play a crucial role in the work of many stakeholders (citizens, users, road agencies, authorities, driverless vehicles, etc.). Consequently, the main objectives of this study presented in this paper are (i) providing an overview of the current approaches, and (ii) presenting a NDT-, and FEM-based monitoring system that was designed to improve the sustainability of the present and future road pavements by means of the road pavement damage detection and prediction. In more detail, the paper is focused on the set up and the calibration of a FEM model that aims at simulating the vibro-acoustic signatures of un-cracked and cracked road pavements. An NDT apparatus was used to gather the vibro-acoustic signatures of road pavement (data set) that was progressively damaged. Subsequently, the data set mentioned above was used to set up the FEM model. Results show that, even though the FEM model is able to replicate only in part the measured signals, this model can be successful used for predicting the variation of the structural health status of the road pavement. Hence, the proposed approach can be used to improve the sustainability of the current road pavements.