Concrete crack propagation in rigid pavements and surfaces: Stochastic analysis for health monitoring

Concrete is widely used as the primary material for constructing rigid pavements of roads and highways due to its versatility. However, it is prone to cracking, which can result in various issues such as rutting, potholes, shoving, and surface failure. The propagation of cracks necessitates regular inspection and rehabilitation throughout the lifespan of a project. The formation and propagation of cracks are influenced by multiple uncertain factors such as material properties, geometry, weather conditions, and traffic loads. To effectively address this issue, a stochastic approach that accounts for these uncertain quantities as random variables with appropriate probability distributions is desirable. The present study addresses the problem of crack propagation in concrete pavements from a stochastic perspective using the concepts of random walk and Markov chains. A procedure for continuous site inspections is proposed to develop statistical crack propagation and orientation models. The results of this study indicate that crack orientations are not uniformly distributed, but rather, they are clustered around specific orientations following a normal distribution with an increased coefficient of variation from the origin and a shifting mean. Thus, the Fokker-Planck equation is a suitable mathematical model for predicting the probability distribution of cracks in concrete pavement surfaces. The proposed model was found to accurately predict the distribution of crack orientations.