Abstract:This article presents the results of a quantitative investigation with descriptive and correlation scopes, where a database for pavements of a Peruvian airport was elaborated, with the purpose of developing a prediction numerical model of the pavement condition, which relates the pavement condition index (PCI) as a function of time (pavement age).
Given the limitation of the pavement condition historical data and the need of them to know the pavement behavior under specific conditions (climate, traffic, material, among others) a quantitative numerical model is proposed applying Markov chains, calculating the Markov probability transition matrix from a data nonlinear logistic regression numerical process.
Finally, the model validation is presented, which is the main tool of an Airport Pavement Management System (APMS), because it allows pavement status forecasting knowing its current status.
|