Data-driven prediction of long-term deterioration of RC bridges
Pablo Alonso Medina, Francisco Javier León González, Leonardo Todisco
Abstract
During the last decades, an increasing number of administrations have been implementing Bridge Management Systems (BMS) to control their infrastructure and detect damages that may require reparation or further analysis. The collection of these data results in inspection databases which include large amounts of information that can be used to understand how reinforced concrete (RC) structures deteriorate over time under different environmental aggressiveness conditions. Based on collected information of 298 roadway RC bridges, this paper demonstrates how the statistical analysis of the data obtained from inspections can be used to predict their ageing evolution over time in a reliable way.