Computational and Experimental Insights into Life-Cycle Structural Reliability Assessment of Concrete Bridges under Corrosion

A recent SEI/ASCE survey highlights that advanced life-cycle models for deteriorating structures are well established for some of the most detrimental damage processes (e.g. corrosion). However, reliability assessment procedures and deterioration models under uncertainties are generally sensitive to change of the probabilistic parameters of the input random variables, and their validation is a difficult task because of the limited availability of data. In this paper, a computational approach to life-cycle reliability assessment of deteriorating structures exposed to aggressive environment is presented and applied to an existing prestressed concrete box-girder railway bridge under corrosion. The material mechanical characteristics and the properties of the exposure scenario are calibrated through an experimental campaign based on non-destructive diagnostic tests and laboratory tests on concrete cores and samples of reinforcing steel bars. Statistical inference and Bayesian updating are used to improve the life-cycle probabilistic prediction model based on the experimental outcomes.