Reinforced concrete bridge deck reliability model incorporating temporal and spatial variations of probabilistic corrosion rate sensor data

Abstract

The reliability of reinforced concrete (RC) bridge decks depends significantly on the rate of corrosion of the reinforcing steel. Structural health monitoring (SHM) techniques, including embedded corrosion rate sensors, can greatly improve the quantification of the steel corrosion rate, which can lead to improved estimates of structural safety and serviceability. Due to uncertainties in concrete properties, environmental conditions, and other factors, the rate of corrosion of reinforcing steel can be highly variable, both within a given structural component and over time. By placing multiple corrosion rate sensors throughout a structural component, such as a bridge deck, these spatial and temporal variabilities can be monitored and as such better predicted, for use in a reliability model. The objective of this investigation is to present a reliability model for a RC bridge deck incorporating both spatial and temporal variations of probabilistic corrosion rate sensor data. This objective is accomplished using a computational reliability model and Monte Carlo simulation. Corrosion rate sensor data is assumed for multiple critical sections throughout a RC bridge deck over time by applying empirical spatial and temporal relationships. This data is then used to improve an existing spatially invariant reliability model. The improved reliability model incorporates several sub-models to determine the changes in load effects on and resistance of a RC bridge deck slab over time, as well as spatial correlation of corrosion and a system approach to account for spatial variability. The improved reliability model incorporating both spatial and temporal variations in corrosion rate data provides a better estimate of the service life of a RC bridge deck slab.