Lifetime Multiobjective Optimization of Cost and Spacing of Corrosion Rate Sensors Embedded in a Deteriorating Reinforced Concrete Bridge Deck

Due to variations in concrete properties, environmental conditions, and other factors, the rate of corrosion of reinforcing steel can be highly variable within a given structural component. By placing multiple corrosion rate sensors throughout a reinforced concrete (RC) bridge deck, this variability can be monitored and corrected for use in a reliability model. There is a limit, however, on the number of sensors that can be feasibly placed in a structure, due to economic and constructability constraints. The constraints on the design variables of a permanent structural health monitoring (SHM) sensor network can be used to formulate a multiobjective optimization problem. This investigation describes the formulation of this problem for a RC bridge deck to be outfitted with corrosion rate sensors. The total cost of sensor system installation and the maximum lifetime dispersion of corrosion current density serve as the two objective functions to be minimized. The design variables are the spacing between adjacent sensors and the unit cost of each sensor. A set of optimal (Pareto) solutions are found for various assumptions using a multiobjective goal seeking algorithm in conjunction with Bayesian updating and interpolation techniques. The set of optimal combinations of sensor spacing and unit cost provide the best tradeoff between total SHM system cost and performance for a given set of constraints.