Probabilistic Optimum Inspection/Repair Planning to Extend Lifetime of Deteriorating Structures

Abstract

Repair actions are generally used to prevent failures and to maintain or extend the lifetime of deteriorating structures. To establish optimum inspection/repair planning for a structure, its performance under uncertainty should be assessed and predicted using probabilistic concepts and methods. This paper presents such an approach applied to deteriorating reinforced concrete (RC) structures under pitting corrosion. The inspection/repair plan is obtained from a probabilistic optimization process. Formulation of the extended lifetime for a given number of inspections is based on a decision tree analysis considering probability of damage detection. A damage detectability function is used to quantify the relation among damage intensity, quality of an inspection method, and probability of damage detection. The probability of repair representing the decision maker’s willingness to make a repair is also considered in the decision analysis. Effects of probabilities of inspection/repair and number of inspections on extended lifetime of an RC structure are investigated. To establish a cost-effective inspection/repair planning process, the formulation proposed is a biobjective optimization problem under uncertainty considering maximization of expected extended lifetime and minimization of expected total cost. The proposed approach is applied to an existing bridge.