Optimized Maintenance Policies for Deteriorating Structures

Reinforced concrete (RC) structures are exposed to a variety of environmental stressors that may initiate the deterioration of structures. The system deterioration, however, must be considered as a stochastic process since the progress of deterioration varies widely with several uncertain factors, which are generally not captured by available data. Considering that maintenance strategies are planned based on the estimates of the extent of structural deterioration, a systematic effort is needed to incorporate various sources of uncertainty in predictive models and decision-making algorithms. To this end, the current study utilizes Weibull distribution to investigate the deterioration of RC bridges. In the developed models, a set of condition states is used to describe the level of structural degradation characterized by different performance rates, ranging from perfect functioning to complete failure. Furthermore, a range of maintenance actions are examined depending on the expected damage state. By taking into account the factor of cost, the developed probabilistic framework directly contributes to improve the current maintenance policies through the identification of the most optimized preventive or corrective actions while the safety of the structure is ensured.