Life-cycle reliability-based maintenance cost optimization of deteriorating structures with emphasis on bridges

The assessment of the current state and the prediction of the future condition of deteriorating structures are crucial processes in the management of civil infrastructure systems. Not only time-varying loads and resistances but also a series of maintenance interventions that are applied to keep structural systems safe and serviceable make the prediction process very difficult. In order to perform a realistic life-cycle analysis of deteriorating structures under different maintenance scenarios the uncertainties involved in this process have to be considered. This paper considers these uncertainties by providing a reliability-based framework and shows that the identification of the optimum maintenance scenario is a straightforward process. This is achieved by using a computer program for Life-Cycle Analysis of Deteriorating Structures (LCADS). This program can consider the effects of various types of actions on the reliability index profile of a group of deteriorating structures. Only the effect of maintenance interventions is considered in this study. However, any environmental or mechanical action affecting the reliability index profile can be considered in LCADS. Most input data are represented by random variables. In this manner, the uncertainties included in maintenance interventions, reliability index profiles, and cost evaluations are all taken into account. The present value of the expected cumulative cost associated with maintenance interventions can be evaluated for both an individual structure and a group of similar structures. Optimization and parametric analysis modules help the identification of the maintenance strategy that best balance cost and reliability index profile over a specified time horizon. Numerical examples of deteriorating bridges are presented to illustrate the capability of the proposed approach. Further development and implementation of this approach are recommended for future research.