Probabilistic Life-Cycle Optimization of Durability-Enhancing Maintenance Actions: Application to FRP Strengthening Planning

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Engineering Structures

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The large number of deteriorating bridges and the goal of sustainable development mean that maintenance actions should not only effectively improve the current condition of bridges but also enhance post-maintenance durability. In this paper, a probabilistic life-cycle optimization method is proposed for the planning of this type of maintenance actions. A physics-based deterioration model is directly employed in the optimization process. The computational efficiency of the proposed method is ensured by efficient sampling algorithms, multi-objective particle swarm optimization, and a bookkeeping technique. The proposed method can provide bridge maintenance schedules that account for two conflicting objectives, i.e. the maximization of life-cycle performance and the minimization of maintenance cost. A deteriorating RC bridge superstructure under chloride-induced corrosion is used to illustrate the proposed method. Point-in-time and cumulative-time failure probabilities are compared as life-cycle performance indicators. As an example of maintenance actions that enhance durability, FRP strengthening implementations for different structural components of the superstructure are scheduled during the service life of the deteriorating superstructure.


© 2019 Elsevier



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