Probability-based maintenance modeling and planning for reinforced concrete assets subjected to chloride ingress

Abstract

Chloride ingress into concrete is the primary cause of steel corrosion that leads to the deterioration of reinforced concrete (RC) assets and eventual reduction of its service life. The maintenance of RC buildings and structures has become a major concern, and thus the development of an effective maintenance plan is required. This study focuses on deterministic and probabilistic analysis of service life (or repair application time) for RC assets repaired by cover rebuilding techniques in extreme marine environments exposed to chloride attack. A maintenance model is developed, based on the mechanism of chloride transport in repaired concrete elements, that simulates different cover rebuilding methods and strategies. Computationally, the probability-based maintenance model combines the Latin Hypercube technique with finite element and finite difference methods. Probabilistic data for five governing random variables is considered, including diffusion coefficient, surface chloride concentration, concrete cover depth, concrete replacement depth, and critical chloride value for corrosion initiation. Two maintenance strategies are introduced, which can be categorized as corrective and preventive repair strategies. The deterministic study shows that a deeper repair depth leads to fewer repairs and larger repair intervals. The results of the probabilistic assessment reveal that a preventive repair model with regularly scheduled repair intervals efficiently decreases corrosion initiation risks. It was also demonstrated how shorter repair intervals and deeper depths of concrete repair can achieve an acceptable probability of corrosion initiation.