Non-uniform Corrosion Mechanism and residual life forecast of marine engineering concrete reinforcement

Reinforced concrete structures are commonly employed in civil engineering due to their low cost and high performance. However, their exposure to the marine environment, which is typically characterized by elevated salt content and humidity levels, heightens the probability of corrosion. Such corrosion can lead to a decrease in the service life of these structures, which is of utmost importance to predict in order to prevent potential safety hazards. To address this issue, this study investigated the corrosion mechanism of reinforced concrete structures in the marine environment and found Cl- concentration to be the most critical parameter for the corrosion of steel. Afterward, a predictive model is proposed based on the Back Propagation Artificial Neural Network (BPANN) to estimate the residual service life of reinforced concrete structures in different marine environments by forecasting the Cl- concentration in reinforced concrete components. The results demonstrate the high accuracy of the proposed BPANN model, with a maximum relative error of 6.292 %. Consequently, the residual service life forecast system of reinforced concrete structures proposed in this study can provide useful guidance based on the simplistic framework for designing concrete structures in the marine environment by predicting their effective service life. Thus, this study provides valuable insights for promoting the safety and economic benefits of reinforced concrete structures in the marine environment.