Numerical modeling for predicting service life of reinforced concrete structures exposed to chloride

In recent decades, there has been a growing interest in predicting the service life of reinforced concrete structures vulnerable to chloride-induced corrosion. The service life is divided into initiation and propagation phases, considering the de-passivation of the reinforcement's protective film as a threshold for active corrosion. However, it is observed that the corrosion process is gradual, requiring considerable time before significant damage occurs. This research presents a comprehensive numerical model that incorporates both passive and active corrosion contributions to predict the service life. The model utilizes a finite difference approach to simulate transportation processes, corrosion current, and rust growth. Time-varying boundary conditions, including relative humidity, temperature, and surface chloride concentration, are considered in solving the partial differential equation governing the transportation processes. The incorporation of both passive and active corrosion contributions, as well as the consideration of time-varying boundary conditions, enhances the accuracy of the predictions. Sensitivity analysis is conducted to evaluate the effects of corrosion rate, cross-section loss rate, and service life, considering variations in relative humidity, temperature, water-to-cement ratio, and cover depth. The results highlight the significant impact of relative humidity and water-to-cement ratio on corrosion rate and cross-section loss. Changing the water-to-cement ratio from 0.5 to 0.4 was observed to double the overall service life of an identical structure. Additionally, cover depth was identified as a crucial factor affecting the service life of the structure. Changing the cover depth from 40 mm to 80 mm enhanced service life by three and a half times in the present case study. Temperature fluctuations had a relatively minor effect within acceptable limits, allowing the use of average temperatures for service life estimation, particularly in coastal regions. The comprehensive model presented can provide aid in informed decision-making for corrosion prevention and mitigation strategies in practice.