Abstract
This paper presents a new algorithm that predicts the service life of concrete contains supplementary cementitious materials, SCMs, and determines time of corrosion initiation. The algorithm drives effective diffusivity from an apparent diffusion model, using experimental binding data performed in the lab, temperature, free ion concentration, and carbonation, and generates free chloride profiles for concrete with and without SCMs by using Fick’s law in a finite element model. Adjusting diffusion coefficient at each step of the solution, by addressing the impact of different parameters, simplifies the algorithm and reduces calculation time without jeopardizing the results’ quality. Results generated by the model compare well to the performance of concrete blocks constructed in an exposure site on the east coast of Saudi Arabia. The exposure site hosted five different mixes of Portland cement and SCMs, and the concrete blocks were exposed to harsh weather over the period of two years. Linear polarization and chloride profiling assessed the performance of the mixes against corrosion activities. Lab work identified the performance of the mixes through binding capacity and chloride profiling. Statistical analysis evidenced the accuracy of the model through correlation and regression analysis. Furthermore, a new proposed binding model, produced from binding data in different studies, alters the experimental binding data in the algorithm to decouple the solution from experimental values. The algorithm proves its accuracy when compared to the experimental free chloride profile. The proposed transport model proves that using effective diffusion and binding capacity are enough to generate reliable results, and the effective diffusion can be calibrated with environmental conditions such as temperature, age, and carbonation. Finally, the algorithm presents its features in an object-oriented programming using C# and user friendly web interface.
Highlights
Concrete remains the most widely used material around the world with over six billion tons of concrete used to establish the required infrastructures
By using the multi-factor approach to express the diffusion coefficient of chloride ion and by incorporating the chloride binding capacity given in Equation (14) into the effective diffusion model of Equation (5), a more accurate expression for chloride transport in concrete can be achieved leading to more realistic prediction of time to corrosion initiation in reinforced concrete
This paper develops a new model for predicting the effective concrete diffusivity which uses the apparent diffusion along with binding, age, temperature, carbonation, and free chloride effects
Summary
Concrete remains the most widely used material around the world with over six billion tons of concrete used to establish the required infrastructures. Riding et al [25] developed a model for chloride concentration that used the apparent diffusion coefficient and Fick’s second law of diffusion using finite difference and validated their model against results from concrete blocks exposed to marine environment for 25 years They pointed out that diffusion is the main chloride transport mechanism for concrete exposed to water and chloride. Fenaux et al [16] have shown that using solely diffusion and chloride binding generates good results They pointed out the difficulty of distinguishing whether the variation of the apparent diffusion coefficient was based on the microstructure or binding capacity of the concrete. The present work uses Fick’s law of diffusion and the effective diffusion coefficient, which accounts for effects of age, temperature, carbonation, free chloride, and experimental binding capacity, to predict free chloride concentrations along the depth of concrete using 1D finite element modeling. The transport model was incorporated into user friendly software application developed using object-oriented based C-Sharp programming language
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
