The greenhouse gases (GHGs), in terms of CO2 emissions, have influenced the climate system by altering the planet's temperature and relative humidity (RH) patterns creating global warming. Reinforced concrete Predictive models Service life Reinforcement corrosion Chlorides Although all models are a simplification of reality, attached some considerations and limitations, there was an evolution of predictive models to higher levels of complexity. Besides that, supplementary analyzes were made, such as the methods for calculating the diffusion coefficient (D), the critical contents (Ccr) used, the consideration of the non-saturation of the concrete by the models, chloride binding, cracks, the direction of penetration of the chlorides, among others. Among the probabilistic models, the most used numerical method was the Monte Carlo simulation. In addition, 72% of the models are analytical. As a result, it was observed that most of the models considered are based on Fick’s Second Law, modified or not modified. This article contemplates part 2 of the Systematic Literature Review (RSL) results with the aim of describing, analyzing and classifying the selected models in deterministic or probabilistic and in empirical, analytical and/or numerical models. The application of these models can improve the efficiency and optimization of the design and service life of reinforced concrete structures. Several models for predicting the service life of reinforced concrete structures model the entry of aggressive agents, such as chlorides, generally based on modified diffusion laws or on multi chemical species transport models, considering different parameters. Finally, parameter analyses are used to identify the effects of individual parameters, including external load level, supplementary cementitious materials and environmental temperature, on the probability of corrosion failure of RC beams over time. Numerical experiments show that the probability of corrosion failure is significantly underestimated if the coupled degradation effect of cracks and corrosion is not considered. To enable an efficient probabilistic assessment, a novel rapid numerical approach (RNA) is implemented for modeling the chloride diffusion. In this work a stochastic model is presented which couples degradation effects of crack development and corrosion progression based on physicochemical and mechanical models to estimate the probability of failure of a RC structure over time. Chloride-induced corrosion is thus one of the most serious threats. RC structures undergo continuous deterioration due to a combination of chloride ingress and loading actions. Most of the existing infrastructures (e.g., oversea bridges) are made of reinforced concrete (RC) therefore, their safety is of high priority for our society.
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