Statistical modelling of carbonation in reinforced concrete

As time passes the properties of concrete change as a result of its interaction with the environment and durability is affected. Reinforcement corrosion is singled out in various studies as being mainly responsible for reinforced concrete degradation. Concrete alkalinity protects the reinforcement bars from corrosion but the carbonation phenomenon significantly contributes to the destruction of their passive coating, thus favouring the corrosion onset. Therefore, concrete carbonation is considered an important problem both in Civil Engineering and in Materials Science. This study’s main objective is to try to quantify the contribution of potential conditioning factors to concrete carbonation’s rate. This study addresses the statistical modelling of the concrete carbonation phenomenon, using a large number of results (964 case studies), collected in the literature. A computational method (multiple linear regression analysis) is used to define a mathematical model that can estimate the carbonation coefficient as a function of a set of conditioning factors. These models allow the estimation of the carbonation coefficient, and consequently the carbonation as a function of the variables considered statistically significant in explaining this phenomenon. Two distinct models are proposed to suit predictions to two environmental exposure relative humidity ranges.