A sensitivity analysis of predictive modelling for chloride diffusion in reinforced concrete structures

Abstract

The corrosion of steel due to chloride ingress is one of the major causes of deterioration of reinforced concrete structures. In order to ensure a structure achieves the design life specified, predictive modelling is employed. To undertake this modelling, details are required on a number of variables; however, each of these variables has a level of uncertainty which can affect the reliability of the model. To address these issues, this paper reports the analysis of data taken from four distinct elements on a port structure, in Australia, constructed in three phases between 1926 and 1985, using both pre-cast and cast in situ techniques. The cover depth, surface chloride concentration and chloride diffusion coefficient were determined for different elements on the structure, with a total of 244 data points obtained. The data was analysed to identify the statistical distributions and probability density functions produced. A novel analytical model was developed based on the solutions to Fick's equation. The results showed that both surface chloride and the diffusion coefficient were positively skewed with no significant variation in the sensitivity. It was also found that controlling the diffusion coefficient has a more influential effect than increasing the cover.