Transient response analysis of steel in concrete

A new approach is presented for the analysis of galvanostatically induced transients allowing for the rapid evaluation of the corrosion activity of steel in concrete. This method of analysis is based on the iterative fitting of a non-exponential model based on a modified KWW (Kohlrausch–Williams–Watt) formalism. This analysis yields values for the parameters related to corrosion such as the concrete resistance, polarisation resistance, interfacial capacitance and β, the non-ideality exponent.

Concentration monitoring and performance of a migratory corrosion inhibitor in steel-reinforced concrete

Inhibitor concentration depth profiles for concrete samples treated with a proprietary migratory corrosion inhibitor (of the Cortec MCI range) are presented. The treated concrete was cored and these cores were then sectioned and crushed before being immersed in distilled water to extract the available inhibitor. The amine concentrations were quantified using an ammonium-sensing electrode and were then related to the inhibitor concentration present. The inhibitor examined, reported to contain a combination of volatile amines and amino carboxylate compounds, was found to readily diffuse through concrete. The inhibitor was subjected to a 5-year trial and found to be effective in suppressing corrosion of steel reinforcement in the presence of high chloride concentrations. The concentration profiles indicate that only relatively low concentrations of inhibitor were required to achieve inhibition in this case.

Application of neural networks in modelling serviceability deterioration of concrete stormwater pipes

Stormwater pipe systems in Australia are designed to convey water from rainfall and surface runoff only and do not transport sewage. Any blockage can cause flooding events with the probability of subsequent property damage. Proactive maintenance plans that can enhance their serviceability need to be developed based on a sound deterioration model. This paper uses a neural network (NN) approach to model deterioration in serviceability of concrete stormwater pipes, which make up the bulk of the stormwater network in Australia. System condition data was collected using CCTV images. The outcomes of model are the identification of the significant factors influencing the serviceability deterioration and the forecasting of the change of serviceability condition over time for individual pipes based on the pipe attributes. The proposed method is validated and compared with multiple discriminant analysis, a traditionally statistical method. The results show that the NN model can be applied to forecasting serviceability deterioration. However, further improvements in data collection and condition grading schemes should be carried out to increase the prediction accuracy of the NN model.