3D corrosion pattern analysis



Abstract: The 3D corrosion patterns of 23 reinforcing bars subjected to accelerated corrosion are characterised using an optical surface measurement technique. A stochastic signal processing methodology is employed for corrosion pattern analysis of the measured data. The statistical analysis of corrosion pattern data shows that a lognormal distribution model can represent the non-uniform distribution of pitted sections along the corroded bars. It was observed that the frequency of corrosion is independent from the mass loss ratio and the length of the bars. Finally, a set of probabilistic distribution models for the geometrical properties of corroded bars is developed.

Keywords: Steel reinforced concrete; Modelling studies; Pitting corrosion; Signal processing


Probabilistic modelling of corrosion deterioration using Markov chain based model



Abstract: Sounds infrastructure deterioration models are essential for accurately predicting their future condition for effective maintenance and rehabilitation strategy. The challenge of developing accurate deterioration models is that condition is often measured on a discrete scale, such as inspectors rating. Furthermore, deterioration is a stochastic process that varies widely with several factors, many of which are generally not captured by available data. Consequently, probabilistic discrete-state models are often used to characterize deterioration. Such models are based on transition probabilities that capture nature of the evolution of condition states from one discrete time point to the next.

In general, state-of-the art Bridge Management Systems (BMSs) have employed Markov chain models to predict the future condition of bridge elements and networks. However, it has not been used for prediction of level of chloride in bridge depth and corrosion initiation time. In this research a new approach using the concept of duration model has developed to predict the future condition of the level of chloride in concrete depth. In this approach firstly the time to corrosion initiation and the corresponding CDF are given from Fickian model and the using the same states as Fickian model the duration model is used to determine the transition probabilities for each state. Finally the overall methodology has been shown how to be used in BMS

Keywords: Markov chain; Chloride induced corrosion; Probabilistic; Fick's second law of diffusoin