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The sulphuric acid is a known growing threat to concrete sewer pipes. Acid production is dictated by rapid urbanisation, increased use of hot water and discharge of toxic metals and sulphate containing detergents into the wastewater. Concrete sewer pipe corrosion due to sulphuric attack is known to be the main contributory factor of pipe degradation. Very little tools are available to accurately predict the corrosion rate and most importantly the remaining safe life of the asset. This paper proposes a new robust model to predict the sewer pipe corrosion rate due to sulphuric acid. The model makes use of a powerful Evolutionary Polynomial Regression method that provides a new methodology of hybrid data-mining. The results obtained by the model which was validated in the field indicates that the proposed hybrid methodology can accurately predict the corrosion rate in concrete sewer pipe’s given that the pipe installation conditions as well as in-pipe sewage conditions are known.


Session R56, Water Distribution Networks: Infrastructure Health



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