Prediction of Timing of Watermain Failure Using Gene Expression Models

Ahmed Sattar (), B. Gharabaghi () and Edward McBean ()

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 5, 1635-1651

Abstract: An innovative predictive equation characterizing watermain failure timing developed from datasets of historical failures in Greater Toronto Area (GTA), Ontario, Canada is described. Gene expression programming (GEP) is used to develop empirical relations between the time to failure and control variables including protection methods for three types of pipes, Cast Iron, Ductile Iron, and Asbestos Cement. The developed GEP model has a correlation coefficient of 0.68, and with the advantage for predicting not only the time to first break, but also subsequent breaks. The prediction uncertainties of the developed GEP were 38 % of the median value for time to next failure. A parametric analysis is performed for further verification of the developed GEP model showing the relation is simple, yet effectively forecasts watermain timing to first failure and subsequent failures. Simulated failure scenarios indicate a return to high failure rates if cement mortar lining and cathodic protection are not extended to all candidate pipes in the distribution system. Copyright Springer Science+Business Media Dordrecht 2016

Keywords: Infrastructure; Watermain; Pipe failure; Prediction; Data mining; Gene expression programming; Asset rehabilitation (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11269-016-1241-x

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