Comparison of Statistical Models for Predicting Pipe Failures: Illustrative Example with the City of Calgary Water Main Failure
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 6, Issue 4
Abstract
Several statistical models have been proposed to study effects of different covariates in the failure of water pipes. In this paper, three statistical models, the Weibull proportional hazard model (WPHM), the Cox proportional hazard model (Cox-PHM), and the Poisson model (PM), were considered. Curve fitting techniques were proposed for estimation of a baseline hazard function equation for the Cox-PHM to allow for its application in break prediction. The water main failure in the City of Calgary is used for this study. From the statistical models, physical covariates (e.g., pipe diameter, length) compared with environmental covariates (e.g., temperature) were the critical factors impacting the pipe failure rate. Furthermore, WHPM and PM showed the best fit for prediction of metallic and PVC pipes, respectively. Pipe break prediction through estimation of baseline hazard by curve fitting techniques produces good results especially for a young system. This study recommends that a combination of models rather than a single model be used in assessing pipe network condition based on the rate of deterioration and material type of the system.
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Acknowledgments
The authors would like to thank the City of Calgary water utility for providing data. The first author acknowledges the Canadian Commonwealth Scholarship Program (CCSP) for allowing him to carry out this research at University of British Columbia (Okanagan Campus).
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Information & Authors
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Published In
Journal of Pipeline Systems Engineering and Practice
Volume 6 • Issue 4 • November 2015
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Dec 4, 2013
Accepted: Nov 26, 2014
Published online: Jan 27, 2015
Discussion open until: Jun 27, 2015
Published in print: Nov 1, 2015
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