Integrating WRc and CERIU Condition Assessment Models and Classification Protocols for Sewer Pipelines
Publication: Journal of Infrastructure Systems
Volume 17, Issue 3
Abstract
Adoption of a suitable sewer pipeline condition classification protocol is recognized as an indispensable first step in worldwide sewer rehabilitation industry. Various condition classification systems for sewers have been developed in this regard. These systems differ according to local requirements in which no integrated and unified sewer condition assessment protocol is available. Therefore, an urgent need exists to develop standardized sewer condition assessment procedures. The presented research in this paper aims to review the historical development of different sewer condition classification protocols and develop a combined condition index (CCI) for sewers that integrates the combined effect of structural and operational conditions. To achieve these objectives, unsupervised neural network models have been developed. The CCI is divided into five condition categories ranging from “acceptable” to “critical.” An unsupervised, self-organizing, neural network approach is also used to develop the CCI. The opinion of municipal practitioners is utilized to verify the CCI and integrated protocol. The developed integrated models and protocols will assist municipal engineers in developing a unified sewer condition assessment system. An unsupervised neural network methodology is adapted for integrating sewer condition assessment protocols and developing the CCI of sewer pipelines. The protocols developed by the Water Research Centre (WRc), United Kingdom, and the Centre for Expertise and Research on Infrastructures in Urban Areas (CERIU), Canada, have been used for the modeling process.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors would like to express gratitude to the Quebec funding agency Fonds Québécois de la Recherche sur la Nature et les Technologies (NATEQ/FQRNT) for its appreciated financial support to this research. They would also like to extend appreciation to all municipal engineers who facilitated the authors’ research by positive participation and providing the required data, particularly the Niagara Falls, Ontario, and Pierrefonds, Quebec, municipalities.
References
Archilla, A. R., and Madanat, S. (2001). “Estimation of rutting models by combining data from different sources.” J. Transp. Eng., 127(5), 379–389.
Ben-Akiva, M., Humplick, F., Madanat, S., and Ramaswamy, R. (1993). “Infrastructure management under uncertainty: latent performance approach.” J. Transp. Eng., 119(1), 43–58.
Centre for Expertise and Research on Infrastructures in Urban Areas (CERIU). (2004). Manuel de Standardization des Observations, 2nd Ed., CERIU, Montreal, Quebec, Canada (in French).
Chughtai, F. (2007). “Integrated condition assessment models for sustainable sewer pipelines.” M.S. thesis, Dept. of Building, Civil, and Environmental Engineering, Concordia Univ., Montreal, Canada.
Chughtai, F., and Zayed, T. (2008). “Infrastructure condition prediction models for sustainable sewer pipelines.” J. Perform. Constr. Facil., 22(5), 333–341.
City of Edmonton. (1996). Sewer physical condition classification manual, Transportation Dept., Drainage Engineering Section, City of Edmonton, Canada.
City of Winnipeg. (2001). “Sewer management study: Technical memoranda for sewer condition assessment, sewer rehabilitation design, and sewer maintenance management for the City of Winnipeg, Canada.”
Deboeck, G., and Kohonen, T. (1998). Visual exploration in finance with self organizing maps, Springer, London.
Gallant, S. (1993). Neural network learning and expert systems, MIT, Cambridge, MA.
Kohonen, T. (1993). “The things you haven’t heard about the self organizing map.” Proc., IEEE Conf., Vol. 5, Piscataway, NJ.
Kohonen, T. (1997). Self organizing maps, 2nd Ed., Springer, Berlin.
Minitab [Computer software]. (2002). “Using best subsets regression.” Minitab Inc., State College, PA.
New Zealand Water and Waste Water Association (NZWWA). (2006). New Zealand pipe inspection manual, 3rd Ed., NZWWA, Wellington, New Zealand.
Rahman, S., and Vanier, D. (2004). “An Evaluation of condition assessment protocols for sewer management.” Research Rep. No. B-5123.6, National Research Council (NRC) of Canada, Ottawa, ON, Canada.
Rustum, R., and Adeloye, A. J. (2007). “Replacing outliers and missing values from activated sludge data using Kohonen self-organizing map.” J. Environ. Eng., 133(9), 909–916.
Schatzmann, J., and Ghanem, M. (2003). “Using self-organizing maps to visualize clusters and trends in multidimensional datasets,” Case Project Rep., Imperial College, London, UK.
Shahin, M., Mair, H., and Jaksa, B. (2004). “Data division for developing neural networks applied to geotechnical engineering.” J. Comput. Civ. Eng., 18(2), 105–114.
Thornhill, R., and Wildbore, P. (2005). “Sewer defect codes: Origin and destination.” 〈http://www.nassco.org/training_edu/pdfs/040105_utech.pdf〉.
Water Research Centre (WRc). (2004). Sewerage rehabilitation manual, 4th Ed., WRc, Wiltshire, U.K.
Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 17 • Issue 3 • September 2011
Pages: 129 - 136
Copyright
© 2011 American Society of Civil Engineers.
History
Received: Nov 13, 2008
Accepted: Nov 6, 2010
Published online: Aug 15, 2011
Published in print: Sep 1, 2011
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.