Condition Rating Model for Underground Infrastructure Sustainable Water Mains
Publication: Journal of Performance of Constructed Facilities
Volume 20, Issue 2
Abstract
One of the greatest challenges facing municipal engineers is the condition rating of buried infrastructure assets, particularly water mains. This is because water mains are typically underground, operated under pressure, and usually inaccessible. Condition rating is a mandatory process to establish and employ management strategies for any asset. To assess the condition of water mains, current research considers physical, environmental, and operational factors and their effect on different types of mains (i.e., cast iron, ductile iron, and asbestos). A condition rating model is developed to assess and set up rehabilitation priority for water mains using the artificial neural network (ANN) approach. Data are collected from different municipalities to train the developed model. The ANN input factors incorporate pipe type, size, age, breakage rate, Hazen-Williams factor, excavation depth, soil type, and top road surface; however, the output is pipe condition. The trained ANN shows robust performance (learning , , correlation coefficient ). Results show that the breakage rate has the highest relative contribution factor among the others. The developed model is relevant to researchers and practitioners (municipal engineers, consultants, and contractors) in order to prioritize pipe inspection and rehabilitation planning for existing water mains.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The writers would like to express their gratitude to the Quebec funding agency NATEQ/FQRNT (Fonds Québécois de la Recherche sur la Nature et les Technologies) for its appreciated financial support to the current research. They would also like to extend their gratitude to all municipal engineers who facilitated the writers’ research by positive participation and providing the required data.
References
American Water Works Association (AWWA). (1989). “Distribution network analysis for water utilities.” Manual no. M32, Denver.
ASCE. (2005). “Report card for America’s infrastructure.” ⟨http://www.asce.org/reportcard/2005/page.cfm⟩ (Nov. 28, 2005).
Baer, N. (1998). “Buried treasures: NRC’s Institute for Research in Construction develops new ways to evaluate the performance of underground pipes.” Can. Consult. Eng., 39(2), 41–43.
Best Practices. (2003a). “Best practices for utility-based data.” Best Practice by the National Guide to Sustainable Municipal Infrastructure, Issue No. 1.0, Ottawa.
Best Practices. (2003b). “Deterioration and inspection of water distribution systems.” Best Practice by the National Guide to Sustainable Municipal Infrastructure, Issue No. 1.1, Ottawa.
Blaga, A. (1973). “Properties and behavior of plastics.” Rep. No. 157-CBD, National Research Council Canada, Ottawa.
Blaga, A. (1981). “Use of plastics as piping materials.” Rep. No. 219-CBD, National Research Council Canada, Ottawa.
Blaga, A. (1982). “Reinforced thermosetting plastic pipe.” Rep. No. CBD-227, National Research Council Canada, Ottawa.
Department of the Environment. (1998). “Deterioration of asbestos cement water mains (MSS 9731 SLD).” Rep. No. DWI0131, London, ⟨http://www.fwr.org/pipeline/dwi0131.htm⟩ (Mar. 8, 2005).
Dikmen, I., Birgonul, M., and Kiziltas, S. (2005). “Prediction of organizational effectiveness in construction companies.” J. Constr. Eng. Manage., 131(2), 252–261.
Kleiner, Y., and Rajani, B. (2001). “Comprehensive review of structural deterioration of water mains: Statistical models.” Urban Water, 3(3), 131–150.
Kleiner, Y., and Rajani, B. (2002). “Forecasting variations and trends in water-main breaks.” J. Infrastruct. Syst., 8(4), 122–131.
Makar, J. M., and Kleiner, Y. (2000). “Maintaining water pipeline integrity.” Proc., AWWA Infrastructure Conf. and Exhibition, Baltimore.
Moselhi, O., and Shehab-Eldeen, T. (2000). “Classification of defects in sewer pipes using neural networks.” J. Infrastruct. Syst., 6(3), 97–104.
Rajani, B., and Kleiner, Y. (2001). “Comprehensive review of structural deterioration of water mains: Physically based models.” Urban Water, 3(3), 151–164.
Rajani, B., and Kleiner, Y. (2004). “Non-destructive inspection techniques to determine structural distress indicators in water mains.” Proc., Conf. on Evaluation and Control of Water Loss in Urban Water Networks, Valencia, Spain, 1–20.
Sadiq, R., Kleiner, Y., and Rajani, B. B. (2004). “Fuzzy cognitive maps for decision support to maintain water quality in aging water mains.” DMUCE 4, Proc., 4th Int. Conf. on Decision-Making in Urban and Civil Engineering, Porto, Portugal, 1–10.
Saint-Gobain Pipelines Inc. (2002). ⟨http://www.saint-gobain-pipelines.co.uk/water/sewer/pipesfittings.cfm⟩ (Mar. 8, 2005).
Tsoukalas, L. H., and Uhrig, R. E. (1997). Fuzzy and neural approaches in engineering, Wiley, New York.
Zayed, T., and Halpin, D. (2005). “Pile construction productivity assessment.” J. Constr. Eng. Manage., 131(6), 705–714.
Information & Authors
Information
Published In
Copyright
© 2006 ASCE.
History
Received: Oct 5, 2005
Accepted: Dec 20, 2005
Published online: May 1, 2006
Published in print: May 2006
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.