Prediction models for sewer infrastructure utilizing rule-based simulation

Management of infrastructure projects is becoming increasingly challenging due to inherent uncertainties. The most effeective way to deal with uncertainty is to collect supplementary information and knowledge. When expensive or infeasible, quantification of uncertainty may be performed using analyti...

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Bibliographic Details
Published inCivil engineering and environmental systems Vol. 21; no. 3; pp. 169 - 185
Main Authors Ruwanpura, Janaka, Ariaratnam, Samuel T., El-assaly ‡, Ashraf
Format Journal Article
LanguageEnglish
Published Reading Taylor & Francis 01.09.2004
Taylor and Francis
Subjects
Applied sciences
Buildings. Public works
Civil systems
Computation methods. Tables. Charts
Exact sciences and technology
Infrastructure
Modeling
Sewer rehabilitation
Sewerage. Sewer construction
Simulation
Structural analysis. Stresses
Canada
North America
America
Combined sewer
Monte Carlo method
Data analysis
Costs
Uncertainty
Project management
Forecast model
Modeling
Recommendation
Civil systems
Simulation
Sewer rehabilitation
Deterioration
Infrastructure
Sewer network
Rehabilitation
Data gathering
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Summary:Management of infrastructure projects is becoming increasingly challenging due to inherent uncertainties. The most effeective way to deal with uncertainty is to collect supplementary information and knowledge. When expensive or infeasible, quantification of uncertainty may be performed using analytical or simulation techniques. The City of Edmonton, Canada has approximately 4600 km of sewer pipes in the combined, sanitary, and storm sewer local systems with uncertainty issues related to deterioration. The City has taken a proactive approach with respect to sewer rehabilitation, as it is more cost-effeective to repair a defective pipe prior to failure rather than after a collapse. This article demonstrates an approach for predicting the condition of a sewer pipe and the related cost of rehabilitation, given the limited data. Three models are described in this article that are developed to assist the City of Edmonton to effeectively plan maintenance expenditure. Each model uses a combination of rule-based simulation and probability analysis to assist in the planning of future expenditures for sewer maintenance, thereby producing an invaluable planning tool. Tel.: 780-440-7188, E-mail: ashraf.el-assaly@ue-1.com Tel.: 403-220-6892; E-mail: janaka@ucalgary.ca
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:1028-6608
1029-0249
DOI:10.1080/10286600410001694192