The lack of sufficient historical data on the deterioration of buried critical infrastructure such as large-diameter transmission water mains and trunk sewers is an obstacle to formulating an effective strategy for managing its failure risk. These historical data are required to model rates of deterioration in order to anticipate and prevent future failures without resorting to frequent inspections that are both very costly and disruptive.
At the National Research Council of Canada (NRC) we have developed a new fuzzy-based approach to model the deterioration of buried critical infrastructure using scarce data. Fuzzy synthetic evaluation is used to discern the 'condition rating' of an asset by aggregating the effects of various distress indicators observed (or estimated) during inspection. A rule-based fuzzy Markov model is used to replicate and predict the possibility of failure. The possibility of failure is combined with fuzzy failure consequences to obtain the fuzzy risk of failure throughout the life of the asset. The fuzzy risk model can be used to plan the renewal of the asset subject to maximum risk tolerance. Additionally, renewal strategies that could include various technologies as well as various scheduling schemes can be compared on discounted costs and maximum risk, to arrive at decisions that are commensurate with the preferences of the decision maker. The concepts are demonstrated using data obtained for a prestressed concrete cylinder pipe (PCCP). Results are discussed as well as model limitations and future research needs.
This paper provides a summary of the research. Technical details have been published elsewhere in refereed journals as well as conferences. The research was conducted with financial support from the American Water Works Association Research Foundation (AwwaRF) and NRC.
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