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Predicting risk of water quality failures in distribution networks under uncertainties using fault-tree analysis
The water quality in a distribution system is affected by many factors, including operational and environmental conditions as well as the condition in and around the distribution network. Lack of reliable data as well as knowledge gaps with respect to the impact of these factors on water quality make the quantification of water quality failure risk very challenging. Furthermore, the variability inherent in (sometimes) thousands of kilometers of distribution pipes presents added complexities. Major modes of water quality failures can be classified into intrusion of contaminants, regrowth of bacteria (biofilm), water treatment breakthrough, leaching of chemicals or corrosion products from system components, and permeation of organic compounds through plastic pipes. Deliberate contamination and negligence of operators have in recent years become an added concern. In earlier works by Sadiq et al. (2004, 2007), an aggregative risk analysis approach using hierarchical structure was proposed to describe all possible mechanisms of contamination. In this paper a similar structure is used as a basis for a fault-tree approach. While fault-tree analysis is widely used for many engineering applications, in this paper we specifically explore how interdependencies among factors might impact analysis results. Two types of uncertainties are considered in the proposed analysis. The first is related to the likelihood of risk events, and the second is related to non-linear dependencies among risk events. Each basic risk event (input factor) is defined using a fuzzy probability (likelihood) to deal with its inherent uncertainty. The dependencies among risk events are explored using Frank copula and Frechet's limit. The proposed approach is demonstrated using two well-documented episodes of water quality failures in Canada, namely, Walkerton (ON) and North Battleford (SK).
Predicting risk of water quality failures in distribution networks under uncertainties using fault-tree analysis
The water quality in a distribution system is affected by many factors, including operational and environmental conditions as well as the condition in and around the distribution network. Lack of reliable data as well as knowledge gaps with respect to the impact of these factors on water quality make the quantification of water quality failure risk very challenging. Furthermore, the variability inherent in (sometimes) thousands of kilometers of distribution pipes presents added complexities. Major modes of water quality failures can be classified into intrusion of contaminants, regrowth of bacteria (biofilm), water treatment breakthrough, leaching of chemicals or corrosion products from system components, and permeation of organic compounds through plastic pipes. Deliberate contamination and negligence of operators have in recent years become an added concern. In earlier works by Sadiq et al. (2004, 2007), an aggregative risk analysis approach using hierarchical structure was proposed to describe all possible mechanisms of contamination. In this paper a similar structure is used as a basis for a fault-tree approach. While fault-tree analysis is widely used for many engineering applications, in this paper we specifically explore how interdependencies among factors might impact analysis results. Two types of uncertainties are considered in the proposed analysis. The first is related to the likelihood of risk events, and the second is related to non-linear dependencies among risk events. Each basic risk event (input factor) is defined using a fuzzy probability (likelihood) to deal with its inherent uncertainty. The dependencies among risk events are explored using Frank copula and Frechet's limit. The proposed approach is demonstrated using two well-documented episodes of water quality failures in Canada, namely, Walkerton (ON) and North Battleford (SK).
Predicting risk of water quality failures in distribution networks under uncertainties using fault-tree analysis
Sadiq, R. (Autor:in) / Saint-Martin, E. (Autor:in) / Kleiner, Y. (Autor:in)
Urban Water Journal ; 5 ; 287-304
01.12.2008
18 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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