Risk-based asset management of water piping networks using neurofuzzy systems

Christodoulou, Symeon E.; Deligianni, Alexandra; Aslani, Pooyan; Agathokleous, Agathoklis

doi:10.1016/j.compenvurbsys.2008.12.001

Cited by 61 publications

(24 citation statements)

References 11 publications

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“…Previous studies (US EPA 2006) showed that all these variables are factors (Table 9). The results of relevant studies in two other cities (New York and Limassol) showed that material, diameter, length and traffic were the most important risk factors in NY city, while previous breaks, diameter, material and traffic were the most important ones for Limassol case (Christodoulou and Deligianni 2010;Christodoulou et al 2009). -Although "Soil" considered as a stable variable (couldn't be ignored and excluded from further analysis), it proved not to be important enough (12/26 scenarios) (Table 8).…”

Section: Resultsmentioning

confidence: 96%

Pipe Networks Risk Assessment Based on Survival Analysis

Tsitsifli

Bakouros

2011

Water Resour Manage

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Integrated management of pipe networks should include methods for monitoring, repairing and replacing deteriorating components (usually pipes), but also methods and everyday operating practices towards a proactive risk assessment approach in order to give a solid answer to the unavoidable "repair or replace" dilemma. The present paper attempts to check whether the Discriminant Analysis and Classification (DAC) method can be used to achieve the above mentioned goals and predict the future behaviour of network pipes. Three pipe networks carrying different types of fluids (oil; gas; and water) are used as case studies. For each case study network, the DAC method is used to classify the pipes into two groups (failures/successes), based on simple variables (pipe/network characteristics) and dimensionless joint ones. Several scenarios are being analysed for each case. The results for the two cases of oil and gas networks are very satisfying. The implementation of the DAC method to water pipe networks needs to overcome serious problems related to the quality, reliability and compatibility of the data records provided by the Water Utilities. In this paper, these shortcomings are faced combining field data with theoretical one. Also the distinction between what "failure" and "success" actually mean in a water pipe network has to be determined. The present study uses the total water volume being lost as a definition criterion.

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Section: Resultsmentioning

confidence: 96%

Pipe Networks Risk Assessment Based on Survival Analysis

Tsitsifli

Bakouros

2011

Water Resour Manage

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“…Several findings on risk assessment and prioritization of 'repair-orreplace' actions were reported by Christodoulou et al (2009Christodoulou et al ( -2011 based on neurofuzzy systems, survival analysis and geospatial clustering of WDNs under both normal and abnormal operating conditions. Their findings reinforced, among other, the importance of risk factors such as pipe age, pipe diameter/length, pipe material and of the network operating conditions, and pointed out the importance of the number of previously observed breaks (NOPB) as a risk-of-failure factor.…”

Section: State Of Knowledgementioning

confidence: 97%

“…Furthermore, the NOPB is a risk factor which, by use of survival analysis, can account for incomplete data. The importance of the NOPB factor as a risk metric has been studied and reported upon extensively in the past (Christodoulou et al 2009, Christodoulou and Deligianni 2010, Christodoulou 2011, Christodoulou and Ellinas 2010.…”

Section: Analysis Of Water Distribution Networkmentioning

confidence: 99%

Seismic Reliability Assessment of Lifeline Systems

Christodoulou

Fragiadakis²

2014

Computing in Civil and Building Engineering (2014)

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A methodology is proposed for the seismic assessment of the reliability of urban water distribution networks (UWDN). The method is based on general seismic assessment standards, as per the American Lifelines Alliance (ALA) guidelines, and on localized historical records of critical risk-of-failure metrics. The proposed methodology is applicable to UWDN under either normal or abnormal operating conditions, and the assessment of reliability considers not only the vulnerabilities of the network components against seismic loading but also the topology of an UWDN and data of past non-seismic performance. This past performance, obtained using records of pipe burst incidents, is utilized with network-specific 'survival curves' in fine-tuning the generalized fragility curves suggested by the ALA. The resulting vulnerability analysis is used in devising 'repair-or-replace' strategies for the studied lifelines. INTRODUCTIONLifeline systems, such as water distribution networks, are of critical importance to the uninterrupted provision of services and thus to the resiliency of a city. Thus, being able to assess the reliability of the network against different hazards helps water distribution agencies prioritize their interventions and ensure a minimum reliability level of the network.A number of previous studies have assessed the vulnerability of infrastructure systems, but seldom has the non-seismic performance of such systems and the system-component interactions been considered in evaluating the seismic vulnerability of such systems. The process proposed in this paper combines data on historical non-seismic performance of urban water distribution networks (UWDN) and their components by use of survival analysis, simulation and a graph-based shortest-path algorithm. The intent is firstly to propose a methodology for assessing the vulnerability of a UWDN using available everyday measurements and secondly to extent the methodology of the American Lifelines Alliance guidelines (ALA 2001) with localized knowledge on the performance and vulnerability of such networks. The ALA guidelines present procedures and fragility relationships that can be used to evaluate the probability of earthquake damage to water transmission systems and to make informed decisions on how to mitigate risks. However, the generic form of the pipe fragility curves obtained through the ALA method does not take into consideration a network's past performance and its effects when calculating the pipe repair rates due to seismic loading. Furthermore, in examining the vulnerability of a network one cannot but consider the vulnerability of the network's components as well as the topology of the network.

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“…The term 'risk' is the cornerstone of the decision-making process (Christodoulou et al 2009). Risk is a combination of likelihood of failure and its associated consequences (Lawrence 1976;Sadiq et al 2005).…”

Section: Introductionmentioning

confidence: 99%

Prioritizing monitoring locations in a water distribution network: a fuzzy risk approach

Francisque

Rodriguez

Sadiq

et al. 2009

Journal of Water Supply: Research and Technology-Aqua

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Selecting and prioritizing monitoring locations (zones) in a water distribution network (DN) involves complex decision-making that warrants the use of risk-based decision-making. This paper couples the concept of risk with fuzzy sets and provides a simple approach to prioritizing monitoring locations in a DN. An index-based approach is proposed to estimate vulnerability, sensitivity and risk indices at a given DN location. The approach is based on fuzzy-based techniques that include fuzzy synthetic evaluation and fuzzy rule-base. Two types of analyses (deterministic and probabilistic) are used to demonstrate the proposed approach for a DN in Quebec City (Canada). Fifteen 'input factors' related to structural integrity, hydraulics, water quality and consumer sensitivity are used in the analyses. Based on the risk index results, the DN is divided into two parts. Sensitivity analysis results reveal that four factors, including two sensitivity factors (i.e. % population , 5 and . 75 yr) and two vulnerability factors (free residual chlorine and pipe breaks), explain 85% of the risk index variability. The usefulness of the proposed approach is demonstrated and strategies to improve the model are discussed.

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Risk-based asset management of water piping networks using neurofuzzy systems

Cited by 61 publications

References 11 publications

Pipe Networks Risk Assessment Based on Survival Analysis

Pipe Networks Risk Assessment Based on Survival Analysis

Seismic Reliability Assessment of Lifeline Systems

Prioritizing monitoring locations in a water distribution network: a fuzzy risk approach

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