PipelineNet: A Model for Monitoring Introduced Contaminants in a Distribution System

Bahadur, Rakesh; Samuels, William B.; Grayman, Walter M.; Amstutz, David E.; Pickus, Jonathan M.

doi:10.1061/40685(2003)128

Cited by 25 publications

(8 citation statements)

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“…Laird et al (2004) and Van Bloemen Waanders et al (2003) use dynamic optimization approaches and nonlinear programming to identify the time and location of contamination. Bahadur et al (2001Bahadur et al ( , 2003 developed the PipelineNet model that simulates the transport of contaminants in water distribution systems.…”

Section: Literature Reviewmentioning

confidence: 99%

Minimizing the Consequences of Intentional Attack on Water Infrastructure

Jeong

Qiao

Abraham³

et al. 2006

Comp-aided Civil Eng

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Since September 11, 2001, protecting the nation's water infrastructure and improving water network resiliency have become priorities in the water industry. In this work, we develop methods to mitigate the consequences of water shortage resulting from destruction of facilities in water networks. These methods integrate search techniques, such as branch‐and‐bound and genetic algorithms, with a hydraulic solver to check demand feasibilities across a residual water network. The objective is to identify a feasible customer demand pattern that minimizes the consequences of water shortage in the downgraded network. We present a mathematical model of the problem addressed along with an exact solution methodology and several heuristics. We apply these methodologies to three water networks ranging in size from approximately 10–700 nodes and compare the solution quality and computational efficiency.

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Section: Literature Reviewmentioning

confidence: 99%

Minimizing the Consequences of Intentional Attack on Water Infrastructure

Jeong

Qiao

Abraham³

et al. 2006

Comp-aided Civil Eng

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“…Other studies have combined modelling of contaminant transport in saturated and unsaturated zones with pipe condition assessments in a GIS-based risk assessment (Sargaonkar et al, 2013;Vairavamoorthy et al, 2007). Populations at risk, sensitive consumers, hydraulics and water quality parameters were furthermore combined in a ranking procedure to locate monitoring sites in a DS (Bahadur et al, 2003;Lindley and Buchberger, 2002). This multi-objective approach is common to all the GIS-based research.…”

Section: Introductionmentioning

confidence: 99%

GISMOWA: Geospatial Risk-Based Analysis Identifying Water Quality Monitoring Sites in Distribution Systems

Larsen

Christensen²,

Albrechtsen³

et al. 2017

J. Water Resour. Plann. Manage.

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Monitoring water quality in drinking water distribution systems is the base for pro-active approaches to prevent or manage emerging water quality issues, and such a monitoring requires a strategic selection of relevant and representative monitoring sites. GISMOWA is a new GIS and risk-based analysis tool to identify and to prioritise pipe segments for water quality monitoring and to comply with existing monitoring and sampling guidelines. The tool was designed to integrate multiple parameters categorized as 1) Hydraulic and structural weaknesses in the system, e.g. residence time, 2) External threats, e.g. contaminated sites, and 3) Sensitive consumers, e.g. hospitals in a GIS environment. The tool used a multi-criteria decision analysis to evaluate multiple monitoring site parameters and map zones particularly suitable for water quality monitoring. GISMOWA was applied to Danish water distribution systems as a transparent and simple-to-use tool which facilitated a complete overview of the distribution system, including sensitive consumers and consumers in general, and thus fulfilling a precondition for a HACCP-based monitoring strategy of drinking water.

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“…2) is a network-based software tool with integrated data base capability that can be used to model the f low and concentration of contaminants in a city's drinking water pipeline infrastructure. [7,8] The application contains a pipe network hydraulic model (EPANET), user defined and selected critical facility locations and a US Census population database. The application permits the user to model the flow and concentration of a biological, chemical or radiological agent within a city or municipal water system and calculate the population and critical facilities at risk.…”

Section: Introductionmentioning

confidence: 99%

The Integration of Network-Based Models for Spill Response and Homeland Security

Amstutz¹,

Bahadur²,

Pickus³

et al. 2008

American J. of Environmental Sciences

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The integration of three hydraulic GIS (Geographic Information System) applications is presented which represent the water infrastructures of cities and urban areas and US streams and rivers. The water infrastructures include drinking water distribution systems, wastewater collection systems and source water. The National Research Council^[1]states that problems dealing with the collective behavior of networks such as river systems, water distribution systems and waste water collection systems are complex because they include feedback loops, produce counter-intuitive behaviors and exhibit behaviors that cannot be predicted from the attributes of individual components. A complex system includes all of the above individual components, yet also exhibits emergent collective behavior caused by the interactions among its features. The integration of these applications have been developed for use in planning, response, training and development of monitoring strategies to address potential deliberate or accidental toxic contamination events

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PipelineNet: A Model for Monitoring Introduced Contaminants in a Distribution System

Cited by 25 publications

References 0 publications

Minimizing the Consequences of Intentional Attack on Water Infrastructure

Minimizing the Consequences of Intentional Attack on Water Infrastructure

GISMOWA: Geospatial Risk-Based Analysis Identifying Water Quality Monitoring Sites in Distribution Systems

The Integration of Network-Based Models for Spill Response and Homeland Security

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