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Identifying Contaminant Intrusion in Water Distribution Networks under Water Flow and Sensor Report Time Uncertainties
Contamination events in water distribution networks (WDNs) could have severe health and economic consequences. Contaminants can be deliberately or accidentally introduced into the WDN. Quick identification of the injection location and time is important in devising a mitigation plan to prevent further spread of the contaminant in the network. A method of identifying the possible intrusion point in a given network and reporting data is to use an inverse calculation by backtracking the potential path of the contaminant in the network. However, there is an element of uncertainty in the data used for calculation, particularly in water flow and sensor report time. Given the uncertainties, a method was developed in this study for fast and accurate contaminant source identification. This paper proposes a comparison filter of results by first identifying potential contaminant locations through backtracking, followed by a forward calculation to determine the injection time range, thereby reducing the potential suspects and providing likeliness comparison among the suspects. The effectiveness of the proposed method was examined by applying it to a benchmark WDN. By simulating uncertainties and filtering through the results, several possible contaminant intrusion locations and times were identified.
Identifying Contaminant Intrusion in Water Distribution Networks under Water Flow and Sensor Report Time Uncertainties
Contamination events in water distribution networks (WDNs) could have severe health and economic consequences. Contaminants can be deliberately or accidentally introduced into the WDN. Quick identification of the injection location and time is important in devising a mitigation plan to prevent further spread of the contaminant in the network. A method of identifying the possible intrusion point in a given network and reporting data is to use an inverse calculation by backtracking the potential path of the contaminant in the network. However, there is an element of uncertainty in the data used for calculation, particularly in water flow and sensor report time. Given the uncertainties, a method was developed in this study for fast and accurate contaminant source identification. This paper proposes a comparison filter of results by first identifying potential contaminant locations through backtracking, followed by a forward calculation to determine the injection time range, thereby reducing the potential suspects and providing likeliness comparison among the suspects. The effectiveness of the proposed method was examined by applying it to a benchmark WDN. By simulating uncertainties and filtering through the results, several possible contaminant intrusion locations and times were identified.
Identifying Contaminant Intrusion in Water Distribution Networks under Water Flow and Sensor Report Time Uncertainties
Malvin S. Marlim (author) / Doosun Kang (author)
2020
Article (Journal)
Electronic Resource
Unknown
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