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    Application of Neural Network–Based Modeling for Leak Localization in Water Mains 

    Source: Journal of Pipeline Systems Engineering and Practice:;2022:;Volume ( 013 ):;issue: 004:;page 04022032
    Author(s): Ahmad Momeni; Kalyan R. Piratla; Kapil Chalil Madathil
    Publisher: ASCE
    Abstract: Water distribution network (WDN) leakage is estimated to account for more than 20% of potable water in the United States. Because existing leakage detection practices are mainly laborious or require excessive budget ...
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    Leveraging Hydraulic Cyber-Monitoring Data to Support Primitive Condition Assessment of Water Mains 

    Source: Journal of Pipeline Systems Engineering and Practice:;2021:;Volume ( 012 ):;issue: 004:;page 04021054-1
    Author(s): Ahmad Momeni; Kalyan R. Piratla
    Publisher: ASCE
    Abstract: Buried water pipelines deteriorate in response to several variables such as pressure transients, corrosion, and pipeline material degradation, among others, that are dynamic processes, and it is therefore difficult to ...
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