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    Risk-Based Water Pipe Failure Prediction through Machine Learning and Hydraulic Models 

    Source: Journal of Water Resources Planning and Management:;2025:;Volume ( 151 ):;issue: 009:;page 04025038-1
    Author(s): Ko, Taegon; Farmani, Raziyeh; Keedwell, Edward; Beig Zali, Ramiz
    Publisher: American Society of Civil Engineers
    Abstract: AbstractFailures in water transmission lines (WTLs) can cause severe disruptions, high repair costs, and extensive damage to surrounding areas. The interest in proactive management through predictive methods as a way to ...
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    Surrogate Model for Predicting Stresses and Strains of Buried PVC Pipes in Water Distribution Networks 

    Source: Journal of Pipeline Systems Engineering and Practice:;2026:;Volume ( 017 ):;issue: 002:;page 04025120-1
    Author(s): Latifi, Milad; Beig Zali, Ramiz; Javadi, Akbar A.; Farmani, Raziyeh
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThis study presents the development of a surrogate model for evaluating the mechanical behavior of buried polyvinyl chloride (PVC) pipes, widely used in the water industry for conveying drinking water under pressure ...
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