Development of a rapid and quantitative prediction model for assessing the leakage status of water pipeline systems
Journal of Civil Structural Health Monitoring, ISSN: 2190-5479, Vol: 13, Issue: 2-3, Page: 605-613
2023
- 7Citations
- 4Captures
- 1Mentions
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Most Recent News
Findings on Civil Structural Health Monitoring Reported by Investigators at Wuhan University of Technology (Development of a Rapid and Quantitative Prediction Model for Assessing the Leakage Status of Water Pipeline Systems)
2023 FEB 02 (NewsRx) -- By a News Reporter-Staff News Editor at Math Daily News -- Data detailed on Engineering - Civil Structural Health Monitoring
Article Description
Monitoring the leakage status of water pipes is of great importance for intelligent water services. In this work, the leakage status of the water pipeline was monitored in real time using a fiber optic distributed acoustic sensing (DAS) system, and the experimental study was conducted based on the mathematical modeling method of the response surface, which systematically reveals the quantitative relationship between water delivery pressure, leakage hole diameter, leakage location, and the flow rate at the leakage hole of water pipeline as well as the measured phase change of light. A theoretical mathematical model for assessing and warning the risk of water pipeline leakage was established. The results show that the water delivery pressure, leakage hole diameter, and leakage location are significantly influential on the flow rate and the phase change of light at the leakage hole. The degree of the influence by these three factors on the phase change of light and flow rate at the leakage hole is ranked as follows: leakage hole diameter > water delivery pressure > leakage location. The larger the leakage hole diameter, the higher the water delivery pressure, and the closer the leakage location is to the pipeline delivery port, the larger the phase change of light and flow rate at the leakage hole. The theoretical value of the model is highly consistent with the actual measured value with relative error less than 4% after experimental verification, which indicates that the predictability of the model works well, and is capable of accurately predicting and assessing the leakage status of the water supply pipeline network.
Bibliographic Details
Springer Science and Business Media LLC
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