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  5. Dynamic effects of a regulating valve in the assessment of water leakages in single pipelines

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Preprint
English
2023

Dynamic effects of a regulating valve in the assessment of water leakages in single pipelines

0 Datasets

0 Files

English
2023
Research Square (Research Square)
DOI: 10.21203/rs.3.rs-3276460/v1

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Oscar Coronado-hernández
Oscar Coronado-hernández

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Oscar Coronado-hernández
Vicente S. Fuertes-Miquel
Modesto Pérez‐Sánchez
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Abstract

Water losses in water distribution systems are typically analysed using extended period simulations, where its numerical resolution is commonly achieved using the gradient method. These models assume that adjustments to regulating valves occur, either manually or automatically, over an extended period of time, then the system inertia can be neglected. This research introduces the development of a rigid water column model for analysing water leakages in single pipelines, which can be employed to account for regulation valve adjustments in shorter time periods, thereby providing greater accuracy when assessing water losses. The application to a case study is presented to analyse pressure variations and leakage flow patterns over 30, 60, and 180 s. A comparison between the extended period simulation and rigid water column model is presented in order to note the order of magnitude on leakages when the system inertia is not considered. The results confirm that is crucial for water utilities the consideration of inertial system to simulate adequately opening and closure manoeuvres in water distribution systems, since according to the case study the extended period simulation can overestimated or underestimated the total leakage volume in percentages of 37.1 and 55.2 %, respectively.

How to cite this publication

Oscar Coronado-hernández, Vicente S. Fuertes-Miquel, Modesto Pérez‐Sánchez, Jairo R. Coronado-Hernández, Édgar Quiñones-Bolaños, Helena M. Ramos (2023). Dynamic effects of a regulating valve in the assessment of water leakages in single pipelines. Research Square (Research Square), DOI: 10.21203/rs.3.rs-3276460/v1.

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Publication Details

Type

Preprint

Year

2023

Authors

6

Datasets

0

Total Files

0

Language

English

Journal

Research Square (Research Square)

DOI

10.21203/rs.3.rs-3276460/v1

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