Factors and interactions that influence the pressure drop across an air volume reducing device on low-pressure water distribution networks

Efficient water supply systems are necessary for the development and sustainability of human societies. One relevant aspect of these systems is the metering function, recorded employing water meters, which determines the charges levied to the clients and estimates the water losses in the network. In...

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Autores:
Carpintero, Javier
A. Canales, Fausto
Fábregas, Jonathan
Ávila, José
Tipo de recurso:
Article of journal
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/8494
Acceso en línea:
https://hdl.handle.net/11323/8494
https://doi.org/10.1007/s40996-021-00682-z
https://repositorio.cuc.edu.co/
Palabra clave:
Water metering
Design of experiments
Pressure drop
Valve diameter
Spring
Rights
openAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 International
Description
Summary:Efficient water supply systems are necessary for the development and sustainability of human societies. One relevant aspect of these systems is the metering function, recorded employing water meters, which determines the charges levied to the clients and estimates the water losses in the network. Inaccurate measurements are detrimental for both the client and the supplier. For allowing more precise metering, one option is to use an air volume reducing device, an accessory similar to a check valve that minimizes the air volume entrapped in the pipelines, thus improving metering accuracy. This research used an experimental design to determine the influence of four factors and their interactions on the pressure drop across these devices as a preliminary step for allowing their extended use on low-pressure water supply systems. The results showed that the diameter, the spring stiffness, and the flow rate are significant factors in the pressure drop. The shape of the valve stem is statistically significant only when interacting with other factors.