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  5. Computational Determination of Air Valves Capacity Using CFD Techniques

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Article
English
2018

Computational Determination of Air Valves Capacity Using CFD Techniques

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0 Files

English
2018
Water
Vol 10 (10)
DOI: 10.3390/w10101433

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Alberto Patino Vanegas
Alberto Patino Vanegas

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Salvador García-Todolí
Pedro L. Iglesias‐Rey
Daniel Mora-Melià
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Abstract

The analysis of transient flow is necessary to design adequate protection systems that support the oscillations of pressure produced in the operation of motor elements and regulation. Air valves are generally used in pressurized water pipes to manage the air inside them. Under certain circumstances, they can be used as an indirect control mechanism of the hydraulic transient. Unfortunately, one of the major limitations is the reliability of information provided by manufacturers and vendors, which is why experimental trials are usually used to characterize such devices. The realization of these tests is not simple since they require an enormous volume of previously stored air to be used in such experiments. Additionally, the costs are expensive. Consequently, it is necessary to develop models that represent the behaviour of these devices. Although computational fluid dynamics (CFD) techniques cannot completely replace measurements, the amount of experimentation and the overall cost can be reduced significantly. This work approaches the characterization of air valves using CFD techniques, including some experimental tests to calibrate and validate the results. A mesh convergence analysis was made. The results show how the CFD models are an efficient alternative to represent the behavior of air valves during the entry and exit of air to the system, implying a better knowledge of the system to improve it.

How to cite this publication

Salvador García-Todolí, Pedro L. Iglesias‐Rey, Daniel Mora-Melià, F. Javier Martínez-Solano, Alberto Patino Vanegas (2018). Computational Determination of Air Valves Capacity Using CFD Techniques. Water, 10(10), pp. 1433-1433, DOI: 10.3390/w10101433.

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Publication Details

Type

Article

Year

2018

Authors

5

Datasets

0

Total Files

0

Language

English

Journal

Water

DOI

10.3390/w10101433

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