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Izquierdo, J.; López, P. A.; López, G.; Martínez, F. J.; Pérez, R.

Encapsulation of air vessel design in a neural network. (English) Zbl 1163.76402

Appl. Math. Modelling 30, No. 5, 395-405 (2006).
Summary: The trial and error process of calculating the characteristics of an air vessel suitable to protect a rising main against the effects of hydraulic transients has proved to be cumbersome for the design engineer. The own experience and sets of charts, which can be found in the literature, can provide some help. The aim of this paper is to present a neural network allowing instantaneous and direct calculation of air and vessel volumes from the system parameters. This neural network has been implemented in the hydraulic transient simulation package DYAGATS.

MSC:

76M25 Other numerical methods (fluid mechanics) (MSC2010)
92B20 Neural networks for/in biological studies, artificial life and related topics

Keywords:

hydraulic transients; water hammer protection techniques; neural networks; function approximation

Software:

Neural Network Toolbox
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Full Text: DOI

References:

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