Encapsulation of air vessel design in a neural network

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.