Improved air valve design using evolutionary polynomial regression

Air valves are usually sized by heuristic methods or, sometimes, even oversized. Although the technical literature has long focused on the correct sizing of air valves to reduce the overpressure generated by the filling of a pipe, the phenomenon is complex and does not seem to be representable by physically based equations in an easy way, to be of practical use for technicians and designers. In this paper, air valve design is approached through an alternative data-modelling approach, based on evolutionary polynomial regression, with the aim to provide symbolic formulas of variable complexity and accuracy, suitable for physical interpretation, and at the same time easy to be used and applied for design purposes. The present investigation suggests a design formula that, given the geometric parameters of the pipeline system where the air valve is installed, provides the maximum tolerable overpressure, thus allowing the optimal air valve orifice size to be identified