A flow field characterization along a side weir in supercritical flow.

Francesco Granata, Rudy Gargano, Giovanni de Marinis, Simone Santopietro

Thursday 2 july 2015

14:35 - 14:50h at Africa (level 0)

Themes: (T) Special session, (ST) Acoustic monitoring of flow, turbulence and river discharge

Parallel session: 12F. Special session: Acoustic monitoring of flow, turbulence and river discharge

Side weirs are hydraulic structures widely used in urban drainage, irrigation and flood protection for their capability to divert high flow rates. Although side weirs have been extensively studied in the technical literature for almost a century, all the different available approaches to the matter (e.g. energy approach, momentum approach, flow power approach, purely empirical approaches) lead to imperfect solutions in various conditions. The analysis can be improved through a detailed investigation of the flow field. In this paper, the results of an experimental study of the flow field in a circular channel along a side weir are shown. The study focused on weakly supercritical flows. Experimental tests were performed in Laboratorio di Ingegneria delle Acque, University of Cassino and Southern Lazio, Italy. Velocities were measured by a Particle Image Velocimetry system, while flow depths were obtained from the same PIV images by applying a specific image processing technique. Velocity profiles were interpolated by means of theoretical formulations. Moreover, they allowed to know the flow rate in each cross section of the channel along the side weir and consequently also the lateral outflow as function of the distance from the weir beginning. Sections in which the lateral outflow is maximum have been identified. An elementary discharge coefficient was also considered. It was found highly variable along the side weir. Finally, energy and flow power variations along the weir were evaluated for the examined configurations. In particular, the knowledge of the actual variation law of the flow power along the side weir allowed to improve predictive capability of the flow power approach.