Self-Aeration and Flow Resistance in High-Velocity Flows Down Spillways with Microrough Inverts
Publication: Journal of Hydraulic Engineering
Volume 149, Issue 6
Abstract
Free-surface aeration is a key characteristic of high-velocity flows on spillways. Despite their common use as conveyance structures, there is a research gap in the understanding of flows across spillways with small invert roughness. To address this gap, this study investigated flows down a moderate sloped spillway with four different microrough invert configurations, providing novel information on flow patterns, flow properties, and flow resistance. Visual observations identified distinctive differences between free-surface roughness and air entrainment, where the former increased with invert roughness and occurred consistently upstream of the intersection of the turbulent boundary layer with the free-surface. The evolution of velocities, air concentrations, and interface frequencies along the chutes was documented. All velocity distributions were well represented by a log law with wake function and uniform free-surface layer. A semianalytical model was able to predict air concentration and interface frequency distributions for all experiments with a characteristic length that was linked closely to the mean air concentration. Analysis of the flow resistance provided previously missing design data and suggested that researchers need to be cautious when reporting microrough invert conditions in order to avoid overestimating their flow resistance. A comparative analysis of the air–water flow properties for the three microroughness configurations showed that the air concentration distributions were well scaled with a Froude similitude, and that the number of free-surface perturbations and entrained bubbles was affected by scale effects.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors acknowledge the technical assistance of Rob Jenkins (WRL, UNSW Sydney). The authors thank Reilly Cox (WRL, UNSW Sydney) and Hanwen Cui (School of Engineering and Information Technology, UNSW Canberra) for discussions of data postprocessing.
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Received: Feb 1, 2022
Accepted: Nov 11, 2022
Published online: Mar 31, 2023
Published in print: Jun 1, 2023
Discussion open until: Aug 31, 2023
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