Start Date

2018 3:15 PM

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Abstract

When considering free surface flow in channels, it is essential to have in-depth knowledge about the inlet flow conditions and the effect of surface roughness on the overall flow field. Hence, we hereby investigate the flow inside an 18m long, free surface, channel by using Particle Tracking Velocimetry (PTV) and Acoustic Doppler Velocimetry (ADV). The roughness of the channel walls is generated using a diamond-square fractal algorithm and is designed to resemble the actual geometry of hydropower tunnels. Four different water levels ranging from 20 to 50cm are investigated. For each depth, the inlet is blocked by 25 and 50% at three positions each, at the centre, to the right and to the left in the flow-direction. The flow is altered for each depth to keep the flow velocity even throughout the measurements. PTV is applied to measure the velocity of the free water surface; four cameras are placed above the setup to capture the entirety of the channel. The results show a clear correlation between roughness height and velocity distribution at depths 20-30 cm. The surface roughness proved effective in dispersing the subsequent perturbations following the inlet blockage. At 50cm, perturbations from the 50% blockage could be observed throughout the channel. However, at 20cm, most perturbations had subsided by a third of the channel. The ADV was used to capture the velocity in a total of 375 points throughout the channel, at a depth of 50 cm with no inlet perturbations.

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May 16th, 3:15 PM

Inlet Blockage Effects in a Free Surface Channel With Artificially Generated Rough Walls

When considering free surface flow in channels, it is essential to have in-depth knowledge about the inlet flow conditions and the effect of surface roughness on the overall flow field. Hence, we hereby investigate the flow inside an 18m long, free surface, channel by using Particle Tracking Velocimetry (PTV) and Acoustic Doppler Velocimetry (ADV). The roughness of the channel walls is generated using a diamond-square fractal algorithm and is designed to resemble the actual geometry of hydropower tunnels. Four different water levels ranging from 20 to 50cm are investigated. For each depth, the inlet is blocked by 25 and 50% at three positions each, at the centre, to the right and to the left in the flow-direction. The flow is altered for each depth to keep the flow velocity even throughout the measurements. PTV is applied to measure the velocity of the free water surface; four cameras are placed above the setup to capture the entirety of the channel. The results show a clear correlation between roughness height and velocity distribution at depths 20-30 cm. The surface roughness proved effective in dispersing the subsequent perturbations following the inlet blockage. At 50cm, perturbations from the 50% blockage could be observed throughout the channel. However, at 20cm, most perturbations had subsided by a third of the channel. The ADV was used to capture the velocity in a total of 375 points throughout the channel, at a depth of 50 cm with no inlet perturbations.