Determining the 2-D Surface Velocity Field around Hydraulic Structures with the Use of a Large Scale Particle Image Velocimetry (LSPIV) Technique

Dermisis, D. C.; Papanicolaou, A. N.

doi:10.1061/40792(173)404

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…The wider the river, the more uncertainty is introduced to a video recording from the riverbank due to an increasing degree of perspective distortion. Though this angle of video recording may be still suitable for estimating the average flow velocity or discharge [41,53,65,66], it does not allow to recognise small-scale flow patterns, especially in the areas that are closer to the riverbank opposite to the one where the camera is mounted. The use of cameras mounted on and under bridges limits data acquisition to areas where bridges are present.…”

Section: Discussionmentioning

confidence: 99%

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Drone-Based Optical Measurements of Heterogeneous Surface Velocity Fields around Fish Passages at Hydropower Dams

et al. 2020

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In Austria, more than a half of all electricity is produced with the help of hydropower plants. To reduce their ecological impact, dams are being equipped with fish passages that support connectivity of habitats of riverine fish species, contributing to hydropower sustainability. The efficiency of fish passages is being constantly monitored and improved. Since the likelihood of fish passages to be discovered by fish depends, inter alia, on flow conditions near their entrances, these conditions have to be monitored as well. In this study, we employ large-scale particle image velocimetry (LSPIV) in seeded flow conditions to analyse images of the area near a fish passage entrance, captured with the help of a ready-to-fly consumer drone. We apply LSPIV to short image sequences and test different LSPIV interrogation area sizes and correlation methods. The study demonstrates that LSPIV based on ensemble correlation yields velocities that are in good agreement with the reference values regarding both magnitude and flow direction. Therefore, this non-intrusive methodology has a potential to be used for flow monitoring near fish passages on a regular basis, enabling timely reaction to undesired changes in flow conditions when possible.

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Section: Discussionmentioning

confidence: 99%

“…PIV is used for in-field flow observations more frequently than PTV [36], and in the literature it is often referred to as large-scale PIV (LSPIV) [39][40][41][42][43][44]. In this paper, we use the terms PIV and LSPIV interchangeably.…”

Section: Introductionmentioning

confidence: 99%

Drone-Based Optical Measurements of Heterogeneous Surface Velocity Fields around Fish Passages at Hydropower Dams

et al. 2020

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“…Existing flow measurement technologies for river and fishway studies rely on propeller flow meters or acoustic doppler velocimetry (ADV), which typically measure the flow velocity at a rate of 1 Hz [26]. Across the river and at the entrance to larger fishway structures, profiles of the flow field can be measured at higher spatial but lower temporal resolution using an acoustic doppler current profiler (ADCP) [27].…”

Section: Fishway Evaluation and Monitoringmentioning

confidence: 99%

Man-made flows from a fish’s perspective: autonomous classification of turbulent fishway flows with field data collected using an artificial lateral line

et al. 2018

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The lateral line system provides fish with advanced mechanoreception over a wide range of flow conditions. Inspired by the abilities of their biological counterparts, artificial lateral lines have been developed and tested exclusively under laboratory settings. Motivated by the lack of flow measurements taken in the field which consider fluid-body interactions, we built a fish-shaped lateral line probe. The device is outfitted with 11 high-speed (2.5 kHz) time-synchronized pressure transducers, and designed to capture and classify flows in fish passage structures. A total of 252 field measurements, each with a sample size of 132 000 discrete sensor readings were recorded in the slots and across the pools of vertical slot fishways. These data were used to estimate the time-averaged flow velocity (R = 0.952), which represents the most common metric to assess fishway flows. The significant contribution of this work is the creation and application of hydrodynamic signatures generated by the spatial distribution of pressure fluctuations on the fish-shaped body. The signatures are based on the collection of the pressure fluctuations' probability distributions, and it is shown that they can be used to automatically classify distinct flow regions within the pools of three different vertical slot fishways. For the first time, field data from operational fishway measurements are sampled and classified using an artificial lateral line, providing a completely new source of bioinspired flow information.

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“…As a result, the LSPIV is an appropriate technique for flow fields where the velocity is smaller than the limit of other measuring instruments. Dermisis and Papanicolaou [14] conducted velocity field in free surface with LSPIV around fish ladders and weirs, and compared the result with Acoustic Doppler Velocimetry (ADV), receiving an approximate error of 10%. Kim [15] listed out 27 sources of errors after analyzing the uncertainty of LSPIV.…”

Section: Introductionmentioning

confidence: 99%

Application of Image Technique to Obtain Surface Velocity and Bed Elevation in Open-Channel Flow

Lin

Lee

et al. 2022

Water

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The frequency of droughts and floods is increasing due to the extreme climate. Therefore, water resource planning, allocation, and disaster prevention have become increasingly important. One of the most important kinds of hydrological data in water resources planning and management is discharge. The general way to measure the water depth and discharge is to use the Acoustic Doppler Current Profiler (ADCP), a semi-intrusive instrument. This method would involve many human resources and pose severe hazards by floods and extreme events. In recent years, it has become mainstream to measure hydrological data with nonintrusive methods such as the Large-Scale Particle Image Velocimetry (LSPIV), which is used to measure the surface velocity of rivers and estimate the discharge. However, the unknown water depth is an obstacle for this technique. In this study, a method combined with LSPIV to estimate the bathymetry was proposed. The experiments combining the LSPIV technique and the continuity equation to obtain the bed elevation were conducted in a 27 m long and 1 m wide flume. The flow conditions in the experiments were ensured to be within uniform and subcritical flow, and thermoplastic rubber particles were used as the tracking particles for the velocity measurement. The two-dimensional bathymetry was estimated from the depth-averaged velocity and the continuity equation with the leapfrog scheme in a predefined grid under the constraints of Courant–Friedrichs–Lewy (CFL). The LSPIV results were verified using Acoustic Doppler Velocimetry (ADV) measurements, and the bed elevation data of this study were verified using conventional point gauge measurements. The results indicate that the proposed method effectively estimated the variation of the bed elevation, especially in the shallow water level, with an average accuracy of 90.8%. The experimental results also showed that it is feasible to combine the nonintrusive imaging technique with the numerical calculation in solving the water depth and bed elevation.

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Determining the 2-D Surface Velocity Field around Hydraulic Structures with the Use of a Large Scale Particle Image Velocimetry (LSPIV) Technique

Cited by 4 publications

References 6 publications

Drone-Based Optical Measurements of Heterogeneous Surface Velocity Fields around Fish Passages at Hydropower Dams

Drone-Based Optical Measurements of Heterogeneous Surface Velocity Fields around Fish Passages at Hydropower Dams

Man-made flows from a fish’s perspective: autonomous classification of turbulent fishway flows with field data collected using an artificial lateral line

Application of Image Technique to Obtain Surface Velocity and Bed Elevation in Open-Channel Flow

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