Fitter, Thomas
(2023)
FlowOnTheGo: A methodological assessment of flow characterisation using image velocimetry.
Master of Philosophy thesis, University of Liverpool.
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Abstract
The quantification of fluvial systems is traditionally undertaken by single-point measurement techniques that require computational and instrument-specific expertise. Due to the importance of hydrological monitoring for water resource management and flood prediction, the availability of monitoring techniques has increased, with a shift towards non-intrusive, image-based methods. Non-intrusive methods have been applied to the characterisation of fluvial dynamics using a range of imagery algorithms. The effective operation of these techniques, however, is often dependent upon equipment and computational capabilities. To address these limitations, this study applies a recently-established non-contact Optical Flow Tracking Velocimetry (OFTV) technique called ‘FlowOnTheGo’ to estimate river flow velocity and turbulent parameters. FlowOnTheGo offers a computationally efficient imaged- based, multi-point measurement technique which is accessible to a range of scientific and non-scientific users through its smartphone and web-based platforms. The study is divided into two main sections. The first section establishes the algorithm’s capability by exploring a range of field-based methodological requirements that influence the computational efficiency and variability in the results. The second section employs FlowOnTheGo to characterise surface flow phenomena by exploring the nature of riverbed and in-river structure interactions with the flow field. The results gathered from the methodological setup, which explored the influence of image brightness, orthorectification and artificial seeding on FlowOnTheGo outputs show that optimal image exposure is critical for accurate flow measurements. Findings reveal that overexposure results in a loss of detail in the image and subsequent underestimation of flow velocities. Underexposure reduces glare on the river surface which facilitates feature tracking, while also offering results which most closely align with normal exposure. Unorthorectified video data tended to overestimate flow velocities relative to orthorectified video data and introduced greater errors (root-mean square error for the time-averaged velocity normalised by the double-averaged velocity and was computed at 0.13 m/s for the streamwise component, and 1.02 m/s for the spanwise component). FlowOnTheGo’s ability to resolve velocity extremes (i.e., the highest and lowest velocity values on the river’s surface) improved following orthorectification, coupled with a reduction in flow variability (0.031 m/s for unorthorectified velocity magnitude compared to 0.12 m/s for orthorectified iii velocity magnitude), due to the exacerbated geometric distortions present in oblique camera angles. Lastly, the effect of seeding on flow velocity measurements was quantified. A comparison between seeded and unseeded flows showed that seeding facilitates tracking across the width of the river and in regions of increased glare on the water surface. Unseeded video footage leads to greater errors in the velocity measurements relative to seeded video (root-mean square error the streamwise flow was 0.38 m/s and 0.15 m/s for the spanwise flow). To characterise phenomena, FlowOnTheGo was used to quantify the influence of riverbed topography on the surface flow field, explore the impact of in-river structures of fluvial hydrodynamics and investigate stress exerted by the river on a bridge structure and the riverbed and banks. When quantifying the influence of riverbed roughness elements on the surface flow, results show that at the highest relative submergence the mean flow was affected by topographic protrusions into the flow field, evidenced by fluctuations in the streamwise and spanwise velocity components. With decreasing relative submergence, the influence of smaller clasts became more pronounced, with the time-averaged flow field undergoing modifications at the lowest relative submergence due to a more uniform influence of the riverbed on the surface flow. The second study revealed a series of flow adjustments around a weir structure. Of note was flow acceleration through the narrowing of the weir walls which caused an increase in Turbulent Kinetic Energy (TKE) downstream of the structure. Increased flow velocities and TKE were also detected downstream of the hydraulic step. The heightened time-averaged velocity and TKE observations in proximity to the weir illustrate the influence of in-river structures on the generation of turbulence, with implications for sediment transport and structural stability. FlowOnTheGo captured a surface shear layer immediately downstream of the weir which consisted of rotational vortices indicative of Kelvin-Helmholtz instability. The final study found an increase in time- averaged flow velocities and turbulence intensity in proximity to the bridge, particularly between the abutments. The acceleration and turbulent intensity increase offer insights into potential scouring and structural instability. The study also investigated stress on the riverbed and banks which revealed the influence of sediment protrusions on the flow which led to flow separation and turbulence. The findings indicate areas that may be vulnerable to erosion by considering turbulent fluctuations generated by the river. Overall, the study builds upon previous velocimetry research by offering a computationally efficient and accessible tool for flow quantification designed for a range of end-users with different operational requirements.
| Item Type: | Thesis (Master of Philosophy) |
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| Divisions: | Faculty of Science and Engineering > School of Environmental Sciences |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 16 Sep 2024 15:06 |
| Last Modified: | 05 Feb 2025 21:09 |
| DOI: | 10.17638/03182006 |
| Supervisors: |
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| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3182006 |
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