Hydraulic Jumps in Adverse-Slope Stilling Basins for Stepped Spillways

Ljubičić, Robert; Zindović, Budo; Vojt, Predrag; Pavlović, Dragutin; Kapor, Radomir; Savić, Ljubodrag

doi:10.3390/w10040460

Cited by 7 publications

(5 citation statements)

References 19 publications

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“…Inflow conditionsclear-water (hw1) and aerated depths (ha1), and Froude numbers (Fr1)were determined according to the empirical relations presented by Boes and Hager [41], [42] for stepped spillways, and are provided for reference purposes only. It should be noted that, for the hydraulic model used in this research, the accuracy of the empirical procedure developed by Boes and Hager [41], [42] was previously investigated using phase detection probes [43]. The results indicated up to 5% error, which is less than 1 mm for supercritical spillway flow.…”

Section: Temporal Filteringmentioning

confidence: 83%

Image processing for hydraulic jump free-surface detection: coupled gradient/machine learning model

Ljubičić¹,

Vicanovic²,

Zindović³

et al. 2020

Meas. Sci. Technol.

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High-frequency oscillations and high surface aeration, induced by the strong turbulence, make water depth measurement for hydraulic jumps a persistently challenging task. The investigation of the hydraulic jump behaviour persists as an important research theme, especially with regards to the stilling basin design. Reliable knowledge of time-averaged and extreme values along a depth profile can help develop an adequate design of a stilling basin, improve safety and aid the understanding of the jump phenomenon. This paper presents an attempt of mitigating certain limitations of existing depth measurement methods by adopting a non-intrusive computer vision-based approach to measuring water depth profile of a hydraulic jump. The proposed method analyses video data in order to detect the boundary between the air-water mixture and the laboratory flume wall. This is achieved by coupling two computer vision methods: (1) analysis of the vertical image gradients, and (2) generalpurpose edge detection using a deep neural network model. While the gradient analysis technique alone can provide adequate results, its performance can be significantly improved in combination with a neural network model which incorporates a "human-like" vision in the algorithm. The model coupling reduces the likelihood of false detections and improves the overall detection accuracy. The proposed method is tested in two experiments with different degrees of jump aeration. Results show that the coupled model can reliably and accurately capture the instantaneous depth profile along the jump, with low sensitivity to image noise and flow aeration. The coupled model presented fewer false detections than the gradientbased model, and offered consistent performance in regions of high, as well as low aeration. The proposed approach allows for automated detection of the free-surface interface and expands the potential of computer vision-based measurement methods in hydraulics.

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Section: Temporal Filteringmentioning

confidence: 83%

Image processing for hydraulic jump free-surface detection: coupled gradient/machine learning model

Ljubičić¹,

Vicanovic²,

Zindović³

et al. 2020

Meas. Sci. Technol.

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“…Pressure measurements in the stepped-spillway stilling basin were performed on a modular scale model (Figure 3) that was used in previous research related to the stepped spillways and stilling basins [4,8,24]. The model was designed to accommodate variations in parameters outlined in Equation (9).…”

Section: Scale Modelsmentioning

confidence: 99%

“…Stepped spillways have become common structures in large-dam hydraulic engineering due to the significant energy dissipation along the chute [1][2][3][4][5][6][7], hence considerably reducing the size and the cost of the stilling basin. The spillway crest should be wide enough to enable low overflow depth, enabling the minimum height of the dam, and the stilling basin should be narrow enough to minimize the excavation costs [8].…”

Section: Introductionmentioning

confidence: 99%

“…Dynamic load for stilling basins has been the subject of research for smooth converging chutes [9] and in plunge pools with hydraulic jump [11,20]. Although there is some amount of experimental research on the stepped stilling basin flow in general [4,21,22], there are few published reports on the subject of dynamic loads in the stepped chute stilling basins [6], and, to the authors' knowledge, there is currently no published research in the area of dynamic loads in the basins of stepped chutes with variable bottom width (chutes with converging walls). In addition, there are no studies on the load on the stilling basin walls in the available literature.…”

Section: Introductionmentioning

confidence: 99%

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Hydrodynamic Loads in a Stilling Basin of a Converging Stepped Spillway: An Experimental Study

Milovanovic,

Vojt,

Zindovic

et al. 2023

Water

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This paper presents a methodology for estimation of hydrodynamic loads acting on the bottom and at the walls of a stilling basin of a stepped chute with converging walls, based on the pressure measurements at the selected points of a scale model. This is the first study of hydrodynamic loads for this type of structure, and the first one of the loads on the stilling basin walls in general. For selected flow discharges, step heights and hydraulic jump submergence ratio, the hydrodynamic pressures were measured at a significant number of points, providing the spatio-temporal distribution of relevant hydrodynamic loads. The most influential effect proved to be a convergence angle of the chute walls. Based on these measurements, appropriate regression expressions were proposed for predicting hydrodynamic loads. These expressions show good agreement with measurements, offering a reliable tool for the structural design of stepped spillway stilling basins.

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“…According to their researches, the air inception location over stepped spillways exits until the boundary layer thickness is between the range of 0.72 and 0.79. Ljubicic et al [41] studied the adverse slope stilling basins with stepped chutes. They studied the momentum, the length of the hydraulic jump, and the energy dissipation by the numerical model, and then compared the results with the experimental data.…”

Section: LImentioning

confidence: 99%

Effect of Height and Geometry of Stepped Spillway on Inception Point Location

2019

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Air entrainment in a stepped spillway is very important to protect the spillway from cavitation damage. The inception point is the location where air starts entering the non-aerated flow zone. The inception point location depends on different parameters, such as the discharge, step height, and step shape. In this paper, various stepped spillways, including flat steps, pooled steps, and round steps with different step heights were numerically simulated using the volume of fluid and realizable k-ε models. The results indicate that the inception point location moves downwards with the increase of the discharge of the stepped spillways. The length of the non-aerated flow zone increases with the discharge. The inception point location moves downwards as the step height decreases and the step number increases at the same discharge. The inception point location of the round stepped spillway model is much closer to the spillway crest than that of the flat stepped spillway with the same number of steps. The inception point location of the pooled stepped spillway is closer to the spillway crest than that of the flat stepped spillway, but more downstream than that of the round stepped spillway.

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Hydraulic Jumps in Adverse-Slope Stilling Basins for Stepped Spillways

Cited by 7 publications

References 19 publications

Image processing for hydraulic jump free-surface detection: coupled gradient/machine learning model

Image processing for hydraulic jump free-surface detection: coupled gradient/machine learning model

Hydrodynamic Loads in a Stilling Basin of a Converging Stepped Spillway: An Experimental Study

Effect of Height and Geometry of Stepped Spillway on Inception Point Location

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