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Journal ArticleDOI

Control of Bed Erosion at 60° River Confluence Using Vanes and Piles

TLDR
In this article, the authors used a distorted model with a non-uniform sediment of mean particle size d¯¯ 50672 ǫ = 0.28mm with a confluence angle of 60°.
Abstract
River confluences have complex hydrodynamics than ambient flows due to different flow characteristics of the two merging flows. Secondary circulation develops due to merging of two flows which leads to bed erosion. The eroded sediment gets deposited at various locations in the downstream of the confluence. It is reported in the literature that major reservoirs in India will lose 50% storage capacity by 2020 and reservoirs all over the world lose storage capacity by as much as 5% every year. In view of controlling bed erosion at the confluence, vane and circular pile models are used as scour mitigation structures and experimental results are presented. Experiments are performed in a distorted model with a non-uniform sediment of mean particle size d 50  = 0.28 mm with a confluence angle of 60°. Two different discharge ratios (Q r = ratio of lateral flow discharge to main flow discharge) of 0.5 and 0.75 are used with a constant flow depth (H m) of 5 cm in the main channel. Vanes of width 0.3H m (1.5 cm), thickness of 1 mm are placed at 15°, 30° and 60° vane angles with respect to main flow. Circular pile models of 8 and 12 mm diameter are also used. Two different spacing of 2H m and 3H m (10 and 15 cm) between the vanes or piles are used to perform the experiments. For Q r = 0.5 and 0.75 using vanes, scour depth reduces by 25 and 34%, respectively. When circular pile models of 8 and 12 mm are used, the scour depth reduces by 25, 38 and 27, 43%, for Q r = 0.5 and 0.75, respectively. The scour depth decreases with an increase of vane angle and pile diameter, but increases with an increase of spacing. Therefore, piles have better performance over vanes in reducing scour at the confluence.

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Citations
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Journal ArticleDOI

Comparing the Scour Upstream of Circular and Square Orifices

TL;DR: In this article, the authors compared the scour pattern upstream of square and circular orifices with equal opening areas of 38.45 cm2 and found that the influence zone area upstream of the square orifice is 1.46 times larger than the circular orifice.
Journal ArticleDOI

Control of sediment inflow into a trapezoidal intake canal using submerged vanes

TL;DR: In this paper, experiments were conducted to control sediment entry into an intake channel using submerged vanes in a physical model with a rectangular mobile-bed main channel and a trapezoidal rigid-bed intake channel diverting at an angle of 45°.
Journal ArticleDOI

Improving the Hydro-Morpho Dynamics of A River Confluence by Using Vanes

TL;DR: In this article, a 2D numerical model is used in simulating hydromorpho dynamics in the rivers confluence to mitigate the erosion and deposition zones by adopting vanes as control structures.
Journal ArticleDOI

Estimation of scour depth around cross-vane structures using a novel non-tuned high-accuracy machine learning approach

TL;DR: In this article, the scour hole depth at the downstream of cross-vane structures with different shapes (i.e., J, I, U, and W) is simulated utilizing a modern artificial intelligence method entitled "Outlier Robust Extreme Learning Machine (ORELM)".
References
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Journal ArticleDOI

Mixing layer in open-channel junction flows

TL;DR: In this article, the shape of the mixing layer appears to be strongly affected by the streamwise acceleration and complex lateral confinement due to the side walls and the corners of the junction, leading to a streamwise increase of the mean velocity along the centerline and a decrease of the velocity difference.
Journal ArticleDOI

Potential hazard analysis from the viewpoint of flow measurement in large open-channel junctions

TL;DR: In this paper, an Acoustic Doppler Velocimeter is used to monitor the flow in large open-channel junctions at the Chihtan purification plant in Taipei.
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Open channel junction velocity prediction by using a hybrid self-neuron adjustable artificial neural network

TL;DR: A new self-neuron number adjustable, hybrid Genetic Algorithm-Artificial Neural Network (GA-ANN), is introduced and its application examined on the complex velocity field prediction of an open channel junction showed that the GA-ANN model can predict theopen channel junction velocity with higher accuracy than the GP model.
Journal ArticleDOI

Experiments to supercritical junction flow

TL;DR: In this paper, the main dimensions of three waves at channel junctions are defined: wave C, wave B and wall wave D. Wave C is a junction wave located at the rear of the junction point and may be compared with the wave due to an abrupt wall deflection.
Journal ArticleDOI

Local scour at open-channel junctions

TL;DR: In this article, the scour patterns at the junction of two loose bed channels were studied under clear-water conditions, where the main dimensionless variables were the angle between the two approach flow branches, the discharge and width ratios of the tributary to the downstream channel branches, and the ratio of the mean downstream velocity to the threshold velocity.
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