Numerical Simulation of the Influence of Spur Dikes Spacing on Local Scour and Flow

Ning, Jian; Li, Guodong; Li, Shanshan

doi:10.3390/app9112306

Cited by 17 publications

(15 citation statements)

References 17 publications

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“…At this angle, the NH 3 ‐N is in full contact with the ecological spur dikes and has the best purification effect on the NH 3 ‐N. The peak NH 3 ‐N concentration C max was the lowest at a spacing of 17 m. As the spacing of the spur dikes decreases, the area of the return zone decreases and the intensity of the return flow increases, which not only leads to localized scouring at the head of the spur dikes, which destabilizes the structure of the spur dikes, but also does not help to intercept and clean the NH 3 ‐N (Cao et al, 2013; Ning et al, 2019). Therefore, the area and strength of the return zone are not as large as they should be.…”

Section: Resultsmentioning

confidence: 99%

Study on purification effect of river ammonia nitrogen and optimization of layout parameters in the combination of ecological spur dikes and deep pool shoals: Experiments and MIKE21

Wang,

Li,

Wang

et al. 2024

River Research & Apps

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The construction of ecological spur dikes and deep pool shoals can increase the diversity of water flow structures while also hastening the transport and transformation of pollutants. However, current research has paid little attention to the effects of the arrangement parameters on water purification capacity when the ecological spur dikes and deep pool shoals are combined. In this study, we investigated the purification capacity of ammonia nitrogen using the combination of spur dikes and deep pool shoals through laboratory flume experiments and numerical simulation. The laboratory flume experiments revealed that the combination of staggered spur dikes and the opposite side deep pool shoals provided the most effective purification. Secondly, in order to obtain the optimal arrangement parameters for the combination of ecological spur dikes and deep pool shoals more easily, the numerical model based on MIKE21 was validated using experimental results and applied to Section 2 of the Shiqiao River in Nanling County, Wuhu City, Anhui Province. The numerical simulation showed that the length of the spur dikes had the greatest impact on the purification effect, followed by the spacing of the spur dikes and the width of the deep pool shoals, the angle of the spur dikes, the spacing of the deep pool shoals, and the length of the deep pool shoals had the least effect. The optimal parameters for the combination of spur dikes and deep pool shoals are as follows: spur dike parameters: 60°(angle), 10 m(length), 17 m(spacing); deep pool shoal parameters: 60 m(length), 10 m(width), and 210 m(spacing).

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Section: Resultsmentioning

confidence: 99%

Study on purification effect of river ammonia nitrogen and optimization of layout parameters in the combination of ecological spur dikes and deep pool shoals: Experiments and MIKE21

Wang,

Li,

Wang

et al. 2024

River Research & Apps

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“…Installing more groins may prolong the regulating length of the river and cause more a complicated turbulent flow pattern, but this is difficult to measure via laboratory experiment. Employing a numerical model validated by experimental data, the complex recirculating flow inside multiple groins field was successfully captured by McCoy et al [35], Fang et al [36], Koutrouveli et al [37] and Ning et al [38]. The simulated results show that the center of the downstream recirculation zone moves towards the groin as groin length increases, and the recirculation zone between groins increased with the spacing between two neighboring groins.…”

Section: Introductionmentioning

confidence: 95%

Experimental Study on Backflow Patterns Induced by a Bilateral Groin Pair with Different Spacing

Kuang

Zheng

et al. 2021

Applied Sciences

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Groins are one of the popular manmade structures to modify the hydraulic flow and sediment response in river training. The spacing between groins is a critical consideration to balance the channel-depth and the cost of construction, which is generally determined by the backflow formed downstream from groins. A series of experiments were conducted using Particle Image Velocimetry (PIV) to observe the influence of groin spacing on the backflow pattern of two bilateral groins. The spacing between groins has significant effect on the behavior of the large-scale recirculation cell behind groins. The magnitude of the wake flow induced by a groin was similar to that induced by another groin on the other side, but the flow direction is opposite. The spanwise velocity near the groin tip dictates the recirculation zone width behind the groins due to the strong links between the spanwise velocity and the contraction ratio of channel cross-sections between groins. Based on previous studies and present experimental results, quantitative empirical relationships are proposed to calculate the recirculation zone length behind groins alternately placed at different spacing along riverbanks. This study provides better understanding and a robust formula to assess the backflow extent of alternate groins and identify the optimum groins array configuration.

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“…One of the new methods for estimating the variables associated with numerous variables is the ANN model. This model uses information processing on experimental data and results from the human brain [22,23]. The structure of the ANN is determined by the try and error process.…”

Section: Artificial Neural Network Modelmentioning

confidence: 99%

Efficiency of Artificial Neural Networks in Determining Scour Depth at Composite Bridge Piers

Amini

Hamidi

Shirzadi

et al. 2019

Preprint

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Scouring is the most common cause of bridge failure. This study was conducted to evaluate the efficiency of the Artificial Neural Networks (ANN) in determining scour depth around composite bridge piers. The experimental data, attained in different conditions and various pile cap locations, were used to obtain the ANN model and to compare the results of the model with most well-known empirical, HEC-18 and FDOT, methods. The data were divided into training and evaluation sets. The ANN models were trained using the experimental data, and their efficiency was evaluated using statistical test. The results showed that to estimate scour at the composite piers, feedforward propagation network with three neurons in the hidden layer and hyperbolic sigmoid tangent transfer function was with the highest accuracy. The results also indicated a better estimation of the scour depth by the proposed ANN than the empirical methods.

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Numerical Simulation of the Influence of Spur Dikes Spacing on Local Scour and Flow

Cited by 17 publications

References 17 publications

Study on purification effect of river ammonia nitrogen and optimization of layout parameters in the combination of ecological spur dikes and deep pool shoals: Experiments and MIKE21

Study on purification effect of river ammonia nitrogen and optimization of layout parameters in the combination of ecological spur dikes and deep pool shoals: Experiments and MIKE21

Experimental Study on Backflow Patterns Induced by a Bilateral Groin Pair with Different Spacing

Efficiency of Artificial Neural Networks in Determining Scour Depth at Composite Bridge Piers

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