scholarly journals Pressure Fluctuations in the Spatial Hydraulic Jump in Stilling Basins with Different Expansion Ratio

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 60
Author(s):  
Nasrin Hassanpour ◽  
Ali Hosseinzadeh Dalir ◽  
Arnau Bayon ◽  
Milad Abdollahpour
Keyword(s):  
Hydraulic Jump ◽  
Laboratory Tests ◽  
Pressure Fluctuations ◽  
Expansion Ratio ◽  
Hydraulic Jumps ◽  
Extreme Pressure ◽  
Flow Conditions ◽  
Stilling Basins ◽  
Channel Expansion ◽  
Shed Light

Pressure fluctuations are a key issue in hydraulic engineering. However, despite the large number of studies on the topic, their role in spatial hydraulic jumps is not yet fully understood. The results herein shed light on the formation of eddies and the derived pressure fluctuations in stilling basins with different expansion ratios. Laboratory tests are conducted in a horizontal rectangular flume with 0.5 m width and 10 m length. The range of approaching Froude numbers spans from 6.4 to 12.5 and the channel expansion ratios are 0.4, 0.6, 0.8, and 1. The effects of approaching flow conditions and expansion ratios are thoroughly analyzed, focusing on the dimensionless standard deviation of pressure fluctuations and extreme pressure fluctuations. The results reveal that these variables show a clear dependence on the Froude number and the distance to the hydraulic jump toe. The maximum values of extreme pressure fluctuations occur in the range 0.609<X<3.385, where X is dimensionless distance from the toe of the hydraulic jump, which makes it highly advisable to reinforce the bed of stilling basins within this range.

scholarly journals Analysis of minimal and maximal pressures, uncertainty and spectral density of fluctuating pressures beneath classical hydraulic jumps

2020 ◽  
Vol 20 (5) ◽  
pp. 1909-1921
Author(s):  
Seyed Nasrollah Mousavi ◽  
Davood Farsadizadeh ◽  
Farzin Salmasi ◽  
Ali Hosseinzadeh Dalir ◽  
Daniele Bocchiola
Keyword(s):  
Spectral Density ◽  
Large Scale ◽  
Pressure Fluctuations ◽  
Low Frequency ◽  
Dominant Frequency ◽  
Standard Uncertainty ◽  
Hydraulic Jumps ◽  
Stilling Basins ◽  
Density Analysis ◽  
Real Scale

Abstract Knowledge of extreme pressures and fluctuations within stilling basins is of the utmost importance, as they may cause potential severe damages. It is complicated to measure the fluctuating pressures of hydraulic jumps in real-scale structures. Therefore, little information is available about the pressure fluctuations in the literature. In this paper, minimal and maximal pressures were analyzed on the flat bed of a stilling basin downstream of an Ogee spillway. Attention has been focused on dimensionless pressures related to the low and high cumulative probabilities of occurrence (P*0.1% and P*99.9%), respectively. The results were presented based on the laboratory-scale experiments. These parameters for the relatively high Froude numbers have not been investigated. The total standard uncertainty for the dimensionless mean pressures (P*m) was obtained around 1.87%. Spectral density analysis showed that the dominant frequency in the classical hydraulic jumps was about 4 HZ. Low-frequency of pressure fluctuations indicated the existence of large-scale vortices. In the zone near the spillway toe, P*0.1% reached negative values of around −0.3. The maximum values of pressure coefficients, namely |CP0.1%|max and CP99.9%max, were achieved around 0.19 and 0.24, respectively. New original expressions were proposed for P*0.1% and P*99.9%, which are useful for estimating extreme pressures.

Prediction of pressure fluctuations on sloping stilling basins

2006 ◽  
Vol 33 (11) ◽  
pp. 1379-1388 ◽  
Author(s):  
A Güven ◽  
M Günal ◽  
A Çevik
Keyword(s):  
Neural Network ◽  
Pressure Fluctuation ◽  
Hydraulic Jump ◽  
Regression Models ◽  
Pressure Fluctuations ◽  
Network Models ◽  
Neural Network Models ◽  
Mean Pressure ◽  
Stilling Basins ◽  
The Mean

Various types of hydraulic jump occurring on horizontal and sloping channels have been analyzed experimentally, theoretically, and numerically and the results are available in the literature. In this study, artificial neural network models were developed to simulate the mean pressure fluctuations beneath a hydraulic jump occurring on sloping stilling basins. Multilayers feed a forward neural network with a back-propagation learning algorithm to model the pressure fluctuations beneath such a type of hydraulic jump (B-jump). An explicit formula that predicts the mean pressure fluctuation in terms of the characteristics that contribute most to the hydraulic jump occurring on the sloping basins is presented. The proposed neural network models are compared with linear and nonlinear regression models that were developed using considered physical parameters. The results of the neural network modelling are found to be superior to the regression models and are in good agreement with the experimental results due to relatively small values of error (mean absolute percentage error).Key words: neural networks, pressure fluctuation, hydraulic jump, sloping stilling basin, explicit NN formulation, regression analysis.

Radial flow stilling basins with baffle blocks

1989 ◽  
Vol 16 (4) ◽  
pp. 489-497 ◽  
Author(s):  
Peter C. Nettleton ◽  
John A. McCorquodale
Keyword(s):  
Key Words ◽  
Hydraulic Jump ◽  
Water Surface ◽  
Radial Flow ◽  
Surface Profile ◽  
Hydraulic Jumps ◽  
Bureau Of Reclamation ◽  
Stilling Basin ◽  
Jump Length ◽  
Stilling Basins

A total of 120 tests of forced radial flow hydraulic jumps have been analyzed in order to develop curves and equations for the design of radial stilling basins. The jump depth, the water surface profile, wave amplitudes, the allowable flare angle, and the jump length are defined in terms of entrance conditions, the baffle position, and the baffle height. An example design is given and compared with a USBR (U.S. Bureau of Reclamation) Type III stilling basin. Key words: forced hydraulic jump, radial flow, design, stilling basins, baffles, radial hydraulic jump, circular hydraulic jump.

scholarly journals An evaluation of ANN methods for estimating the lengths of hydraulic jumps in U-shaped channel

2012 ◽  
Vol 15 (1) ◽  
pp. 147-154 ◽  
Author(s):  
Larbi Houichi ◽  
Noureddine Dechemi ◽  
Salim Heddam ◽  
Bachir Achour
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Hydraulic Jump ◽  
Empirical Models ◽  
Generalized Regression Neural Network ◽  
Hydraulic Jumps ◽  
Hydraulic Characteristics ◽  
Stilling Basins ◽  
High Turbulence ◽  
Predictive Strength

Modelling of hydraulic characteristics of jump using theoretical and empirical models has always been a difficult task. The length of jump may be defined as the distance measured from the toe of the jump to the location of the surface rise. Due to high turbulence this length cannot be determined easily by theory. However, it has been investigated experimentally so as to design the stilling basins with hydraulic jumps. In this work, the control of a hydraulic jump by broad-crested sills in a U-shaped channel is recalled theoretically and experimentally examined. The study begins with a multiple regression (MR) analysis. Then, and in order to model the relative lengths of hydraulic jumps, we have implemented and evaluated two different artificial neural networks (ANN): multilayer perceptron neural network (MLPNN) and generalized regression neural network (GRNN). The results demonstrate the predictive strength of GRNN and its potential to predict hydraulic problems with an adaptive spread value. However, the MLPNN model remains best classified by these indexes of performance.

scholarly journals Estimation of hydraulic jump characteristics of channels with sudden diverging side walls via SVM

2017 ◽  
Vol 76 (7) ◽  
pp. 1614-1628 ◽  
Author(s):  
Kiyoumars Roushangar ◽  
Reyhaneh Valizadeh ◽  
Roghayeh Ghasempour
Keyword(s):  
Froude Number ◽  
Hydraulic Jump ◽  
Relative Energy ◽  
Expansion Ratio ◽  
Superior Performance ◽  
Support Vector ◽  
Great Performance ◽  
Stilling Basins ◽  
Side Walls ◽  
Sequent Depth

Sudden diverging channels are one of the energy dissipaters which can dissipate most of the kinetic energy of the flow through a hydraulic jump. An accurate prediction of hydraulic jump characteristics is an important step in designing hydraulic structures. This paper focuses on the capability of the support vector machine (SVM) as a meta-model approach for predicting hydraulic jump characteristics in different sudden diverging stilling basins (i.e. basins with and without appurtenances). In this regard, different models were developed and tested using 1,018 experimental data. The obtained results proved the capability of the SVM technique in predicting hydraulic jump characteristics and it was found that the developed models for a channel with a central block performed more successfully than models for channels without appurtenances or with a negative step. The superior performance for the length of hydraulic jump was obtained for the model with parameters F1 (Froude number) and (h2—h1)/h1 (h1 and h2 are sequent depth of upstream and downstream respectively). Concerning the relative energy dissipation and sequent depth ratio, the model with parameters F1 and h1/B (B is expansion ratio) led to the best results. According to the outcome of sensitivity analysis, Froude number had the most significant effect on the modeling. Also comparison between SVM and empirical equations indicated the great performance of the SVM.

scholarly journals Predictive Modeling the Free Hydraulic Jumps Pressure through Advanced Statistical Methods

Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 323
Author(s):  
Seyed Nasrollah Mousavi ◽  
Renato Steinke Júnior ◽  
Eder Daniel Teixeira ◽  
Daniele Bocchiola ◽  
Narjes Nabipour ◽  
...  
Keyword(s):  
Probability Distribution ◽  
Pressure Fluctuations ◽  
Mean Value ◽  
Maximum Pressure ◽  
Hydraulic Jumps ◽  
Statistical Parameters ◽  
Characteristic Points ◽  
Stilling Basins ◽  
The Stability ◽  
Cumulative Curves

Pressure fluctuations beneath hydraulic jumps potentially endanger the stability of stilling basins. This paper deals with the mathematical modeling of the results of laboratory-scale experiments to estimate the extreme pressures. Experiments were carried out on a smooth stilling basin underneath free hydraulic jumps downstream of an Ogee spillway. From the probability distribution of measured instantaneous pressures, pressures with different probabilities could be determined. It was verified that maximum pressure fluctuations, and the negative pressures, are located at the positions near the spillway toe. Also, minimum pressure fluctuations are located at the downstream of hydraulic jumps. It was possible to assess the cumulative curves of pressure data related to the characteristic points along the basin, and different Froude numbers. To benchmark the results, the dimensionless forms of statistical parameters include mean pressures (P*m), the standard deviations of pressure fluctuations (σ*X), pressures with different non-exceedance probabilities (P*k%), and the statistical coefficient of the probability distribution (Nk%) were assessed. It was found that an existing method can be used to interpret the present data, and pressure distribution in similar conditions, by using a new second-order fractional relationships for σ*X, and Nk%. The values of the Nk% coefficient indicated a single mean value for each probability.

scholarly journals Experimental Analysis on the Use of Counterflow Jets as a System for the Stabilization of the Spatial Hydraulic Jump

Water ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 2572
Author(s):  
Shokoofeh Sharoonizadeh ◽  
Javad Ahadiyan ◽  
Anna Rita Scorzini ◽  
Mario Di Bacco ◽  
Mohsen Sajjadi ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Experimental Analysis ◽  
Hydraulic Jump ◽  
Laboratory Tests ◽  
Hydraulic Jumps ◽  
Flow Uniformity ◽  
Subcritical Flow ◽  
Stilling Basin ◽  
Geometric Configurations ◽  
Dissipation System

This study presents an investigation on the use of submerged counterflow jets as a means for stabilizing the spatial hydraulic jump occurring in abruptly expanding channels. The characteristics of the flow downstream from the stilling basin and the main parameters influencing the effectiveness of the device in improving flow uniformity and reducing scouring potential are examined in laboratory tests, under several geometric configurations and hydraulic boundary conditions. The position within the stilling basin and the jet density (i.e., the number of orifices issuing the counterflow jets) were found to be important parameters influencing the performance of the device. Overall, the results indicate that this dissipation system has promising capabilities in forcing the transition from supercritical to subcritical flow, by significantly shortening the protection length needed to limit the phenomena of instability associated with spatial hydraulic jumps.

scholarly journals Application of a model of internal hydraulic jumps

2017 ◽  
Vol 834 ◽  
pp. 125-148 ◽  
Author(s):  
S. A. Thorpe ◽  
J. Malarkey ◽  
G. Voet ◽  
M. H. Alford ◽  
J. B. Girton ◽  
...  
Keyword(s):  
Hydraulic Jump ◽  
Mixing Layer ◽  
Strong Support ◽  
Deep Ocean ◽  
Hydraulic Jumps ◽  
Model Predictions ◽  
Mode 2 ◽  
Mediterranean Outflow ◽  
Unknown Structure ◽  
Internal Hydraulic Jump

A model devised by Thorpe & Li (J. Fluid Mech., vol. 758, 2014, pp. 94–120) that predicts the conditions in which stationary turbulent hydraulic jumps can occur in the flow of a continuously stratified layer over a horizontal rigid bottom is applied to, and its results compared with, observations made at several locations in the ocean. The model identifies two positions in the Samoan Passage at which hydraulic jumps should occur and where changes in the structure of the flow are indeed observed. The model predicts the amplitude of changes and the observed mode 2 form of the transitions. The predicted dissipation of turbulent kinetic energy is also consistent with observations. One location provides a particularly well-defined example of a persistent hydraulic jump. It takes the form of a 390 m thick and 3.7 km long mixing layer with frequent density inversions separated from the seabed by some 200 m of relatively rapidly moving dense water, thus revealing the previously unknown structure of an internal hydraulic jump in the deep ocean. Predictions in the Red Sea Outflow in the Gulf of Aden are relatively uncertain. Available data, and the model predictions, do not provide strong support for the existence of hydraulic jumps. In the Mediterranean Outflow, however, both model and data indicate the presence of a hydraulic jump.

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