Investigation of Free Flow Under the Sluice Gate with the Sill Using Flow-3D Model

Karami, Shima; Heidari, Mohammad Mehdi; Rad, Mohammad Hossein Adib

doi:10.1007/s40996-019-00310-x

Cited by 11 publications

(3 citation statements)

References 13 publications

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“…For example: the flow gauging test directly affects farmland irrigation; irrigation gates cannot be arbitrarily raised and lowered; the upstream water flow cannot be freely controlled; the water flow pattern needs some time to stabilize after the gate opening change; flow measurement equipment is greatly affected by environmental factors and large measurement errors can lead to low accuracy of the flow calculation model; and there is a lack of a professional testing institution and testing platform for the integrated measurement and control gates. Due to the above reasons, there are few reports of indoor flow gauging tests, and most scholars mainly use numerical simulation to conduct flow gauging tests [15,16]. The numerical simulation results need to be verified with actual measurement data, so there is an urgent need to conduct indoor flow gauging tests to provide data support for subsequent research.…”

Section: Flow Gauging Test Of the Integrated Measurement And Control ...mentioning

confidence: 99%

Flow Prediction of a Measurement and Control Gate Based on an Optimized Back Propagation Neural Network

Hou,

Niu,

Zhu

et al. 2023

Applied Sciences

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The measurement and control gate, as a new type of measurement and control equipment, has been widely used for water quantity control in irrigation areas. However, there is a lack of methods for calibrating the flow inside the measurement box at present. This paper establishes a flow prediction model based on a back propagation (BP) neural network and its optimization algorithm by using 450 sets of sample data obtained from the indoor gate overflow test and verified the effectiveness and accuracy of the prediction model by using another 205 sets of sample data. The results show that the gate flow prediction model based on a BP neural network and its optimization algorithm has self-adaptability to different flow patterns, and its prediction accuracy is significantly higher than that of the traditional water measurement method. Compared to the unoptimized BP model, the BP model optimized by the genetic algorithm (GA) or particle swarm optimization (PSO) has higher prediction accuracy and better error distribution. Both GA and PSO algorithms can be used to optimize the initial weights and thresholds of the BP flow prediction model. However, by comprehensively analyzing the prediction accuracy, error distribution, and running time, the PSO algorithm has better optimization performance compared to the GA algorithm. The prediction model can provide a reference for flow rate calibration and the anomaly rejection of measurement and control gates in the irrigation area.

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Section: Flow Gauging Test Of the Integrated Measurement And Control ...mentioning

confidence: 99%

Flow Prediction of a Measurement and Control Gate Based on an Optimized Back Propagation Neural Network

Hou,

Niu,

Zhu

et al. 2023

Applied Sciences

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“…Salmasi and Norouzi [12] showed that a circular sill increases the C d value by at least 23-31%. Karami et al [13] numerically investigated the effect of geometric sill shape on C d ; they found that the semicircular sill has a greater effect. Salmasi and Abraham [14] carried out experiments on sills.…”

Section: Introductionmentioning

confidence: 99%

Sill Role Effect on the Flow Characteristics (Experimental and Regression Model Analytical)

Abbaszadeh,

Norouzi,

Sume

et al. 2023

Fluids

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This study investigates the effects of gate openings and different sill widths on the sluice gate’s energy dissipation and discharge coefficient (Cd). The physical model of the sills includes rectangular sills of different dimensions. The results show that the gate opening size is inversely related to the Cd for a gate without a sill. In addition, increasing the gate opening size for a given discharge decreases the relative energy dissipation, and increasing the Froude number increases the relative energy dissipation. The results also show that the Cd and relative energy dissipation decrease when the width of the sill is decreased, thus increasing the total area of the flux flowing through the sluice gate and vice versa. According to the experimental results, the relative energy dissipation and the Cd of the sluice gate are larger for all sill widths than without the sill. Finally, non-linear polynomial relationships are presented based on dimensionless parameters for predicting the relative energy dissipation and outflow coefficient.

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“…A sluice is considered as a typical structural system that is frequently used in the field of water infrastructure engineering. To meet the demand of water conservancy functions such as flood control, irrigation, drainage, water diversion, and environmental protection, a great number of sluices have been constructed [ 1 , 2 ]. Hoist beams are important structural components in sluice systems, bearing significant dynamic loads when the sluice gates are opened.…”

Section: Introductionmentioning

confidence: 99%

Identification of Damage on Sluice Hoist Beams Using Local Mode Evoked by Swept Frequency Excitation

Wei

et al. 2021

Sensors

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As a global vibration characteristic, natural frequency often suffers from insufficient sensitivity to structural damage, which is associated with local variations of structural material or geometric properties. Such a drawback is particularly significant when dealing with the large scale and complexity of sluice structural systems. To this end, a damage detection method in sluice hoist beams is proposed that relies on the utilization of the local primary frequency (LPF), which is obtained based on the swept frequency excitation (SFE) technique and local resonance response band (LRRB) selection. Using this method, the local mode of the target sluice hoist beam can be effectively excited, while the vibrations of other components in the system are suppressed. As a result, the damage will cause a significant shift in the LPF of the sluice hoist beam at the local mode. A damage index was constructed to quantitatively reflect the damage degree of the sluice hoist beam. The accuracy and reliability of the proposed method were verified on a three-dimensional finite element model of a sluice system, with the noise resistance increased from 0.05 to 0.2 based on the hammer impact method. The proposed method exhibits promising potential for damage detection in complex structural systems.

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Investigation of Free Flow Under the Sluice Gate with the Sill Using Flow-3D Model

Cited by 11 publications

References 13 publications

Flow Prediction of a Measurement and Control Gate Based on an Optimized Back Propagation Neural Network

Flow Prediction of a Measurement and Control Gate Based on an Optimized Back Propagation Neural Network

Sill Role Effect on the Flow Characteristics (Experimental and Regression Model Analytical)

Identification of Damage on Sluice Hoist Beams Using Local Mode Evoked by Swept Frequency Excitation

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