Analysis of Rectangular Side Sluice Gate

Swamee, Prabhata K.; Pathak, Shray; Ali, Masoud S.

doi:10.1061/(asce)0733-9437(1993)119:6(1026)

Cited by 40 publications

(9 citation statements)

References 3 publications

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“…Swamee et al . () also computed the elementary discharge coefficient using their proposed equation and compared it with those observed and found that the computed elementary coefficient was within ±10% of the observed ones. To check the accuracy of the equation for the discharge coefficient, Ghodsian () used average percentage error ε , defined as

ε = \frac{100}{N} \sum_{i = 1}^{N} |\frac{C_{d} ((), computed) - C_{d} ((), observed)}{C_{d} ((), observed)}|

…”

Section: Resultsmentioning

confidence: 79%

“…The proposed equation for C d for computation of discharge through the sluice gate is better than the equations proposed by Swamee et al . () and Ghodsian (). Based on the above discussion, it is concluded that the proposed equation can be used for the computation of discharge through the sluice gate with good accuracy within the range of data used for developing Equation ().…”

Section: Resultsmentioning

confidence: 99%

“…Focus on these problems is very limited and the available literature on the side sluice gate is Panda (), Swamee et al . () and Ghodsian (). Considering flow through a side sluice gate as a spatially varied flow, Swamee et al .…”

Section: Introductionmentioning

confidence: 99%

“…Considering flow through a side sluice gate as a spatially varied flow, Swamee et al . () and Ghodsian () introduced an elementary discharge coefficient for the discharge equation of the sluice gate and related this with the approximate Froude number, ratio of upstream depth and opening height of sluice gate for free flow conditions, and with an additional parameter ‘the ratio of tail‐water depth to the gate opening’ for the submerged flow. However, computation of discharge through the sluice gate using those equations is not straightforward, and needs solution of an implicit equation.…”

Section: Introductionmentioning

confidence: 99%

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Computation of Discharge Through Side Sluice Gate Using Gene‐expression Programming

Azamathulla

Ahmad

Ghani

2012

Irrigation and Drainage

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The existing equations for the computation of discharge through a sluice gate are derived based on the statistical approach and implicit in form. This paper presents an intelligent prediction of discharge through a side sluice gate under free flow conditions using gene-expression programming (GEP), which is an extension of genetic programming (GP). Considering the flow through a side sluice gate as orifice flow, a closed form equation for the prediction of discharge is derived. The coefficient of discharge is related to the approximate Froude number in the main channel and the ratio of upstream depth and gate opening. The proposed equation for the coefficient of discharge using GEP and available existing data produces better results (R 2 = 0.935 and RMSE = 0.0658) compared to the existing equations for the side sluice gate. The computed coefficient of discharge is within AE5% of those observed for the data used for the validation of the proposed equation. The average percentage error in the coefficient of discharge computed using proposed equation is of the order of 2.15. RÉSUMÉLes équations existantes pour le calcul débit d'une vanne à guillotine sont dérivées d'approches statistique et implicite. Cet article présente une prévision intelligente du débit d'une telle vanne en condition dénoyée à l'aide de la programmation d'expression génique (GEP), qui est une extension de la programmation génétique (GP). Considérant que l'écoulement à travers la vanne est proche de l'écoulement à travers un orifice, une équation de forme fermée a été dérivée. Le coefficient de débit est en relation avec une valeur approchée du nombre de Froude dans le canal principal, le rapport du tirant d'eau en amont et en aval, de l'ouverture de la vanne. L'équation proposée pour le coefficient de débit avec l'utilisation de GEP est confrontée aux données existantes; elle produit de meilleurs résultats (R2 = 0,935 et RMSE = 0,0658) que les équations existantes pour des vannes de ce type. Le coefficient de débit calculé est inférieur à AE 5% aux valeurs observées. Le pourcentage d'erreur moyenne du coefficient de débit calculé en utilisant l'équation proposée est de l'ordre 2,15.

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ε = \frac{100}{N} \sum_{i = 1}^{N} |\frac{C_{d} ((), computed) - C_{d} ((), observed)}{C_{d} ((), observed)}|

…”

Section: Resultsmentioning

confidence: 79%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Computation of Discharge Through Side Sluice Gate Using Gene‐expression Programming

Azamathulla

Ahmad

Ghani

2012

Irrigation and Drainage

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show abstract

“…For instance, Ramamurthy et al (1987), Gill (1987), Swamee et al (1993) and Ojha and Subbaiah (1997) examined the hydraulic behavior of gates and side orifices. Hussein et al (2010) conducted an experimental study on the behavior of the passing flow through rectangular channels with circular side orifice.…”

Section: Introductionmentioning

confidence: 99%

Optimization of ANFIS network using firefly algorithm for simulating discharge coefficient of side orifices

et al. 2019

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Side orifices are installed on side walls of the main channel to regulate and measure the flow. Generally, discharge coefficient is the most important hydraulic parameter of side orifices. In this study, using ANFIS and firefly algorithm, discharge coefficient of rectangular and circular side orifices was simulated. Firstly, effective parameters were defined then six ANFIS and ANFIS-FA models were introduced. Monte Carlo simulations were utilized to survey the ability of numerical models, and the k-fold cross-validation approach was used to validate numerical results. Then, a sensitivity analysis was employed to introduce the superior model. The superior model predicted discharge coefficient with reasonable accuracy. This model estimated discharge coefficient in terms of all input variables. For example, for ANFIS model, R and SI were computed 0.832 and 0.029, respectively. In addition, for the hybrid model, RMSE, MARE and SI were calculated as 0.017, 0.017 and 0.027, respectively. Additionally, the ratio of width of the main channel to the side orifice diameter (B/D) was identified as the most effective parameter.

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A New Approach to Estimate the Discharge Coefficient in Sharp-Crested Rectangular Side Orifices Using Gene Expression Programming

Bonakdari

Gharabaghi

Ebtehaj

et al. 2020

Advances in Intelligent Systems and Computing

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Analysis of Rectangular Side Sluice Gate

Cited by 40 publications

References 3 publications

Computation of Discharge Through Side Sluice Gate Using Gene‐expression Programming

Computation of Discharge Through Side Sluice Gate Using Gene‐expression Programming

Optimization of ANFIS network using firefly algorithm for simulating discharge coefficient of side orifices

A New Approach to Estimate the Discharge Coefficient in Sharp-Crested Rectangular Side Orifices Using Gene Expression Programming

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