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

2020 ◽  
pp. 77-96
Author(s):  
Hossein Bonakdari ◽  
Bahram Gharabaghi ◽  
Isa Ebtehaj ◽  
Ali Sharifi
Keyword(s):  
Gene Expression ◽  
Discharge Coefficient ◽  
Gene Expression Programming ◽  
New Approach

Discharge coefficients for ogee weirs including the effects of a sloping upstream face

2020 ◽  
Vol 20 (4) ◽  
pp. 1493-1508 ◽  
Author(s):  
Farzin Salmasi ◽  
John Abraham
Keyword(s):  
Gene Expression ◽  
Experimental Data ◽  
Regression Analysis ◽  
Discharge Coefficient ◽  
Gene Expression Programming ◽  
Linear Interpolation ◽  
Performance Criteria ◽  
Upstream Face ◽  
Discharge Coefficients ◽  
Regression Techniques

Abstract Discharge coefficients (C0) for ogee weirs are essential factors for predicting the discharge-head relationship. The present study investigates three influences on the C0: effect of approach depth, weir upstream face slope, and the actual head, which may differ from the design head. This study uses experimental data with multiple non-linear regression techniques and Gene Expression Programming (GEP) models that are applied to introduce practical equations that can be used for design. Results show that the GEP method is superior to the regression analysis for predicting the discharge coefficient. Performance criteria for GEP are R2 = 0.995, RMSE = 0.021 and MAE = 0.015. Design examples are presented that show that the proposed GEP equation correlates well with the data and eliminates linear interpolation using existing graphs.

scholarly journals Prediction of Discharge Capacity of Labyrinth Weir with Gene Expression Programming

2020 ◽  
Author(s):  
Hossein Bonakdari ◽  
Isa Ebtehaj ◽  
Bahram Gharabaghi ◽  
Ali Sharifi ◽  
Amir Mosavi
Keyword(s):  
Gene Expression ◽  
Relative Error ◽  
Discharge Coefficient ◽  
Gene Expression Programming ◽  
Vertex Angle ◽  
Dimensionless Parameters ◽  
Labyrinth Weir ◽  
Predicted Values ◽  
Crest Length ◽  
Labyrinth Weirs

This paper proposes a model based on gene expression programming for predicting discharge coefficient of triangular labyrinth weirs. The parameters influencing discharge coefficient prediction were first examined and presented as crest height ratio to the head over the crest of the weir (p/y), crest length of water to channel width (L/W), crest length of water to the head over the crest of the weir (L/y), Froude number (F=V/√(gy)) and vertex angle () dimensionless parameters. Different models were then presented using sensitivity analysis in order to examine each of the dimensionless parameters presented in this study. In addition, an equation was presented through the use of nonlinear regression (NLR) for the purpose of comparison with GEP. The results of the studies conducted by using different statistical indexes indicated that GEP is more capable than NLR. This is to the extent that GEP predicts the discharge coefficient with an average relative error of approximately 2.5% in such a manner that the predicted values have less than 5% relative error in the worst model.

Gene expression programming to predict the discharge coefficient in rectangular side weirs

2015 ◽  
Vol 35 ◽  
pp. 618-628 ◽  
Author(s):  
Isa Ebtehaj ◽  
Hossein Bonakdari ◽  
Amir Hossein Zaji ◽  
Hamed Azimi ◽  
Ali Sharifi
Keyword(s):  
Gene Expression ◽  
Discharge Coefficient ◽  
Gene Expression Programming ◽  
Side Weirs
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