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Prediction of Optimum Intak Angle at Open Channel Junction Using Gene Expression Programing Technique

    Authors

    • Batool Alaa Mousa 1
    • Abdulkider Aziz Mutasher 1
    • Fatima Asaad Mahdi 2

    1 Department of Civil Techniques, Kerbala Technical Institute, Al-Furat Al-Awsat Technical University, Kerbala, Iraq

    2 Department of Civil Techniques, Babylon Technical Institute, Al-Furat Al-Awsat Technical University, Babylon, Iraq

,

Document Type : Research Article

10.63463/kjes1185
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Abstract

Usually, water intakes are used to divert water from the primary canal or river to the tertiary canals and turbine systems. In cases when the flow is being separated at the branch channel's inlet, the flow structure in this area is more intricate than in other parts of the network. For the most part, intakes are built at right angles, which creates a sizable separation zone at the entrance of the subchannel and decreases flow discharge. In order to minimize the separation zone's dimensions, the intake should be positioned at the best possible angle. A numerical study was run in a rectangular channel with a side channel branching off of it to determine the optimal intake angle. To achieved this study, eleven intakes were installed on one side of the main channel at varying angles of 15, 30, 45, 60, 75, 90, 105, 120, 135, 150 and 165 degrees to find the optimum intake position. Additionally, a unique method for estimating the separation zone's dimensions utilizing an advanced microcomputing modeling approach called Gene Expression Programming (GEP) has been proposed as a result of the study's findings. The outcomes of the numerical simulation were then utilize to make a compare between the GEP model and the nonlinear regression model (NLR). As a comparison, high R values and small RMSE and MAE indicate that the empirical formula derived using the GEP program is superior to the NLR formula (R2=0.903, RMSE=0.109, and MAE=0.092).

Keywords

  • Branching Angle
  • GEP Model
  • NLR Model
  • Shape Index
  • Separation Zone
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References
[1]          A. Keshavarzi and L. Habibi, "Optimizing water intake angle by flow separation analysis," Irrigation and Drainage: The journal of the International Commission on Irrigation and Drainage, vol. 54, no. 5, pp. 543-552, 2005, doi: https://doi.org/10.1002/ird.207.
[2]          W. H. Al-Mussawi, "Numerical analysis of velocity profile and separation zone in open channel junctions," Al-Qadisiyah Journal for Engineering Sciences, vol. 2, no. 2, pp. 262-274, 2009.
[3]          M. Heydari and S. Shabanlou, "The effects of flow division angle in rectangular channel branches," Water and Soil Science, vol. 30, no. 1, pp. 193-204, 2020, doi: https://dor.isc.ac/dor/20.1001.1.20085133.1399.30.1.15.1.
[4]          FLOW-3Dmanual, "FLOW-3D user manual," N. Flow Science Santa Fe, Ed., ed, 2017.
[5]          M. Muzzammil, J. Alama, and M. Danish, "Scour prediction at bridge piers in cohesive bed using gene expression programming," Aquatic Procedia, vol. 4, pp. 789-796, 2015, doi: https://doi.org/10.1016/j.aqpro.2015.02.098.
[6]          M. Najafzadeh and G.-A. Barani, "Comparison of group method of data handling based genetic programming and back propagation systems to predict scour depth around bridge piers," Scientia Iranica, vol. 18, no. 6, pp. 1207-1213, 2011, doi: https://doi.org/10.1016/j.scient.2011.11.017.
[7]          H. M. Azamathulla, A. A. Ghani, N. A. Zakaria, and A. Guven, "Genetic programming to predict bridge pier scour," Journal of Hydraulic Engineering, vol. 136, no. 3, p. 165, 2010, doi: https://doi.org/10.1061/(ASCE)HY.1943-7900.0000133.
[8]          M. Najafzadeh and H. M. Azamathulla, "Neuro-fuzzy GMDH to predict the scour pile groups due to waves," Journal of Computing in Civil Engineering, vol. 29, no. 5, p. 04014068, 2015, doi: https://doi.org/10.1061/(ASCE)CP.1943-5487.0000376.
[9]          M. Khan, H. M. Azamathulla, and M. Tufail, "Gene-expression programming to predict pier scour depth using laboratory data," Journal of Hydroinformatics, vol. 14, no. 3, pp. 628-645, 2012, doi: https://doi.org/10.2166/hydro.2011.008.
[10]        Y. A. M. Moussa, "Modeling of local scour depth downstream hydraulic structures in trapezoidal channel using GEP and ANNs," Ain Shams Engineering Journal, vol. 4, no. 4, pp. 717-722, 2013, doi: https://doi.org/10.1016/j.asej.2013.04.005.
[11]        A. Ramamurthy, J. Qu, and D. Vo, "Numerical and experimental study of dividing open-channel flows," Journal of Hydraulic Engineering, vol. 133, no. 10, pp. 1135-1144, 2007, doi: https://doi.org/10.1061/(ASCE)0733-9429(2007)133:10(1135).
[12]        C. Ferreira, Gene expression programming: mathematical modeling by an artificial intelligence. Springer, 2006.
[13]        C. Ferreira, "Gene expression programming: a new adaptive algorithm for solving problems," arXiv preprint cs/0102027, 2001, doi: https://doi.org/10.48550/arXiv.cs/0102027.
[14]        A. Ab. Ghani and H. Md. Azamathulla, "Gene-expression programming for sediment transport in sewer pipe systems," Journal of pipeline systems engineering and practice, vol. 2, no. 3, pp. 102-106, 2011, doi: https://doi.org/10.1061/(ASCE)PS.1949-1204.0000076.
[15]        Z. Xie, X. Li, B. Di Eugenio, W. Xiao, T. M. Tirpak, and P. C. Nelson, "Using gene expression programming to construct sentence ranking functions for text summarization," in COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics, 2004, pp. 1381-1384.
[16]        A. Fernando, A. Shamseldin, and R. Abrahart, "Using gene expression programming to develop a combined runoff estimate model from conventional rainfall-runoff model outputs," in Proc., 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation, 2009, pp. 2377-2383, doi: http://mssanz.org.au/modsim09.
[17]        K. A. Eldrandaly and A.-A. Negm, "Performance Evaluation of Gene Expression Programming for Hydraulic Data Mining," Int. Arab J. Inf. Technol., vol. 5, no. 2, pp. 126-131, 2008.
[18]        A. Bărbulescu and E. Băutu, "Time series modeling using an adaptive gene expression programming algorithm," International journal of mathematical models and methods in applied sciences, vol. 3, no. 2, pp. 85-93, 2009.
[19]        S. Dehuri and S.-B. Cho, "Multi-objective classification rule mining using gene expression programming," in 2008 Third International Conference on Convergence and Hybrid Information Technology, 2008, vol. 2: IEEE, pp. 754-760, doi: https://doi.org/10.1109/ICCIT.2008.27.
 
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Kerbala Journal for Engineering Sciences
Volume 5, Issue 3
September 2025
Pages 92-116
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  • Article View: 242
  • PDF Download: 87

APA

Mousa, B., Mutasher, A., & Mahdi, F. (2025). Prediction of Optimum Intak Angle at Open Channel Junction Using Gene Expression Programing Technique. Kerbala Journal for Engineering Sciences, 5(3), 92-116. doi: 10.63463/kjes1185

MLA

Batool Alaa Mousa; Abdulkider Aziz Mutasher; Fatima Asaad Mahdi. "Prediction of Optimum Intak Angle at Open Channel Junction Using Gene Expression Programing Technique". Kerbala Journal for Engineering Sciences, 5, 3, 2025, 92-116. doi: 10.63463/kjes1185

HARVARD

Mousa, B., Mutasher, A., Mahdi, F. (2025). 'Prediction of Optimum Intak Angle at Open Channel Junction Using Gene Expression Programing Technique', Kerbala Journal for Engineering Sciences, 5(3), pp. 92-116. doi: 10.63463/kjes1185

VANCOUVER

Mousa, B., Mutasher, A., Mahdi, F. Prediction of Optimum Intak Angle at Open Channel Junction Using Gene Expression Programing Technique. Kerbala Journal for Engineering Sciences, 2025; 5(3): 92-116. doi: 10.63463/kjes1185

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