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Taji, Milad, Morsali, Massoud, Eilbeigi, Mehdi. (1404). Estimation of Energy Dissipation in Non-Aerated Flow Regimes over Stepped Spillways Using Advanced Soft Computing Techniques. پژوهشنامه مدیریت اجرایی, 1(1), 68-77. doi: 10.22080/ceas.2025.29211.1012
Milad Taji; Massoud Morsali; Mehdi Eilbeigi. "Estimation of Energy Dissipation in Non-Aerated Flow Regimes over Stepped Spillways Using Advanced Soft Computing Techniques". پژوهشنامه مدیریت اجرایی, 1, 1, 1404, 68-77. doi: 10.22080/ceas.2025.29211.1012
Taji, Milad, Morsali, Massoud, Eilbeigi, Mehdi. (1404). 'Estimation of Energy Dissipation in Non-Aerated Flow Regimes over Stepped Spillways Using Advanced Soft Computing Techniques', پژوهشنامه مدیریت اجرایی, 1(1), pp. 68-77. doi: 10.22080/ceas.2025.29211.1012
Taji, Milad, Morsali, Massoud, Eilbeigi, Mehdi. Estimation of Energy Dissipation in Non-Aerated Flow Regimes over Stepped Spillways Using Advanced Soft Computing Techniques. پژوهشنامه مدیریت اجرایی, 1404; 1(1): 68-77. doi: 10.22080/ceas.2025.29211.1012

Estimation of Energy Dissipation in Non-Aerated Flow Regimes over Stepped Spillways Using Advanced Soft Computing Techniques

Civil Engineering and Applied Solutions
مقاله 4، دوره 1، شماره 1، شهریور 2025، صفحه 68-77    اصل مقاله (1.06 M)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22080/ceas.2025.29211.1012
نویسندگان
Milad Taji1؛ Massoud Morsali* 2؛ Mehdi Eilbeigi3
1Department of Civil engineering (hydraulic structures), University of Shahrkord, Shahrkord, Iran
2Department of Geology, Faculty of Science, University of Isfahan, Isfahan, Iran
3Department of Hydrogeology, Shahid Chamran University, Ahvaz, Iran
تاریخ دریافت: 20 اردیبهشت 1404،  تاریخ پذیرش: 27 اردیبهشت 1404 
چکیده
Stepped spillways have garnered significant attention due to their high efficiency in dissipating flow energy, primarily attributed to the presence of steps that enhance turbulence and energy loss. A stepped spillway consists of a sequence of vertical drops extending from the crest at the upstream end to the stilling basin at the downstream. Under high discharge conditions, the flow regime transitions into non-aerated skimming flow, characterized by substantial energy levels that necessitate careful management. Accurate estimation of energy dissipation is essential for the safe and economical design of downstream energy dissipators. In this study, 154 experimental data points from physical models of stepped spillways were utilized, encompassing a broad range of hydraulic conditions by varying parameters such as the drop number, spillway slope, number of steps, critical depth-to-step height ratio, and Froude number. To predict the energy dissipation, several soft computing techniques were applied, including Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), and Support Vector Regression (SVR). The models' predictive capabilities were assessed using key statistical performance metrics, including the coefficient of determination ( ), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). Comparative analysis of the results demonstrated that the ANN model exhibited superior accuracy over the other models, achieving , RMSE, and MAE values of 0.99, 0.96, and 0.67, respectively. The findings underscore the potential of soft computing models, particularly ANN, as powerful predictive tools in hydraulic engineering applications. The proposed modeling approach offers an effective means for estimating energy dissipation in stepped spillways, facilitating optimized and cost-effective design of hydraulic structures.
کلیدواژه‌ها
Stepped spillways؛ ANFIS؛ ANN؛ Soft models؛ Energy dissipation؛ SVR
مراجع
  1. Parsaie, A., Haghiabi, A. H., Saneie, M., Torabi, H. Applications of Soft Computing Techniques for Prediction of Energy Dissipation on Stepped Spillways. Neural Computing and Applications, 2018; 29 (12): 1393–1409. doi:10.1007/s00521-016-2667-z.
  2. Mohammad Rezapour Tabari, M., Tavakoli, S. Effects of Stepped Spillway Geometry on Flow Pattern and Energy Dissipation. Arabian Journal for Science and Engineering, 2016; 41 (4): 1215–1224. doi:10.1007/s13369-015-1874-8.
  3. Mishra, C.S., Ojha, S. P. Prediction of energy dissipation in skimming flow of stepped spillway by using machine learning approach. In: Pandey M, Umamahesh NV, Ahmad Z, Oliveto G, editors. Hydraulics and fluid mechanics. Volume 1. Singapore: Springer Nature Singapore; 2025. p. 423–38.
  4. Mojtahedi, A., Soori, N., Mohammadian, M. Energy Dissipation Evaluation for Stepped Spillway Using a Fuzzy Inference System. SN Applied Sciences, 2020; 2 (8). doi:10.1007/s42452-020-03258-0.
  5. Mei, J., Zhou, Y., Xu, K., Xu, G., Shu, Z., Gan, Q., et al. Energy dissipation on inclined stepped spillways. Water. 2025;17(2):251. doi:10.3390/w17020251.
  6. Li, S., Zhang, J., Nie, J., Peng, Y. Energy Dissipation and Flow Characteristics of Baffles and Sills on Stepped Spillways. Journal of Hydraulic Research, 2014; 52 (1): 140–142. doi:10.1080/00221686.2013.856040.
  7. Chanson, H. Jet Flow on Stepped Spillways. Journal of Hydraulic Engineering, 1995; 121 (5): 441–448. doi:10.1061/(asce)0733-9429(1995)121:5(441).
  8. Torabi, S., Rostami, A., Torabi, S., Boustani, F., Roushan, A. Energy Dissipation on Stepped Spillways with Reverse Inclination. Water Resources Engineering, 6 (Vol6/No17/Summer 2013): 63–78.
  9. hamani, M.R., Rajaratnam, N. Characteristics of skimming flow over stepped spillways. Journal of Hydraulic Engineering, 1999; 125(4): 361–368. doi:10.1061/(ASCE)0733-9429(1999)125:4(361).
  10. Asghari Pari, S. A., Kordnaeij, M., Razmkhah, A. Experimental study of flow characteristics in a stepped spillway with the installation of a continuous obstacle with different geometric characteristics. Journal of Hydraulics, 2025; 20(1): 91-109. doi: 10.30482/jhyd.2024.433085.1690.
  11. Zhou, Y., Wu, J., Ma, F., Qian, S. Experimental Investigation of the Hydraulic Performance of a Hydraulic-Jump-Stepped Spillway. KSCE Journal of Civil Engineering, 2021; 25 (10): 3758–3765. doi:10.1007/s12205-021-1709-y.
  12. Ikinciogullari, E. A Novel Design for Stepped Spillway Using Staggered Labyrinth Trapezoidal Steps. Flow Measurement and Instrumentation, 2023; 93: 102439. doi:10.1016/j.flowmeasinst.2023.102439.
  13. Salmasi, F., Özger, M. Neuro-Fuzzy Approach for Estimating Energy Dissipation in Skimming Flow over Stepped Spillways. Arabian Journal for Science and Engineering, 2014; 39 (8): 6099–6108. doi:10.1007/s13369-014-1240-2.
  14. Tabbara, M., Chatila, J., Awwad, R. Computational Simulation of Flow over Stepped Spillways. Computers and Structures, 2005; 83 (27): 2215–2224. doi:10.1016/j.compstruc.2005.04.005.
  15. Felder, S., Chanson, H. Energy Dissipation, Flow Resistance and Gas-Liquid Interfacial Area in Skimming Flows on Moderate-Slope Stepped Spillways. Environmental Fluid Mechanics, 2009; 9(4): 427–441. doi:10.1007/s10652-009-9130-y.
  16. Hamedi, A., Malekmohammadi, I., Mansoori, A., Roshanaei, H. Energy dissipation in stepped spillway equipped with inclined steps together with end sill. In: Proceedings of the Fourth International Conference on Computational Intelligence and Communication Networks; 2012 Nov 3–5; Mathura, India. p. 638–42. doi:10.1109/CICN.2012.109.
  17. Husain, S. M., Muhammed, J. R., Karunarathna, H. U., Reeve, D. E. Investigation of Pressure Variations over Stepped Spillways Using Smooth Particle Hydrodynamics. Advances in Water Resources, 2014; 66: 52–69. doi:10.1016/j.advwatres.2013.11.013.
  18. Hou, X., Chen, J., Yang, J. The numerical simulation of aeration and energy dissipation for stepped spillway. In: Proceedings of the 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC 2013); 2013 Dec 20–22; Shenyang, China. IEEE; 2013. p. 2495–9. doi:10.1109/MEC.2013.6885456.
  19. Shahheydari, H., Nodoshan, E. J., Barati, R., Moghadam, M. A. Discharge Coefficient and Energy Dissipation over Stepped Spillway under Skimming Flow Regime. KSCE Journal of Civil Engineering, 2015; 19(4): 1174–1182. doi:10.1007/s12205-013-0749-3.
  20. Khatibi, R., Salmasi, F., Ghorbani, M. A., Asadi, H. Modelling Energy Dissipation Over Stepped-Gabion Weirs by Artificial Intelligence. Water Resources Management, 2014; 28(7): 1807–1821. doi:10.1007/s11269-014-0545-y.
  21. Mostefa, G., Kheira, B., Abdelkader, D., Naima, D. Study of the Effect of the Rate Flow and the Slope of the Channel on the Energy Dissipation in the Stepped Channels: Proposing an Empirical Models. Procedia Engineering, 2015; 118: 1044–1051. doi:10.1016/j.proeng.2015.08.547.
  22. Hanbay, D., Baylar, A., Ozpolat, E. Predicting Flow Conditions over Stepped Chutes Based on ANFIS. Soft Computing, 2009; 13(7): 701–707. doi:10.1007/s00500-008-0343-7.
  23. Roushangar, K., Akhgar, S., Salmasi, F., Shiri, J. Modeling Energy Dissipation over Stepped Spillways Using Machine Learning Approaches. Journal of Hydrology, 2014; 508: 254–265. doi:10.1016/j.jhydrol.2013.10.053.
  24. Ekmekcioğlu, Ö., Başakın, E. E., Özger, M. Tree-Based Nonlinear Ensemble Technique to Predict Energy Dissipation in Stepped Spillways. European Journal of Environmental and Civil Engineering, 2022; 26(8): 3547–3565. doi:10.1080/19648189.2020.1805024.
  25. Baharvand, S., Rezaei, R., Talebbeydokhti, N., Nasiri, R., Amiri, S. M. Investigation of Energy Dissipation Rate of Stepped Vertical Overfall (SVO) Spillway Using Physical Modeling and Soft Computing Techniques. KSCE Journal of Civil Engineering, 2022; 26(12): 5067–5081. doi:10.1007/s12205-022-1870-y.
  26. Tabari, M. M. R., Azari, T., Dehghan, V. A Supervised Committee Neural Network for the Determination of Aquifer Parameters: A Case Study of Katasbes Aquifer in Shiraz Plain, Iran. Soft Computing, 2021; 25(6): 4785–4798. doi:10.1007/s00500-020-05487-2.
  27. Jafari, S. M., Zahiri, A. R., Bozorg Hadad, O., Mohammad Rezapour Tabari, M. A Hybrid of Six Soft Models Based on ANFIS for Pipe Failure Rate Forecasting and Uncertainty Analysis: A Case Study of Gorgan City Water Distribution Network. Soft Computing, 2021; 25(11): 7459–7478. doi:10.1007/s00500-021-05706-4.
  28. Tabari, M. M. R., Sanayei, H. R. Z. Prediction of the Intermediate Block Displacement of the Dam Crest Using Artificial Neural Network and Support Vector Regression Models. Soft Computing, 2019; 23(19): 9629–9645. doi:10.1007/s00500-018-3528-8.
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