Experimental and Machine Learning Approaches for Discharge Estimation in Arched Labyrinth Weirs
Keywords:
Labyrinth weir, Coefficient of discharge, Froude number, Artificial Neural NetworkAbstract
A weir is a hydraulic structure installed across or parallel to an open channel to regulate or measure flow discharge. Weirs are classified based on shape, discharge characteristics, crest width, and crest type. Among these, the arched labyrinth weir is characterized by its extended crest length, achieved through arching and notches, which enhances its hydraulic efficiency. This study presents a comprehensive analytical and experimental investigation into the discharge characteristics of arched labyrinth weirs in open channels. The artificial neural network model demonstrated exceptional predictive performance, achieving a mean squared error of 2.84×10−7, a mean absolute percentage error of 0.000191, and a correlation coefficient approaching 1, highlighting its accuracy and reliability in discharge estimation.
References
1. Amanian, N. (1987). Performance and design of labyrinth spillway. 99. https://digitalcommons.usu.edu/etd/7658/
2. Ansari, M. F., Hussain, A., & Ahmad Ansari, M. (2021). Experimental studies and model development of flow over Arched Labyrinth Weirs using GMDH method. Journal of Applied Water Engineering and Research, 9(4), 265–276. https://doi.org/10.1080/23249676.2020.1799443
3. Reddy, V. A. R. (2024). Generative Intelligence for Healthcare Claims Processing and Personalized Benefits Management. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 7(3), 14099.
4. Ayaz, M., Chourasiya, S., & Danish, M. (2023). Performance analysis of different ANN modelling techniques in discharge prediction of circular side orifice. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-023-01766-7
5. Azimi, H., Shabanlou, S., Ebtehaj, I., Bonakdari, H., & Kardar, S. (2017). Combination of Computational Fluid Dynamics, Adaptive Neuro-Fuzzy Inference System, and Genetic Algorithm for Predicting Discharge Coefficient of Rectangular Side Orifices. Journal of Irrigation and Drainage Engineering, 143(7). https://doi.org/10.1061/(ASCE)IR.1943-4774.0001190
6. Kolla, S. H. (2024). Retrieval-Augmented Enterprise Intelligence: Enhancing Accuracy, Trust, and Operational Decision-Making. International Journal of Future Innovative Science and Technology (IJFIST), 7(2), 12425.
7. Bilhan, O., & Emiroglu, M. E. (2016). Experimental Studies on Determination of Discharge Capacity of Circular Labyrinth Weirs Located on A Straight Channel. International Journal of Electronics, Mechanical and Mechatronics Engineering, 6, 1227–1239. https://api.semanticscholar.org/CorpusID:62910498
8. Crookston, B. M. (2010). Labyrinth weirs (Ph. D. Dissertation). Logan: Utah State University Library, 95–122.
9. Crookston, B. M., Flake, L. K., & Felder, S. (2024). Flow Nonuniformity and Energy Dissipation in Moderate-Sloped Stepped Chutes with a Labyrinth Crest. Journal of Hydraulic Engineering, 150(5). https://doi.org/10.1061/JHEND8.HYENG-13881
10. Nagubandi, A. R. (2023). Advanced Multi-Agent AI Systems for Autonomous Reconciliation Across Enterprise Multi-Counterparty Derivatives, Collateral, and Accounting Platforms. International Journal of Finance (IJFIN)-ABDC Journal Quality List, 36(6), 653-674.
11. Crookston, B. M., & Tullis, B. P. (2012). Labyrinth Weirs: Nappe Interference and Local Submergence. Journal of Irrigation and Drainage Engineering, 138(8), 757–765. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000466
12. Crookston, B. M., & Tullis, B. P. (2013). Hydraulic Design and Analysis of Labyrinth Weirs. II: Nappe Aeration, Instability, and Vibration. Journal of Irrigation and Drainage Engineering, 139(5), 371–377. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000553
13. Loganathan, R. (2024). GENERATIVE AI-ENABLED COMPLIANCE DOCUMENTATION AND AUDIT TRAIL AUTOMATION FOR GLOBAL DATA CENTER GOVERNANCE. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 15(3), 487-504.
14. Darvas, L. A. (1971). Discussion of “Performance and Design of Labyrinth Weirs.” Journal of the Hydraulics Division, 97(8), 1246–1251. https://doi.org/10.1061/JYCEAJ.0003056
15. Ebtehaj, I., Bonakdari, H., Khoshbin, F., & Azimi, H. (2015). Pareto genetic design of group method of data handling type neural network for prediction discharge coefficient in rectangular side orifices. Flow Measurement and Instrumentation, 41, 67–74. https://doi.org/10.1016/j.flowmeasinst.2014.10.016
16. Ghodsian, M. (2009). Stage–discharge relationship for a triangular labyrinth spillway. Proceedings of the Institution of Civil Engineers - Water Management, 162(3), 173–178. https://doi.org/10.1680/wama.2009.00033
17. Aitha, A. R. (2021). Dev Ops Driven Digital Transformation: Accelerating Innovation In The Insurance Industry. Available at SSRN 5622190.
18. Hay, N., & Taylor, G. (1970). Performance and Design of Labyrinth Weirs. Journal of the Hydraulics Division, 96(11), 2337–2357. https://doi.org/10.1061/JYCEAJ.0002766
19. Hornik, K., Stinchcombe, M., & White, H. (1989). Multilayer feedforward networks are universal approximators. Neural Networks, 2(5), 359–366. https://doi.org/10.1016/0893-6080(89)90020-8
20. Kolla, S. K. (2024). Clinical Knowledge Intelligence through Deep Learning and Natural Language Understanding in Healthcare Platforms. International Journal of Advanced Engineering Science and Information Technology (IJAESIT), 7(3), 14088.
21. Houston, K. L. (1982). Hydraulic model study of Ute Dam labyrinth spillway. Report GR-82-7 August 1982. 47 p, 30 Fig, 2 Tab, 4 Ref, 1 Append.
22. Hussain, R. A., Hassan, S. A., & Jamel, A. A. J. (2022). Experimental Study on Flow over Triangular Labyrinth Weirs. International Journal of Design & Nature and Ecodynamics, 17(2), 249–255. https://doi.org/10.18280/ijdne.170211
23. Idrees, A. K., & Al-Ameri, R. (2022). Improving the performance of the compound labyrinth weirs using an artificial ventilation approach. Water Supply, 22(8), 6585–6602. https://doi.org/10.2166/ws.2022.260
24. Idrees, A. K., & Al-Ameri, R. (2023). Investigation of flow characteristics and energy dissipation over new shape of the trapezoidal labyrinth weirs. Flow Measurement and Instrumentation, 89, 102276. https://doi.org/10.1016/j.flowmeasinst.2022.102276
25. Davuluri, P. N. (2020). Event-Driven Architectures for Real-Time Regulatory Monitoring in Global Banking.
26. Idrees, A. K., Al-Ameri, R., Chua, L. H. C., & Das, S. K. (2018). Discharge characteristics for trapezoidal compound labyrinth. https://api.semanticscholar.org/CorpusID:190202605
27. Idrees, A. K., Al-Ameri, R., & Das, S. K. (2016). Determination of discharge coefficient for flow over one cycle compound trapezoidal plan form labyrinth weir. https://api.semanticscholar.org/CorpusID:76655879
28. Khode, B. V, & Tembhurkar, A. R. (2010). Evaluation and Analysis of Crest Coefficient for Labyrinth Weir. World Applied Sciences Journal, 11, 835–839. https://api.semanticscholar.org/CorpusID:16856730
29. Lux, F. (1984). Discharge Characteristics of Labyrinth Weirs. Water for Resource Development, 385–389. https://api.semanticscholar.org/CorpusID:116591065
30. Ramamurthy, A. S., Tim, U. S., & Sarraf, S. (1986). Rectangular Lateral Orifices in Open Channels. Journal of Environmental Engineering, 112(2), 292–300. https://doi.org/10.1061/(ASCE)0733-9372(1986)112:2(292)
31. Inala, R. Advancing Group Insurance Solutions Through Ai-Enhanced Technology Architectures And Big Data Insights.
32. Sangsefidi, Y., Mehraein, M., & Ghodsian, M. (2018). Experimental study on flow over in-reservoir arced labyrinth weirs. Flow Measurement and Instrumentation, 59, 215–224. https://doi.org/10.1016/j.flowmeasinst.2017.12.002
33. Savage, B. M., Frizell, K. H., & Crowder, J. W. (2004). Brains versus Brawn : The Changing World of Hydraulic Model Studies. https://api.semanticscholar.org/CorpusID:46743321
34. Taylor, G. (1968). The performance of labyrinth weirs. University of Nottingham Nottingham, England.
35. Tullis, B. P., Young, J. C., & Chandler, M. A. (2007). Head-Discharge Relationships for Submerged Labyrinth Weirs. Journal of Hydraulic Engineering, 133(3), 248–254. https://doi.org/10.1061/(ASCE)0733-9429(2007)133:3(248)
36. Tullis, J. P., Amanian, N., & Waldron, D. (1995). Design of Labyrinth Spillways. Journal of Hydraulic Engineering, 121(3), 247–255. https://doi.org/10.1061/(ASCE)0733-9429(1995)121:3(247)
37. Yousif, O. S. Q., & Karakouzian, M. (2020). Effect of Corner Shape on Hydraulic Performance of One-Cycle Rectangular Labyrinth Weirs. Fluids, 5(3), 117. https://doi.org/10.3390/fluids5030117
38. Md Ayaz; Mohd Danish. [In Press]. “Discussion of “A Novel and Enhanced Calibration of the Tilting Weir as a Flow Measurement Structure" by Joseph E. Pugh et al.” Journal of Hydraulic Engineering. 10.1061/JHEND8/HYENG-14206
Additional Files
Published
Data Availability Statement
The data used in this study will be available on reasonable request to the corresponding author.
Issue
Section
License
Copyright (c) 2025 Ajmal Hussain, Mujib Ansari, Mohd Danish, Hazi Azamathulla (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
