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Prediction of Scour at a Side-Weir with GEP, ANN and Regression Models

  • Research Article - Civil Engineering
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Abstract

Side-weir is known as a lateral intake structure, which is widely used in irrigation, land drainage, and urban sewerage system by flow diversion device. Local scour in-/volves the removal of material around piers, abutments, side-weir, spurs, and embankments. Clear-water scour depth based on four dimensional parameters: approach flow velocity (V 1/ V c ), water head ratio (h 1 − p)/h 1, side-weir length (L/b) and sediment size (d 50/p). The equilibrium depth of scour increases by the increase of the dimensionless parameters of approach flow velocity, water head ratio, side-weir length and sediment size. This study presents artificial neural network (ANN) and gene expression programming (GEP) models, which is an algorithm based on genetic algorithms and genetic programming, for prediction of the clear-water scour depth at side-weir. The explicit formulations of the GEP models are developed. The GEP-based formulation and ANN approach are compared with experimental results, multiple linear/nonlinear regressions (MLR/MNLR). The performance of GEP is found in slightly more influential than ANN approach and MNLR for predicting the clear-water scour depth at side-weir.

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References

  1. Yu-Tech L.: Discussion of spatially varied flow over side-weir. ASCE J. Hydraul. Eng. 98(11), 2046–2048 (1972)

    Google Scholar 

  2. Ramamurthy A.S.: Lateral weirs in trapezoidal channels. J.Irrig. Drain. Eng. ASCE 112(2), 130–137 (1986)

    Article  Google Scholar 

  3. Cheong H.F.: Discharge coefficient of lateral diversion from trapezoidal channel. ASCE J. Irrig. Drain. Eng. 117(4), 461–475 (1991)

    Article  Google Scholar 

  4. Singh R., Manivannan D., Satyanarayana T.: Discharge coefficient of rectangular side weirs. ASCE J. Irrig. Drain. Eng. 120(4), 814–819 (1994)

    Article  Google Scholar 

  5. Agaccioglu H., Yuksel Y.: Side-weir flow in curved channels. J. Irrig. Drain. Eng. ASCE 124(3), 163–175 (1998)

    Article  Google Scholar 

  6. Muslu Y.: Numerical analysis for lateral weir flow. J. Irrig. Drain. Eng. ASCE 127(4), 246–253 (2001)

    Article  Google Scholar 

  7. Fares Y.R.: Changes of bed topography in meandering rivers at a neck cutoff intersection. J. Environ. Hydrol. 8(13), 1–18 (2000)

    MathSciNet  Google Scholar 

  8. Onen, F.: Hareketli tabanli akarsularda yanal akimin hidrodinamiğinin incelenmesi. (An investigation of hydrodynamic of lateral flows in movable bed rivers). PhD thesis presented to Yildiz Tecnical University, Istanbul. Turkey (in Turkish) (2005)

  9. Onen F., Agaccioglu H.: Scour at a side weir intersection located on an alluvial river. Nord. Hydrol. 38(2), 165–176 (2007)

    Article  Google Scholar 

  10. Chow, V.T.: Open Channel Hydraulics, pp. 439–460. Mcgraw Hill, Chap. 16, (1959)

  11. Raudkivi A.J.: Functional trends of scour at bridge piers. J. Hydraul. Eng. ASCE 112(1), 1–13 (1986)

    Article  Google Scholar 

  12. Melville B.W., Chiew Y.M.: Time scale for local scour at bridge piers. J. Hydraul. Eng. ASCE 125(1), 59–65 (1999)

    Article  Google Scholar 

  13. Harris E.L., Babovic V., Falconer R.A.: Velocity predictions in compound channels with vegetated floodplains using genetic programming. Int. J. River Mang. 1(2), 117–123 (2003)

    Article  Google Scholar 

  14. Dorado J., Rabunal J.R., Pazos A., Rivero D., Santos A., Puertas J.: Prediction and modeling of the rainfall–runoff transformation of a typical urban basin using ANN and GP. Appl. Artif. Intell. 17, 329–343 (2003)

    Article  Google Scholar 

  15. Khorchani M., Blanpain O.: Development of a discharge equation for side weirs using artificial neural networks. J. Hydroinform. 7(1), 31–39 (2005)

    Google Scholar 

  16. Srinivasulu S., Jain A.: A comparative analysis of training methods for artificial neural network rainfall–runoff models. Appl. Soft Comput. 6, 295–306 (2006)

    Article  Google Scholar 

  17. Aytek A., Kisi O.: A genetic programming approach to suspended sediment modeling. J. Hydrol. 351, 288–298 (2008)

    Article  Google Scholar 

  18. Guven A., Gunal M.: Genetic programming approach for prediction of local scour downstream hyraulic structures. J. Irrig. Drain. Eng. 134(2), 241–249 (2008)

    Article  Google Scholar 

  19. Guven A., Aytek A.: New approach for stage-discharge relationship: gene-expression programming. J. Hydrol. Eng. 14(8), 812–820 (2009)

    Article  Google Scholar 

  20. Azamathulla H.M.D., Ghani A.A.B., Zakaria N.A., Lai S.H., Chang C.K., Leow C.S., Abuhasan Z.: Genetic programming to predict ski-jump bucket spill-way scour. J. Hydrodyn. 20(4), 477–484 (2008)

    Article  Google Scholar 

  21. Azamathulla H.M.D., Ghani A.A.B., Zakaria N.A., Guven A.: Genetic programming to predict bridge pier scour. J. Hydraul. Eng. 136(3), 165–169 (2010)

    Article  Google Scholar 

  22. Eldrandaly K.: Integrating gene expression programming and geographic information systems for solving a multi site land use allocation problem. Am. J. Appl. Sci. 6(5), 1021–1027 (2009)

    Article  Google Scholar 

  23. Bilhan O., Emiroglu M.E., Emiroglu M.E.: Use of artificial neural networks for prediction of discharge coefficient of triangular labyrinth side-weir in curved channels. Adv. Eng. Softw. 42(4), 208–214 (2011)

    Article  MATH  Google Scholar 

  24. Baylar A., Unsal M., Ozkan F.: GEP Modeling of oxygen transfer efficiency prediction in aeration cascades. KSCE J. Civil Eng. 15(5), 799–804 (2011)

    Article  Google Scholar 

  25. Unsal M.: GEP Modeling of penetration depth in sharp crested weirs. Arab. J. sci.Eng. 37(8), 2163–2174 (2012)

    Article  MathSciNet  Google Scholar 

  26. Toth E., Brandimarte L.: Prediction of local scour depth at bridge under piers under clear-water and live-bed condition: comparison of literature formulae and artificial neural networks. J. Hydroinform. 13(4), 812–824 (2011)

    Article  Google Scholar 

  27. Azamathulla H.M.D.: Gene-expression programming to predict scour at a bridge abutment. J. Hydroinform. 14(2), 324–331 (2012)

    Article  Google Scholar 

  28. Karami H., Ardeshir A., Saneie M., Salamation A.: Prediction of time variation of scour depth around spur dikes using neural networks. J. Hydrodyn. 14(1), 180–191 (2012)

    Google Scholar 

  29. Esmaeili, T.: Hydraulic and geometric numerical simulation of scouring around concrete bridge piers (case study), M.S. thesis, Dept. Hydr. Eng, Islamic Azad Univ-South Tehran Branch., Iran (2009)

  30. Richardson J.E., Panchang V.G.: Three-dimensional simulation of scour-inducing flow at bridge piers. J. Hydraul. Eng. ASCE 124(5), 530–540 (1998)

    Article  Google Scholar 

  31. Olsen, N.R.B.; Jimenes, O.F.; Abrahamsen, L.; Lovoll, A.: 3D CFD modeling of water and sediment flow in a hydropower reservoir. J. Sedimet. Res. 14(1), 1–8 (1999)

  32. Tseng M.H., Yen C.L., Song C.S.: Computation of three dimensional flow around square and circular piers. Int. J. Numer. Methods Fluids 122, 120–128 (2000)

    Google Scholar 

  33. Esmaeili T., Dehghani A.A., Zahiri A.R, Suzuki K.: 3D Numerical simulation of scouring around bridge piers, World Academy of Science. Eng. Technol. 34, 1028–1032 (2009)

    Google Scholar 

  34. Taskiran T.: Prediction of California bearing ratio (CBR) of fine grained soils by AI methods. Adv. Eng. Softw. 41(9), 1115–1123 (2010)

    Article  Google Scholar 

  35. Ferreira C.: Gene expression programming and the evolution of computer programs. In: de Castro, L.N., Zuben, F.J. (eds) Recent Developments in Biologically Inspired Computing, pp. 82–103. Idea Group Publishing, Hershey (2004)

    Chapter  Google Scholar 

  36. Ferreira C.: Gene expression programming: a new adaptive algorithm for solving problems. Complex Syst. 13, 87–129 (2001)

    MATH  Google Scholar 

  37. Ferreira C.: Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence. Angra do Heroismo, Portugal (2002)

    Google Scholar 

  38. Jacomino V.M.F., Fields D.E.: A critical approach to the calibration of a watershed model. J. Am. Water Resour. Assoc. 33(1), 143–154 (1997)

    Article  Google Scholar 

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  1. Civil Engineering Department, Engineering Faculty, Dicle University, 21280, Diyarbakir, Turkey

    Fevzi Onen

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Onen, F. Prediction of Scour at a Side-Weir with GEP, ANN and Regression Models. Arab J Sci Eng 39, 6031–6041 (2014). https://doi.org/10.1007/s13369-014-1244-y

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  • DOI: https://doi.org/10.1007/s13369-014-1244-y

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