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New Model for Determining Local Scour Depth Around Piers

  • Research Article - Civil Engineering
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Abstract

Since a lot of factors play role in the creation of scouring phenomenon, the exact determination of scouring is considered to be difficult in practice. Consequently, the determination of scouring depth is still conducted mostly based on the empirical relationships though it has been investigated for several decades using numerous methods. Currently, the major estimation of bridge scour calculation has been conducted utilizing the existing software on river engineering based on the available empirical equations. In this study, a new model is proposed using modified honey bee mating optimization algorithm to estimate the scour depth of the piers using various reliable field data. The performance of the proposed model was found more effective comparing with five other conventional and practical present models, which have been widely used in predicting the scour depth of bridge piers.

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References

  1. Lee T., Jeng D., Zhang G., Hong J.: Neural network modeling for estimation of scour depth around bridge piers. J. Hydrodyn. Ser. B 19(3), 378–386 (2007)

    Article  Google Scholar 

  2. Briaud J.L., Ting F.C., Chen H., Gudavalli R., Perugu S., Wei G.: Sricos: prediction of scour rate in cohesive soils at bridge piers. J. Geotech. Geoenviron. 125(4), 237–246 (1999)

    Article  Google Scholar 

  3. Breusers H., Nicollet G., Shen H.: Local scour around cylindrical piers. J. Hydraul. Res. 15(3), 211–252 (1977)

    Article  Google Scholar 

  4. Breusers, H.; Raudkivi, A.: Scouring, hydraulic structures design manual. IAHR, AA Balkema, Rotterdam, vol. 143 (1991)

  5. Ghazanfari Hashemi S., Shahidi A.: Prediction of scour depth around bridge pier by support vector machines. Modares Civ. Engi. J. 12(2), 23–36 (2012)

    Google Scholar 

  6. Ettema R., Melville B.W., Barkdoll B.: Scale effect in pier-scour experiments. J. Hydraul. Eng.-ASCE 124(6), 639–642 (1998)

    Article  Google Scholar 

  7. Shen, H.W.; Schneider, V.; Karaki, S.: Local scour around bridge piers. J. Hydraul. Eng. Div.-ASCE 96(6), 1919–1940 (1969)

  8. Baker C.: Theoretical approach to prediction of local scour around bridge piers. J. Hydraul. Res. 18(1), 1–12 (1980)

    Article  Google Scholar 

  9. Yanmaz A.M., Altinbilek H.D.: Study of time-dependent local scour around bridge piers. J. Hydraul. Eng.-ASCE 117(10), 1247–1268 (1991)

    Article  Google Scholar 

  10. Kothyari U., Ranga Raju K., Garde R.: Live-bed scour around cylindrical bridge piers. J. Hydraul. Res. 30(5), 701–715 (1992)

    Article  Google Scholar 

  11. Olsen N.R., Melaaen M.C.: Three-dimensional calculation of scour around cylinders. J. Hydraul. Eng.-ASCE 119(9), 1048–1054 (1993)

    Article  Google Scholar 

  12. Dou, X.: Numerical Simulation of Three-Dimensional Flow Field and Local Scour at Bridge Crossings. Ph.D. thesis, University of Mississippi (1997)

  13. 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 

  14. Roulund A., Sumer B.M., Fredsøe J., Michelsen J.: Numerical and experimental investigation of flow and scour around a circular pile. J. Fluid Mech. 534, 351–401 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  15. Gamal, T.; Hosny, M.; Tarek, A.S.; Atta, N.A.: Prediction of maximum scour around bridge piers due to aquatic weed racks. Int. J. Eng. Res. Technol. 2 1735–1743 (2013)

  16. Melville B., Sutherland A.: Design method for local scour at bridge piers. J. Hydraul. Eng.-ASCE 114(10), 1210–1226 (1988)

    Article  Google Scholar 

  17. Melville B.W., Coleman S.E.: Bridge Scour. Water Resources Publication, New Zealand (2000)

    Google Scholar 

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

    Article  Google Scholar 

  19. Raudkivi A.J., Ettema R.: Clear-water scour at cylindrical piers. J. Hydraul. Eng.-ASCE 109(3), 338–350 (1983)

    Article  Google Scholar 

  20. Richardson, E.V.; Davis, S.R.: Evaluating Scour at Bridges HEC-18. US Department of Transportation, Federal Highway Administration, Colorado, 4th edn. FHWA NHI 01-001 edn. (2001)

  21. Bateni S.M., Borghei S., Jeng D.S.: Neural network and neuro-fuzzy assessments for scour depth around bridge piers. Eng. Appl. Artif. Intell. 20(3), 401–414 (2007)

    Article  Google Scholar 

  22. Kambekar A., Deo M.: Estimation of pile group scour using neural networks. Appl. Ocean. Res. 25(4), 225–234 (2003)

    Article  Google Scholar 

  23. Haddad O.B., Afshar A., Marino M.A.: Honey-bees mating optimization (HBMO) algorithm: a new heuristic approach for water resources optimization. Water Resour. Manag. 20(5), 661–680 (2006)

    Article  Google Scholar 

  24. Kaya A.: Artificial neural network study of observed pattern of scour depth around bridge piers. Comput. Geotech. 37(3), 413–418 (2010)

    Article  MathSciNet  Google Scholar 

  25. Azamathulla H.M., Ghani A.A., Zakaria N.A., Guven A.: Genetic programming to predict bridge pier scour. J. Hydraul. Eng.-ASCE 136(3), 165–169 (2009)

    Article  Google Scholar 

  26. Khan M., Azamathulla H.M., Tufail M., Ab Ghani A.: Bridge pier scour prediction by gene expression programming. Proc. ICE-Water Manag. 165(9), 481–493 (2012)

    Google Scholar 

  27. Beg, M.: Predictive competence of existing bridge pier scour depth predictors. Eur. Int. J. Sci. Technol. 2, 191–196 (2013)

  28. Cheng, M.Y.; Cao, M.T.; Wu, Y.W.: Predicting equilibrium scour depth at bridge piers using evolutionary radial basis function neural network. J. Comput. Civ. Eng. 29(5), 04014070 (2015)

  29. Brunner, G.W.: HEC-RAS River Analysis System Users Manual Version 4.1. Technical Report, US Army Corps of Engineers Institute for Water Resources Hydrologic Engineering Center (HEC), CA, USA (2010)

  30. 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 

  31. Mohamed T.A., Noor M.J., Ghazali A.H., Huat B.B.: Validation of some bridge pier scour formulae using field and laboratory data. Am. J. Environ. Sci. 1(2), 119 (2005)

    Article  Google Scholar 

  32. Sheikholeslami M., Kashefpoor S.M.: Estimation of scour depth at bridge piers by using faster model. J. Water Irrig. 1(1), 57–68 (2009)

    Google Scholar 

  33. Ahmad, M.: Experiments on design and behavior of spur dikes. In: Proceedings@ sMinnesota International Hydraulic Convention, pp. 145–159. ASCE (1953)

  34. Ansari, S.A.; Qadar, A.: Ultimate depth of scour around bridge piers. In: Hydraulic Engineering (1994), pp. 51–55. ASCE (1994)

  35. Chase, K.J.; Holnbeck, S.R.: Evaluation of Pier-Scour Equations for Coarse-Bed Streams. US Department of the Interior, US Geological Survey (2004)

  36. Chitale S.: Discussion of ”scour at bridge crossings,” by em laursen. Trans. ASCE 217(1), 191–196 (1962)

    Google Scholar 

  37. Froehlich, D.C.: Local scour at bridge abutments. In: Proceedings of the 1989 National Conference on Hydraulic Engineering, pp. 13–18 (1989)

  38. Inglis, C.C.: The Behaviour and Control of Rivers and Canals (With the Aid of Models), vol. 13. Yeravda Prison Press, Poona, India (1949)

  39. Johnson P.A.: Comparison of pier-scour equations using field data. J. Hydraul. Eng.-ASCE 121(8), 626–629 (1995)

    Article  Google Scholar 

  40. Larras, J.: Profondeurs maximales d’érosion des fonds mobiles autour des piles en rivière. In: Annales des Ponts et Chausses, vol. 133, pp. 411–424 (1963)

  41. May, R.; Willoughby, I.: Local Scour Around Large Obstructions. Hydraulics Research Wallingford (1990)

  42. Melville B.W.: Pier and abutment scour: integrated approach. J. Hydraul. Eng.-ASCE 123(2), 125–136 (1997)

    Article  Google Scholar 

  43. Molinas, A.: Bridge scour in nonuniform sediment mixtures and in cohesive materials: synthesis report. Technical Report (2004)

  44. Mueller, D.S.; Wagner, C.R.: Field observations and evaluations of streambed scour at bridges. Technical Report (2005)

  45. Shen H.: Scour near piers. River Mech. 2, 23–1 (1971)

  46. Sheppard D.M., Miller Jr W.: Live-bed local pier scour experiments. J. Hydraul. Eng.-ASCE 132(7), 635–642 (2006)

    Article  Google Scholar 

  47. Wilson, K.V.: Scour at selected bridge sites in Mississippi. Report 94-4241, U.S. Geological Survey, Water-Resources Investigations (1995)

  48. Sheppard D., Melville B., Demir H.: Evaluation of existing equations for local scour at bridge piers. J. Hydraul. Eng.-ASCE 140(1), 14–23 (2013)

    Article  Google Scholar 

  49. Sheppard, D.; Renna, R.: Bridge scour manual. Florida Department of Transportation, vol. 605 (2005)

  50. Froehlich, D.C.: Analysis of onsite measurements of scour at piers. In: Proceedings of the ASCE National Hydraulic Engineering Conference, pp. 534–539 (1988)

  51. Holnbeck, S.R.: Investigation of pier scour in coarse-bed streams in Montana, 2001 through 2007. Report 94-4241, U.S. Geological Survey Scientific Investigations (2011)

  52. Pier Scour Data Table: http://water.usgs.gov/osw/techniques/bs/bsdms/data-tables/pierscourtable.htm (2014)

  53. Arneson, L.A.; Zevenbergen, L.W.; Lagasse, P.F.; Clopper, P.E.: Evaluating scour at bridges HEC-18. US Department of Transportation, Federal Highway Administration, Colorado, 5th edn. fhwa-hif-12-003 edn. (2012)

  54. Richardson, E.V.; Sabol, G.V., Nordin Jr, C.F.: Scour at bridge structures and channel aggradation and degradation field measurements. US Department of Transportation, Federal Highway Administration, FHWA-AZ90-814 (1990)

  55. Niknam T.: An efficient hybrid evolutionary algorithm based on pso and HBMO algorithms for multi-objective distribution feeder reconfiguration. Energy Convers. Manag. 50(8), 2074–2082 (2009)

    Article  Google Scholar 

  56. Afshar A., Bozorg Haddad O., Mariño M.A., Adams B.: Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation. J. Frankl. Inst. 344(5), 452–462 (2007)

    Article  MATH  Google Scholar 

  57. Niazkar M., Afzali S.H.: Assessment of modified honey bee mating optimization for parameter estimation of nonlinear muskingum models. J. Hydrol. Eng. 20(4), 04014055 (2015)

    Article  Google Scholar 

  58. Esmi Jahromi M., Afzali S.: Application of the HBMO approach to predict the total sediment discharge. Iran. J. Sci. Technol. Trans. Civ. Eng. 38(C1), 123 (2014)

    Google Scholar 

  59. Niazkar M., Afzali S.H.: Optimum design of lined channel sections. Water Resour. Manag. 29(6), 1921–1932 (2015)

    Article  Google Scholar 

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  1. Civil Engineering, School of Engineering, Shiraz University, Zand Blvd., Shiraz, Iran

    Seied Hosein Afzali

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Afzali, S.H. New Model for Determining Local Scour Depth Around Piers. Arab J Sci Eng 41, 3807–3815 (2016). https://doi.org/10.1007/s13369-015-1983-4

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  • DOI: https://doi.org/10.1007/s13369-015-1983-4

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