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Design of Riprap Stone Around Bridge Piers Using Empirical and Neural Network Method | ||
Civil Engineering Infrastructures Journal | ||
مقاله 12، دوره 48، شماره 1، شهریور 2015، صفحه 175-188 اصل مقاله (1.02 M) | ||
نوع مقاله: Research Papers | ||
شناسه دیجیتال (DOI): 10.7508/ceij.2015.01.012 | ||
نویسندگان | ||
Mojtaba Karimaee Tabarestani* 1؛ Amir Reza Zarrati2 | ||
1Ph.D. of Water Engineering, Civil and Environmental Department, Amirkabir University of Technology, P.O. Box 15915, Tehran, Iran | ||
2Professor, Civil and Environmental Department, Amirkabir University of Technology, P.O. Box 15915, Tehran, Iran | ||
چکیده | ||
An attempt was made to develop a method for sizing stable riprap around bridge piers based on a huge amount of experimental data, which is available in the literature. All available experimental data for circular as well as round-nose-and-tail rectangular piers were collected. The data for rectangular piers, with different aspect ratios, aligned with the flow or skewed at different angles to the flow, were used in this analysis. In addition, new experiments were also conducted for larger pier width to riprap size ratio, which was not available in the literature. Based on at least 190 experimental data, the effect of important parameters on riprap stability were studied which showed that the effective pier width is the most effective parameter on riprap stability. In addition, an empirical equation was developed by multiple regression analysis to estimate the stable riprap stone size around bridge piers. The ratio of predicted to experiment riprap size value for all experimental data is larger than one with an average value of 1.75, which is less than many other empirical equations. Finally, in order to achieve a higher accuracy for riprap design, the artificial neural network (ANN) method based on utilizing non-dimensional parameters was deployed. The results showed that the ANN model provides around a 7% improved prediction for riprap size compared to the conventional regression formula. | ||
کلیدواژهها | ||
Artificial Neural Network Method؛ Local Scour؛ Rectangular and Circular Bridge Pier؛ Riprap Design؛ Riprap Stone Stability؛ Shear Failure | ||
مراجع | ||
Azmathullah, H.M., Deo, M.C. and Deolalikar, P.B. (2005). “Neural Networks for estimation of scour downstream of a ski-jump bucket”, Journal of Hydraulic Engineering, 131(10), 898-908. Breusers, H.N.C., Nicollet, G. and Shen, H.W. (1977). “Local scour around cylindrical piers”, Journal of Hydraulic Research, 15(3), 211–252. Bateni, S.M., Jeng, D.S. and Melville, B.W. (2007). “Bayesian neural networks for prediction of equilibrium and time-dependent scour depth around bridge piers”, Advance in Engineering Software, 38(2), 102-111. Chiew, Y.M. and Melville, B. (1987). “Local scour around bridge piers”, Journal of Hydraulic Research, 25(1), 15-26. Chiew, Y.M. (1995). “Mechanics of riprap failure at bridge piers”, Journal of Hydraulic Engineering, 121(2), 635-643. Croad, R.N. (1997). Protection from scour of bridge piers using riprap, Transit New Zealand Research Report No. PR3-0071, Works Consultancy Services Ltd., Central Laboratories Lower Hutt, New Zealand. Froehlich, D.C. (2013). “Protecting bridge piers with loose rock riprap”, Journal of Applied Water Engineering and Research, 1(1), 39-57. Gaudio, R., Tafarojnoruz, A. and Calomino, F. (2012). “Combined flow-altering countermeasures against bridge pier scour”, Journal of Hydraulic Research, 50(1), 35-43. Hager, W. H. and Oliveto, G. (2002). “Shields entrainment criterion in bridge hydraulics”, Journal of Hydraulic Engineering, 128(5), 538–542. Hornik, K., Stinchcombe, M. and White, H. (1989). “Multilayer feed forward networks are universal approximates”, Neural Networks, 2(5), 359–366. Hosseini, S.H., Hosseinzadeh Dalir, A., Farsadizadeh, D., Arvanaghi, H. and Ghorbani, M.A. (2011). “Application of submerged vanes to control scouring around rectangular bridge piers”, Civil Engineering Infrastructures Journal, 45(3), 301-310. Hsu, K.L. (2011). “Hydrologic forecasting using artificial neural networks: a Bayesian sequential Monte Carlo approach”, Journal of Hydroinformatics, 13(1), 25-35. Kambekar, A.R. and Deo, M.C. (2003). “Estimation of group pile scour using neural networks”, Journal of Applied Ocean Research, 25(4), 225-334. Karimaee Tabarestani M. and Zarrati A.R. (2013). “Design of stable riprap around aligned and skewed rectangular bridge piers”, Journal of Hydraulic Engineering, 139(8), 911-916. Karimaee Tabarestani M. and Zarrati A.R. (2011). “Effect of collar on time development and extent of scour hole around cylindrical bridge piers”, International Journal of Engineering, Transactions C, 25(1), 11-16. Kirkgoz S. and Ardichoglu M. (1997). “Velocity profiles of developing and developed open channel flow”, Journal of Hydraulic Engineering, 123(12), 1099-1105. Lagasse, P.F., Clopper, P.E., Zevenbergen, L.W. and Girard, L.G. (2007). “Countermeasures to protect bridge piers from scour”, NCHRP Report 593, TRB, NAS, Washington D.C., 272p. www.trb.org. Lauchlan, C.S. and Melville, B.W. (2001). “Riprap protection at bridge piers”, Journal of Hydraulic Engineering, 127(5), 412-418. Lee, S.O. and Sturm, T.W. (2009). “Effect of sediment size scaling on physical modeling of bridge pier scour”, Journal of Hydraulic Engineering, 135(10), 793-802. Mashahir, M.B., Zarrati, A.R. and Mokallaf, E. (2009). “Application of riprap and collar to prevent scouring around piers rectangular bridge”, Journal of Hydraulic Engineering, 136(3), 183-187. Muzzammil, M. and Siddiqui, R. (2003). “An artificial neural network model for scour prediction: Advances in Civil Engineering”, Prospective of Developing Countries. Vol. II., Parmar and Kumar (ed.), 430–441, Alied Publishers Pvt. Limited. Parola, A.C. (1993). “Scour protection at bridge piers”, Journal of Hydraulic Engineering 118(2), 1260-1269. Quazi, M.E., and Peterson, A.W. (1973). “A method for bridge pier riprap design”, Proceedings of 1st Canadian Hydraulic Conference, Edmonton, AB, pp. 96–106. Raudkivi, A.J. (1998). Loose boundary hydraulics, Balkema, Rotterdam, The Netherlands. Richardson, E.V. and Davis, S.R. (1995). “Evaluating scour at bridges”, Hydraulic Engineering Circular (HEC), No. 18, FHWA-IP-90-017, Fairbank Turner Hwy. Res. Ctr., McLean, Va. Sheppard, D.M., Odeh, M. and Glasser, T. (2004). “Large scale clear-water local pier scour experiments”, Journal of Hydraulic Engineering, 130(10), 957-963. Shirole, A.M. and Holt, R.C. (1991). Planning for a comprehensive bridge safety assurance program, Transportation Research Record 1290, Transportation Research Board, Washington, D.C., 137–142. Shin, J.H. and Park, H.I. (2010). “Neural network formula for local scour at piers using field data”, Marine Georesources and Geotechnology, 28(1), 37-48. Soltani-Gerdefaramarzi, S., Afzalimehr, H., Chiew, Y.M. and Lai, J.S. (2013). “Jets to control scour around bridge piers”, Canadian Journal of Civil Engineering, 40(3), 204-212. Tafarojnoruz, A., Gaudio, R. and Calomino, F. (2012). “Bridge pier scour mitigation under steady and unsteady flow conditions”, Acta Geophysica, 60(4), 1076-1097. Zarrati, A.R., Gholami, H. and Mashahir, M.B. (2004). “Application of collar to control scouring around rectangular bridge Piers”, Journal of Hydraulic Research, 42(1), 97-103. Zarrati, A.R., Chamani, M.R., Shafaei, A. and Latifi, M. (2010). “Scour countermeasures for cylindrical bridge piers using riprap and combination of collar and riprap”, International Journal of Sediment Research, 25(3), 313–321. | ||
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