Estimation of Clear-Water Local Scour at Pile Groups Using Genetic Expression Programming and Multivariate Adaptive Regression Splines
This article has a reply.
VIEW THE REPLYPublication: Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 145, Issue 1
Abstract
The physical process of scour around pile groups is complex. Due to economical and geotechnical considerations, multiple pile bridge piers have become more common in bridge designs. Various empirical models have been developed to estimate scour depth at pile groups. However, these models are mostly based on the conventional statistical regression approaches and are not able to adequately capture the highly nonlinear and complex relationship between scour depth and its influential factors. In this study, genetic expression programming (GEP) and multivariate adaptive regression splines (MARS) were utilized to estimate clear-water local scour depth at pile groups using the flow, sediment, and pile characteristics. Two combinations of data were used to train the GEP and MARS models. The first combination included dimensional variables (e.g., mean flow velocity and depth, mean grain diameter, pile diameter). The second combination contained nondimensional parameters. Results indicated that GEP and MARS can accurately estimate scour depth. Both models yielded better results when the dimensional data were used. In addition, the MARS model with a root mean square error (RMSE) of 0.0220 m and correlation coefficient (R2) of 0.902 outperformed the GEP model with an RMSE of 0.0285 m and R2 of 0.834. Performance of the GEP and MARS models was compared with that of the existing equations. The comparison showed that both models perform better than the regression-based empirical equations. Finally, a sensitivity analysis showed that pile diameter has the most significant impact on equilibrium scour depth.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This is contributed paper WRRC-CP-2019-05 of the Water Resources Research Center, University of Hawaii at Manoa, Honolulu, Hawaii.
References
Amini, A., B. W. Melville, T. M. Ali, and A. H. Ghazali. 2012. “Clear-water local scour around pile groups in shallow-water flow.” J. Hydraul. Eng. 138 (2): 177–185. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000488.
Ataie-Ashtiani, B., and A. A. Beheshti. 2006. “Experimental investigation of clear-water local scour at pile groups.” J. Hydraul. Eng. 132 (10): 1100–1104. https://doi.org/10.1061/(ASCE)0733-9429(2006)132:10(1100).
Ataie-Ashtiani, B., Z. Baratian-Ghorghi and A. Beheshti. 2010. “Experimental investigation of clear-water local scour of compound piers.” J. Hydraul. Eng. 136 (6): 343–351.
Azamathulla, H. M., and R. D. Jarrett. 2013. “Use of gene-expression programming to estimate Manning’s roughness coefficient for high gradient streams.” Water Resour. Manage. 27 (3): 715–729. https://doi.org/10.1007/s11269-012-0211-1.
Balshi, M. S., A. D. McGuire, P. Duffy, M. Flannigan, J. Walsh, and J. Melillo. 2009. “Assessing the response of area burned to changing climate in western boreal North America using a multivariate adaptive regression splines (MARS) approach.” Global Change Biol. 15 (3): 578–600. https://doi.org/10.1111/j.1365-2486.2008.01679.x.
Bateni, S. M., S. M. Borghei, and D. S. Jeng. 2007a. “Neural network and neuro-fuzzy assessments for scour depth around bridge piers.” Eng. Appl. Artif. Intell. 20 (3): 401–414. https://doi.org/10.1016/j.engappai.2006.06.012.
Bateni, S. M., D. S. Jeng, and B. W. Melville. 2007b. “Bayesian neural networks for prediction of equilibrium and time-dependent scour depth around bridge piers.” Adv. Eng. Software 38 (2): 102–111. https://doi.org/10.1016/j.advengsoft.2006.08.004.
Beheshti, A. A., B. Ataie-Ashtiani, and M. J. Khanjani. 2013. “Discussion of ‘clear-water local scour around pile groups in shallow-water flow’ by Ata Amini, Bruce W. Melville, Thamer M. Ali, and Abdul H. Ghazali.” J. Hydraul Eng. 139 (6): 679–680. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000688.
Brandimarte, L., P. Paron, and G. Di Baldassarre. 2012. “Bridge pier scour: A review of processes, measurements and estimates.” Environ. Eng. Manage. J. 11 (5): 975–989. https://doi.org/10.30638/eemj.2012.121.
Coleman, S. E. 2005. “Clearwater local scour at complex piers.” J. Hydraul. Eng. 131 (4): 330–334. https://doi.org/10.1061/(ASCE)0733-9429(2005)131:4(330).
Conoscenti, C., M. Ciaccio, N. A. Caraballo-Arias, A. Gómez Gutiérrez, E. Rotigliano, and V. Agnesi. 2015. “Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice River basin (western Sicily, Italy).” Geomorphology 242 (Aug): 49–64. https://doi.org/10.1016/j.geomorph.2014.09.020.
Deng, L., and C. S. Cai. 2010. “Bridge scour: Prediction, modeling, monitoring, and countermeasures—Review.” Pract. Period. Struct. Des. Constr. 15 (2): 125–134. https://doi.org/10.1061/(ASCE)SC.1943-5576.0000041.
Ebtehaj, I., A. M. A. Sattar, H. Bonakdari, and A. H. Zaji. 2016. “Prediction of scour depth around bridge piers using self-adaptive extreme learning machine.” J. Hydroinf. 19 (2): 207–224. https://doi.org/10.2166/hydro.2016.025.
Emamgholizadeh, S., S. M. Bateni, D. Shahsavani, T. Ashrafi, and H. Ghorbani. 2015. “Estimation of soil cation exchange capacity using genetic expression programming (GEP) and multivariate adaptive regression splines (MARS).” J. Hydrol. 529 (3): 1590–1600. https://doi.org/10.1016/j.jhydrol.2015.08.025.
Ferraro, D., A. Tafarojnoruz, R. Gaudio, and A. H. Cardoso. 2013. “Effects of pile cap thickness on the maximum scour depth at a complex pier.” J. Hydraul. Eng. 139 (5): 482–491. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000704.
Ferreira, C. 2001. “Gene expression programming: a new adaptive algorithm for solving problems.” Complex Syst. 13 (2): 87–129.
FHWA (Federal Highway Administration). 1988. Evaluating scour at bridges. 4th ed. Hydraulic Engineering Circular No. 18, FHWA NHI-01-001. Washington, DC: FHWA.
Friedman, J. H. 1991. “Multivariate adaptive regression splines.” Ann. Stat. 19 (1): 1–67. https://doi.org/10.1214/aos/1176347963.
Friedman, J. H., and C. B. Roosen. 1995. “An introduction to multivariate adaptive regression splines.” Stat. Methods Med. Res. 4 (3): 197–217. https://doi.org/10.1177/096228029500400303.
Ghaemi, N., A. Etemad-Shahidi, and B. Ataie-Ashtiani. 2012. “Estimation of current-induced pile groups scour using a rule based method.” J. Hydroinf. 15 (2): 516–528. https://doi.org/10.2166/hydro.2012.175.
Ghani, A. A., and H. M. Azamathulla. 2014. “Development of GEP-based functional relationship for sediment transport in tropical rivers.” Neural Comput. Appl. 24 (2): 271–276. https://doi.org/10.1007/s00521-012-1222-9.
Grimaldi, C., and A. H. Cardoso. 2010. “Methods for local scour depth estimation at complex bridge piers.” In Proc., 1st IAHR European Div. Congress, edited by S. Arthur. Edinburgh, UK: Heriot-Watt Univ.
Haghiabi, A. H. 2017. “Prediction of river pipeline scour depth using multivariate adaptive regression splines.” J. Pipeline Syst. Eng. Pract. 8 (1): 04016015. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000248.
Hajzaman, M. 2008. “Experimental study of local scour around various complex piers.” [In Persian.] M.Sc. thesis, Dept. of Civil Engineering, Sharif University of Technology, Tehran, Iran.
Hannah, C. R. 1978. Scour at pile groups. Research Rep. No. 28-3. Christchurch, New Zealand: Dept. of Civil Engineering, Univ. of Canterbury.
Hashmi, M. Z., A. Y. Shamseldin, and B. W. Melville. 2011. “Statistical downscaling of watershed precipitation using Gene Expression Programming (GEP).” Environ. Modell. Software 26 (12): 1639–1646. https://doi.org/10.1016/j.envsoft.2011.07.007.
Hastie, T., R. Tibshirani, and J. H. Friedman. 2009. The elements of statistical learning: Data mining, inference and prediction. 2nd ed. New York: Springer.
Heidarpour, M., H. Afzalimehr, and E. Izadinia. 2010. “Reduction of local scour around bridge pier groups using collars.” Int. J. Sediment Res. 25 (4): 411–422. https://doi.org/10.1016/S1001-6279(11)60008-5.
Hosseini, R., and A. Amini. 2015. “Scour depth estimation methods around pile groups.” KSCE J. Civil Eng. 19 (7): 2144–2156. https://doi.org/10.1007/s12205-015-0594-7.
Kambekar, A. R., and M. C. Deo. 2003. “Estimation of pile group scour using neural networks.” Appl. Ocean Res. 25 (41): 225–234. https://doi.org/10.1016/j.apor.2003.06.001.
Khaple, S. K., P. R. Hanmaiahgari, and S. Dey. 2014. “Studies on the effect of an upstream pier as a scour protection measure of a downstream bridge pier.” In Proc., IAHR River Flow, edited by A. J. Schleiss, G. de Cesare, M. J. Franca, and M. Pfister, 2047–2052. London: Taylor & Francis.
Lança, R., C. Fael, R. Maia, J. P. Pêgo, and A. H. Cardoso. 2013. “Clear-water scour at pile groups.” J. Hydraul. Eng. 139 (10): 1089–1098. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000770.
Martin-Vide, J. P., C. Hidalgo, and A. Bateman. 1998. “Local scour at piled bridge foundations.” J. Hydraul. Eng. 124 (4): 439–444. https://doi.org/10.1061/(ASCE)0733-9429(1998)124:4(439).
Melville, B. W., and S. E. Coleman. 2000. Bridge scour. Highlands Ranch, CO: Water Resource Publications.
Melville, B. W., and A. J. Sutherland. 1988. “Design method for local scour at bridge piers.” J. Hydraul. Eng. 114 (10): 1210–1226. https://doi.org/10.1061/(ASCE)0733-9429(1988)114:10(1210).
Moreno, A., R. Maia, and L. Couto. 2016. “Effects of relative column width and pile-cap elevation on local scour depth around complex piers.” J. Hydraul. Eng. 142 (2): 04015051. https://doi.org/10.1061/(ASCE)HY.1943-7900.0001080.
Moreno, M., R. Maia, L. Couto, and A. Cardoso, 2014. “Contribution of complex pier components on local scour depth.” In Proc., 3rd IAHR Europe Congress. Porto, Portugal: Int. Assoc. for Hydro-Environment Engineering and Research (IAHR).
Najafzadeh, M., M. R. Balf, and E. Rashedi. 2016. “Prediction of maximum scour depth around piers with debris accumulation using EPR, MT, and GEP models.” J. Hydroinf. 18 (5): 867–884. https://doi.org/10.2166/hydro.2016.212.
Nouri Imamzadehei, A., M. Heidarpour, M. Nouri Imamzadehei, and A. Fazlollahi. 2013. “Control of local scour around bridge pier groups using geotextile armored soil.” J. River Eng. 1 (2): 1–6. https://doi.org/10.1007/s40891-016-0045-7.
Parola, A. C., D. G. Hagerty, D. S. Mueller, B. W. Melville, G. Parker, and J. S. Usher. 1997. “The need for research on scour at bridge crossings.” In Vol A of Proc., 27th IAHR Congress, Int. Association for Hydraulic Research, 124–129. Delft, Netherlands: IAHR.
Richardson, E. V., and S. R. Davis. 2001. Evaluating scour at bridges. 4th ed. Publication No. FHWA-HIF-12-003, Hydraulic Engineering Circular No. 18. Washington, DC: Federal Highway Administration.
Salim, M., and J. S. Jones. 1998. “Scour around exposed pile foundations.” In ASCE compendium, stream stability, scour at highway bridges, edited by P. Richardson, and B. Lagasse, 349–364. Reston, VA: ASCE.
Sattar, A. M. A. 2014. “Gene expression models for the prediction of longitudinal dispersion coefficients in transitional and turbulent pipe flow.” J. Pipeline Syst. Eng. Pract. 5 (1): 04013011. https://doi.org/10.1061/(ASCE)PS.1949-1204.0000153.
Selamoglu, M., A. M. Yanmaz, and M. Koken. 2014. “Temporal variation of scouring topography around dual bridge piers.” In Proc., 7th Int. Conf. on Scour and Erosion, edited by L. Cheng, S. Draper, and H. An, 495–500. Boca Raton, FL: CRC Press.
Sharda, V. N., S. O. Prasher, R. M. Patel, P. R. Ojasvi, and C. Prakash. 2008. “Performance of multivariate adaptive regression splines (MARS) in predicting runoff in mid-Himalayan micro-watershed with limited data.” Hydrol. Sci. J. 53 (6): 1165–1175. https://doi.org/10.1623/hysj.53.6.1165.
Sheppard, D. M. 2003. Scour at complex piers. Project No. BC354 RPWO 35. Tallahassee, FL: Florida Dept. of Transportation.
Sheppard, D. M., and R. Renna. 2005. Bridge scour manual. Tallahassee, FL: Florida Dept. of Transportation.
Shiri, J., P. Marti, and V. P. Singh. 2014. “Evaluation of gene expression programming approaches for estimating daily evaporation through spatial and temporal data scanning.” Hydrol. Processes 28 (3): 1215–1225. https://doi.org/10.1002/hyp.9669.
Shiri, J., A. A. Sadraddini, A. H. Nazemi, O. Kisi, P. Marti, A. Fakheri Fard, and G. Landeras. 2013. “Evaluation of different data management scenarios for estimating daily reference evapotranspiration.” Hydrol. Res. 44 (6): 1058–1070. https://doi.org/10.2166/nh.2013.154.
Shrestha, C. K. 2015. “Bridge pier flow interaction on the process of scouring.” Ph.D. thesis, Faculty of Engineering, Information Technology, Univ. of Technology.
Zhao, G., and D. M. Sheppard. 1999. “The effect of flow skew angle on sediment scour near pile groups.” In Stream stability and scour at highway bridges: Compendium of Stream Stability and Scour Papers Conference, edited by E. V. Richardson, and P. F. Lagass, 377–391. Reston, VA: ASCE.
Zounemat-Kermani, M., A. A. Beheshti, B. Ataie-Ashtiani, and S. R. Sabbagh-Yazdi. 2009. “Estimation of current-induced scour depth around pile groups using neural network and adaptive neuro-fuzzy inference system.” Appl. Soft Comput. 9 (2): 746–755. https://doi.org/10.1016/j.asoc.2008.09.006.
Information & Authors
Information
Published In
Copyright
© 2018 American Society of Civil Engineers.
History
Received: Nov 30, 2017
Accepted: Jun 25, 2018
Published online: Oct 11, 2018
Published in print: Jan 1, 2019
Discussion open until: Mar 11, 2019
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.