Genetic Programming to Predict River Pipeline Scour
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Abstract
The process involved in the local scour below pipelines is so complex that makes it difficult to establish a general empirical model to provide an accurate estimation for scour. This technical note describes the use of genetic programming (GP) to estimate the pipeline scour depth. The data sets of laboratory measurements were collected from published literature and used to train the network or evolve the program. The developed network and evolved programs were validated by using the observations that were not involved in the training. The performance of GP was found to be more effective when compared with the results of regression equations and artificial neural networks modeling in predicting the scour depth around pipelines.
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Acknowledgments
The writers wish to express their sincere gratitude to Universiti Sains Malaysia for funding a short-term grant to conduct this ongoing research (Grant No. UNSPECIFIED304.PREREDAC.6035262). The writers wish to thank Robert D. Jarrett, U.S. Geological Survey (USGS) for his suggestions in the preparation of this note and for his reviews.
References
American Society of Civil Engineers (ASCE) Task Committee. (2000). “The ASCE Task Committee on application of artificial neural networks in hydrology.” J. Hydrol. Eng., 5(2), 115–137.
Azamathulla, H. Md., Deo, M. C., and Deolalikar, P. B. (2008). “Alternative neural networks to estimate the scour below spillways.” Adv. Eng. Softw., 39(8), 689–698.
Azamathulla, H. Md., Ghani, A. A., Zakaria, N. A., and Aytac, G. (2010). “Genetic programming to predict bridge pier scour.” J. Hydraul. Eng., 136(3), 165–169.
Azmathullah, H. Md., Deo, M. C., and Deolalikar, P. B. (2005). “Neural networks for estimation of scour downstream of ski-jump bucket.” J. Hydraul. Eng., 131(10), 898–908.
Babovic, V., and Keijzer, M. (2000). “Genetic programming as a model induction engine.” J. Hydroinform., 2(1), 35–60.
Bijker, E. W., and Leeuwestein, W. (1984). “Interaction between pipelines and the seabed under influence of waves and currents.” Proc., Symp. on Int. Union of Theoretical Applied Mechanics/Int. Union of Geology and Geophys., Graham and Trotman, Gettysburg, Md., 235–242.
Brameier, M., and Banzhaf, W. (2001). “A comparison of linear genetic programming and neural networks in medical data mining.” IEEE Trans. Evol. Comput., 5, 17–26.
Chao, J. L., and Hennessy, P. V. (1972). “Local scour under ocean outfall pipe-lines.” J. Water Pollut. Control Fed., 44(7), 1443–1447.
Chiew, Y. M. (1991). “Prediction of maximum scour depth at submarine pipelines.” J. Hydraul. Eng., 117(4), 452–466.
Davidson, J. W., Savic, D. A., and Walters, G. A. (1999). “Method for identification of explicit polynomial formulae for the friction in turbulent pipe flow.” J. Hydroinform., 1(2), 115–126.
Dey, S., and Singh, N. P. (2008). “Clear-water scour below underwater pipelines under steady flow.” J. Hydraul. Eng., 134(5), 588–600.
Giustolisi, O. (2004). “Using genetic programming to determine Chèzy resistance coefficient in corrugated channels.” J. Hydroinform., 6(3), 157–173.
Holland, J. H. (1975). Adaptation in natural and artificial system, University of Michigan Press, Ann Arbor, Mich.
Ibrahim, A., and Nalluri, C. (1986). “Scour prediction around marine pipelines.” Proc., 5th Int. Symp. on Offshore Mechanics and Arctic Engineering, American Society of Mechanical, 679–684.
Johari, A., Habibagahi, G., and Ghahramani, A. (2006). “Prediction of soil-water characteristic curve using genetic programming.” J. Geotech. Geoenviron. Eng., 132(5), 661–665.
Keijzer, M., and Babovic, V. (2002). “Declarative and preferential bias in GP-based scientific discovery.” Genet. Program. Evolvable Mach., 3(1), 41–79.
Kizhisseri, A. S., Simmonds, D., Rafiq, Y., and Borthwick, M. (2005). “An evolutionary computation approach to sediment transport modeling.” 5th Int. Conf. on Coastal Dynamics, ASCE, Reston, Va.
Kjeldsen, S. P., Gjørsvik, O., Bringaker, K. G., and Jacobsen, J. (1973). “Local scour near offshore pipelines.” Proc., 2nd Int. Conf. on Port and Ocean Engineering under Arctic Conditions, Univ. of Iceland, Reykjavik, 308–331.
Lim, F. H., and Chiew, Y. M. (2001). “Parametric study of riprap failure around bridge piers.” J. Hydraul. Res., 39(1), 61–72.
Melville, B. W. (1992). “Local scour at bridge abutments.” J. Hydraul. Eng., 118(4), 615–631.
Moncada-M., A. T., and Aguirre-Pe, J. (1999). “Scour below pipeline in river crossings.” J. Hydraul. Eng., 125(9), 953–958.
Oltean, M., and Groşan, C. (2003). “A comparison of several linear genetic programming techniques.” Complex Syst., 14(1), 1–29.
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Information
Published In
Journal of Pipeline Systems Engineering and Practice
Volume 1 • Issue 3 • August 2010
Pages: 127 - 132
Copyright
© 2010 ASCE.
History
Received: Oct 31, 2009
Accepted: Apr 16, 2010
Published online: Apr 22, 2010
Published in print: Aug 2010
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