Applicability of Several Soft Computing Approaches in Modeling Oxygen Transfer Efficiency at Baffled Chutes
Publication: Journal of Irrigation and Drainage Engineering
Volume 143, Issue 5
Abstract
The present study investigates the accuracy of five different data-driven techniques in estimating oxygen transfer efficiency in baffled chutes: feedforward neural network (FFNN), radial basis neural network (RBNN), generalized regression neural network (GRNN), adaptive neuro fuzzy inference system with subtractive clustering (ANFIS-SC), and adaptive neuro fuzzy inference system with fuzzy c-means clustering (ANFIS-FCM). Baffled apron chutes or drops are used on channel structures to dissipate the energy in the flow. A baffled chute design is effective both in energy dissipation and in aerating the flow and reducing nitrogen supersaturation. There is a close relationship between energy dissipation and oxygen transfer efficiency. This study aims to determine the aeration efficiency of baffled chutes with stepped (), wedge (), trapezoidal (), and -shaped () baffle blocks. The performances of the FFNN, RBNN, GRNN, ANFIS-SC, and ANFIS-FCM models are compared with those of multilinear and nonlinear regression models. Based on the comparisons, it was observed that all data-driven models could be successfully employed in modeling the aeration efficiency of , , and baffle blocks from the available experimental data. Among data-driven models, the FFNN model was found to be the best.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors also wish to thank Dr. Nihat Kaya for their assistance in running the experiments.
References
Abbood, D. W., and Abood, H. H. (2014). “The effect of hydraulic structure on aeration performance case study: Stepped cascade with end sill.” Civ. Environ. Res., 6(8), 11–18.
Abyaneh, H. Z., Nia, A. M., Varkeshi, M. B., Marofi, S., and Kisi, O. (2011). “Performance evaluation of ANN and ANFIS models for estimating garlic crop evapotranspiration.” J. Irrig. Drain. Eng., 280–286.
Alp, E., and Melching, C. S. (2011). “Allocation of supplementary aeration stations in the Chicago waterway system for dissolved oxygen improvement.” J. Environ. Manage., 92(6), 1577–1583.
Avery, S. T., and Novak, P. (1978). “Oxygen transfer at hydraulic structures.” J. Hydraul. Div., 104(11), 1521–1540.
Ayvaz, M. T., Karahan, H., and Aral, M. M. (2007). “Aquifer parameter and zone structure estimation using kernel-based fuzzy c-means clustering and genetic algorithm.” J. Hydrol., 343(3–4), 240–253.
Baylar, A., and Emiroglu, M. E. (2003). “Study of aeration efficiency at stepped channels.” Proc. Institution Civ. Eng. Water and Mar. Eng., 156(3), 257–263).
Baylar, A., Emiroglu, M. E., and Bagatur, T. (2006). “An experimental investigation of aeration performance in stepped spillways.” Water Environ. J., 20(1), 35–42.
Bilhan, O., Emiroglu, M. E., and Kisi, O. (2010). “Application of two different neural network techniques to lateral outflow over rectangular side weirs located on a straight channel.” Adv. Eng. Software, 41(6), 831–837.
Broomhead, D., and Lowe, D. (1988). “Multivariable functional interpolation and adaptive networks.” Complex Syst., 2(3), 321–355.
Chamani, M. R., and Rajaratnam, N. (1999). “Characteristics of skimming flow over stepped spillways.” J. Hydr. Eng., 361–368.
Chanson, H. (1993). “Stepped spillway flows and air entrainment.” Can. J. Civ. Eng., 20(3), 422–435.
Chanson, H., and Toombes, L. (2002a). “Energy dissipation and air entrainment in stepped storm waterway: Experimental study.” J. Irrig. Drain. Eng., 305–315.
Chanson, H., and Toombes, L. (2002b). “Experimental investigations of air entrainment in transition and skimming flows down a stepped chute.” Can. J. Civ. Eng., 29(1), 145–156.
Chen, S., Cowan, C. F. N., and Grant, P. M. (1991). “Orthogonal least squares learning algorithm for radial basis function networks.” IEEE Trans. Neural Networks, 2(2), 302–309.
Chu, K., Hua, Z., and Ji, L. (2014). “Aeration at overflow dams with curved surfaces by different flashboard spillways.” J. Environ. Eng. Landscape Manage., 22(3), 226–236.
Cobaner, M., Seckin, G., and Kisi, O. (2008). “Initial assessment of bridge backwater using artificial neural network approach.” Can. J. Civ. Eng., 35(5), 500–510.
Dawson, W. C., and Wilby, R. (1998). “An artificial neural network approach to rainfall-runoff modeling.” Hydrol. Sci. J., 43(1), 47–66.
Dursun, O. F., Talu, M. F., Kaya, N., and Alcin, O. F. (2016). “Length prediction of non-aerated region flow at baffled chutes using intelligent nonlinear regression methods.” Environ. Earth Sci., 75(8), 1–10.
Emiroglu, M. E., Bilhan, O., and Kisi, O. (2011). “Neural networks for estimation of discharge capacity of triangular labyrinth side-weir located on a straight channel.” Exp. Syst. Appl., 38(1), 867–874.
Ervine, D. A. (1998). “Air entrainment in hydraulic structures: A review.” Proc. Inst. Civ. Eng. Water Mar. Energy, 130(3), 142–153.
Gameson, A. L. H. (1957). “Weirs and the aeration of rivers.” J. Inst. Water Eng., 11(5), 477–490.
Genc, O., Kisi, O., and Ardiclioglu, M. (2014). “Determination of mean velocity and discharge in natural streams using neuro-fuzzy and neural network approaches.” Water Resour. Manage., 28(9), 2387–2400.
Govindaraju, R. (2000). “Artificial neural networks in hydrology. II: Hydrological applications.” J. Hydrol. Eng., 5(2), 124–137.
Gulliver, J. S., Thene, J. R., and Rindels, A. J. (1990). “Indexing gas transfer in self-aerated flows.” J. Envir. Eng., 503–523.
Gulliver, J. S., Wilhelms, S. C., and Parkhill, K. L. (1998). “Predictive capabilities in oxygen transfer at hydraulics structures.” J. Hydraul. Eng., 664–671.
Hagan, M. T., and Menhaj, M. B. (1994). “Training feed forward networks with the marquaradt algorithm.” IEEE Trans. Neural Networks, 5(6), 861–867.
Haykin, S. (1998). Neural networks: A comprehensive foundation, 2nd Ed., Prentice-Hall, Upper Saddle River, NJ, 26–32.
Houck, C. P., Brooks, J., French, R. D., and Humble, D. (1992). “Non-traditional water quality approaches.” Proc., Natl. Conf. on Environ., ASCE, New York, 433–438.
Jang, J.-S. R. (1993). “ANFIS: Adaptive-network-based fuzzy inference system.” IEEE Trans. Syst. Manage. Cybern., 23(3), 665–685.
Jang, J.-S. R., Sun, C.-T., and Mizutani, E. (1997). Neuro-fuzzy and soft computing: A computational approach to learning and machine intelligence, Prentice-Hall, Upper Saddle River, NJ.
Kaya, N., and Emiroglu, M. E. (2010). “Study of oxygen transfer efficiency at baffled chutes.” Proc. Inst. Civ. Eng., 13(9), 447–456.
Khatibi, R., Salmasi, F., Ghorbani, M. A., and Asadi, H. (2014). “Modelling energy dissipation over stepped-gabion weirs by artificial intelligence.” Water Resour. Manage., 28(7), 1807–1821.
Khdhiri, H., Potier, O., and Leclerc, J.-P. (2014). “Aeration efficiency over stepped cascades: Better predictions from flow regimes.” Water Res., 55, 194–202.
Kisi, O. (2005). “Suspended sediment estimation using neuro-fuzzy and neural network approaches.” Hydrol. Sci. J., 50(4), 683–696.
Kişi, Ö. (2006). “Daily pan evaporation modelling using a neuro-fuzzy computing technique.” J. Hydrol., 329(3), 636–646.
Kocabas, F., Kisi, O., and Ardiclioglu, M. (2009). “An artificial neural network model for prediction of critical submergence for an intake in a stratified fluid media.” Civ. Eng. Environ. Syst., 26(4), 367–375.
Kumar, A., Moulick, S., Singh, B. K., and Mal, B. C. (2013). “Design characteristics of pooled circular stepped cascade aeration system.” Aquacult. Eng., 56, 51–58.
Lee, G. C., and Chang, S. H. (2003). “Radial basis function networks applied to DNBR calculation in digital core protection systems.” Ann. Nuclear Energy, 30(15), 1561–1572.
Lewis, W. K., and Whitman, W. G. (1924). “Principles of gas absorption Ind.” Eng. Chem., 16(12), 1215–1220.
Mamak, M., Seckin, G., Cobaner, M., and Kisi, O. (2009). “Bridge afflux analysis through arched bridge constrictions using artificial intelligence methods.” Civ. Eng. Environ. Syst., 26(3), 279–293.
Markovsky, M., and Kobus, H. (1978). “Unified presentation of weir aeration data.” J. Hydraul. Div., 104(HY4), 562–568.
MATLAB [Computer software]. MathWorks, Natick, MA.
Nakasone, H. (1987). “Study of aeration of weirs and cascades.” J. Environ. Eng., 64–81.
Peterka, A. J. (1984). “Hydraulic design of stilling basins and energy dissipators.” U.S. Dept. of the Interior Bureau of Reclamation, Denver.
Rhone, T. J. (1977). “Baffled apron as spillway energy dissipator, 103(HY12).” J. Hydraul. Div., 103(17), 1391–1401.
Sahu, M., Khatua, K. K., and Mahapatra, S. S. (2011). “A neural network approach for prediction of discharge in straight compound open channel flow.” Flow Meas. Instrum., 22(5), 438–446.
Sayed, T., Tavakolie, A., and Razavi, A. (2003). “Comparison of adaptive network based fuzzy inference systems and B-spline neuro-fuzzy mode choice models.” J. Comput. Civil Eng., 123–130.
SNJDEP (State of New Jersey Department of Environmental Protection). (2016). “Division of water monitoring and standards.” ⟨http://www.state.nj.us/dep/wms/bears/swqs.htm⟩ (Aug. 15, 2016).
Sorensen, R. M. (1985). “Stepped spillway hydraulic model investigation.” J. Hydr. Eng., 1461–1472.
Specht, D. F. (1991). “A general regression neural network.” IEEE Trans. Neural Networks, 2(6), 568–576.
Toombes, L., and Chanson, H. (2000). “Air-water flow and gas transfer at aeration cascades: A comparative study of smooth and stepped chutes.” Proc., Int. Workshop on Hydraulics of Stepped Spillways, A.A. Balkema, Amsterdam, Netherlands, 77–84.
Toombes, L., and Chanson, H. (2005). “Air-water mass transfer on a stepped waterway.” J. Environ. Eng.,. 1377–1386.
Tsoukalas, L. H., and Uhrig, R. E. (1997). Fuzzy and neural approaches in engineering, Wiley, New York.
Urban, A. L., Gulliver, J. S., and Johnson, D. W. (2008). “Modeling total dissolved gas concentration downstream of spillways.” J. Hydraul. Eng., 550–561.
Wilhelms, S. C., and Gulliver, J. S. (2007). “Bubbles and waves description of self-aerated spillway flow.” J. Hydraul. Res., 45(1), 142–144.
Wilhelms, S. C., Gulliver, J. S., and Parkhill, K. (1992). “Re-aeration at low-head hydraulic structures.” U.S. Army Engineer Waterways Experiment Station, Vicksburg, MI.
Wüthrıch, D., and Chanson, H. (2014). “Hydraulics, air entrainment, and energy dissipation on a Gabion stepped weir.” J. Hydraul. Eng., .
Yang, H.-C., and Chang, F.-J. (2005). “Modelling combined open channel flow by artificial neural networks.” Hydrol. Process., 19(18), 3747–3762.
Yazdi, J., and Zarrati, A. R. (2011). “An algorithm for calculating air demand in gated tunnels using a 3D numerical model.” J. Hydro-environ. Res., 5(1), 3–13.
Information & Authors
Information
Published In
Journal of Irrigation and Drainage Engineering
Volume 143 • Issue 5 • May 2017
Copyright
©2016 American Society of Civil Engineers.
History
Received: Apr 26, 2016
Accepted: Sep 27, 2016
Published online: Nov 30, 2016
Discussion open until: Apr 30, 2017
Published in print: May 1, 2017
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.