Estimating Free and Submerged Hydraulic Jump’s Length in Horizontal and Slopping Channels Using Support Vector Regression

Document Type : Research Paper

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Abstract

Hydraulic jump is the most common method for kinetic energy dissipating at downstream of spillways, chutes and gates. Several relations have been proposed to estimate the length of hydraulic jump, but the results of these equations are not general and acceptable due to the uncertainty of the functions. Consequently, it is essential to estimate the hydraulic jump length, accurately. In this paper, hydraulic jump length was estimated for free and submerged hydraulic jumps on horizontal and slopping smooth beds using support vector regression as one of the machine learning methods and the rate of influence of input parameters in each jump was analyzed. Totally, 294 patterns of the observed data were used for training and testing processes of the four kinds of hydraulic jump models. Comparison between support vector regression (SVR), classical and empirical equations and gene expression programming (GEP) method showed the noticeable efficiency of the support vector regression.

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References

عباسپور ا، 1393. پیش‌بینی مشخصات پرش هیدرولیکی بر روی بستر زبر با استفاده از شبکه عصبی مصنوعی و برنامه­ریزی ژنتیک. نشریه دانش آب و خاک، جلد 24، شماره 2، صفحه‌های 1 تا 10.
Abbaspour A, Hosseinzadeh Dalir A, Farsadizadeh D and Sadraddini AA, 2009. Effect of sinusoidal corrugated bed on hydraulic jump characteristics. Journal of Hydro-environment Research 3: 109-117.
Ahmed HMA, Gendy ME, Mirdan AMH, Mohamed Ali AA and Abdel Haleem FSF, 2014. Effect of corrugated beds on characteristics of submerged hydraulic jump. Ain Shams Engineering Journal 5: 1033-1042.
Ansari M, 2014. ANN model for prediction of length of hydraulic jump on rough beds. International Journal of Civil Engineering and Technology 5: 23-31.
Bhutto H, 1987. Hydraulic jump control and energy dissipation. Doctoral dissertation, Mehran University of engineering and technology. Jamshoro.
Bakhmateff BA and Matzeke AE, 1938. The Hydraulic Jump in Sloped Channels. Transactions of ASME 60: 111-118.
Carollo FG, Ferro V and Pampalone V, 2007. Hydraulic jump on rough beds. Journal of Hydraulic Engineering 133: 989-999.
Feng Li C, 1995. Determining the location of hydraulic jump by model test and HEC-2 Flow routing. Master thesis, college of engineering and technology. Ohio University.
Ferreira C, 2001. Gene expression programming: A new adaptive algorithm for solving problems. Complex Systems 13(2): 87-129.
Henderson FM, 1966. Open Channel Flow. Macmillan Publishing Co., Inc., New York.
Naseri M and Othman F, 2012. Determination of the length of hydraulic jumps using artificial neural networks. Advance in Engineering Software 48: 27-31.
Nolan P, 1936. Discussions of “The Hydraulic Jump in Terms of Dynamic Similarity”, by Bakhmateff, B.A., Matzeke AE., Transactions of ASCE 101: 630-664.
Semetana J, 1934. Experimentalni Studie Vodniho Skoku Vzdutoho, (Experimental Study of Drowned Hydraulic Jump. Zpravy Verejne Stuzby Techicke, Czechoslovakia.
Vapnik, V, 1999. The Nature of Statistical Learning Theory. Springer, Information Science and Statistics series, 314 p.
Woyocicki k, 1931. Wassersprug, Deckwalze Und Ausfluss Unter Einer Schutze, (The hydraulic Jump, Its Top Roll and Discharge through a Sluice Gate. Warschau, Polnischen Akademie der Techn, 55 p.
Water and Soil Science
Volume 26, 3-2
December 2016
Pages 51-62

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