Prediction of Vortex on Vertical Intakes by K-nearest Neighbor Modeling

Document Type : Original Article

Authors

Abstract

Using vertical intakes is a common method of water withdrawal from rivers or storages to supply potable or agriculture water. Formation of vortex at vertical intakes is one of serious problems encountered in vertical intakes. Vortex formation reduces the efficiency of structure and causes loss of life. In this study, according to hydraulic conditions and geometry of vertical intakes, vortex formation was predicted by the K-nearest neighbor modeling for different ratios of channel length to width (L/W). The efficiency and precision of the model was evaluated by some statistical coefficients. Appropriate values of the correlation coefficient 0.912, the efficiency of model 0.827 and the root mean square error 0.105 shows this model is suitable and efficient.

Keywords


  1.  

    1. 1.  جلای، و.ح.  و م. همایی. 1390. ارئه مدلی غیرپارامتریک با استفاده از تکنیک k نزدیک‌ترین همسایگی در براورد جرم مخصوص ظاهری خاک. نشریه علوم آب و خاک، سال پانزدهم، شماره 56، ص 189-181.

    2. زمردیان، م. و م. شجاعیان. 1383. تاثیرهندسه کانال تقرب بر قدرت چرخش گرداب و ضریب آبدهی آبگیرقائم. مجله علوم کشاورزی ایران، جلد 35، شماره 3 ، ص 678-669.

    3. Constantinescu, G.S. and V.C. Patel. 2000. “Role of turbulence model in prediction of pump-      bay vortices.” J. Hydraul. Eng., 126(5), 387–391.

    4. Hastie, T., R. Tibshirani and J. Friedman. 2008. The Elements of Statistical Lerning. Second edition, Springer series, California.

    5. Hecker, G.E. 1981. “Model-Prototype Comparison of Free Surface Vortices.” J. Hydraul. Eng., 107(10), 1243–1259.

    6. Knauss, J. 1987. “Swirling Flow Problems at intakes”, IAHR Hydraulic structure Manual No 1, A.A. Balkema, Rotterdam, The Netherlands.

    7. Rindels, A.J. and J.S. Gulliver. 1983. “An experimental study of critical submergence to avoid free-surface vortices at vertical intakes.” Project Rep. No. 224, Saint Anthony Falls Hydraulic Laboratory, Univ. of Minnesota, Minneapolis.

    8. Sharif, M. and D. Burn. 2007. ImprovedK-Nearest Neighbor Weather Generating Model. Journal of Hydrologic Engineering, 137 (6), 42–51.

    9. Travis, Q.B. and L.W. Mays. 2011. “Prediction of Intake Vortex Risk.” J. Hydraul. Eng., 126(5), 701–705.

    10. Vermeyen, T.B. 1999. “Glen Canyon Dam multi-level intake structure  hydraulic model study.” Rep. R-99-02 , U.S. Dept. of the Interior, Bureau of Reclamation, Water Resources Research Laboratory, Denver.

    11. Witten, I.H. and E. Frank. 2005. “Data mining: Practical machine learn ing tools with java implementations, 2nd Ed., Morgan Kaufmann, San Francisco.

    12. Xindung, W. and V. Kumar.  2009. Top Ten Algorithm in Data Mining. First edition, Taylor & Francis Group, USA.