Using Artificial Neuron Network on the Impact Characteristics Analysis of Free Overfall Flow

Article Preview

Abstract:

This study is to forecast the impact force and impact position of free over-fall flow in the downstream by using artificial neuron networks (ANN). A simulation procedure for the ANN algorithm was established to train and validate numerical samples with the experimental data. The outcomes of simulation show the ANN method can properly estimate the impact force and position.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

4124-4128

Citation:

Online since:

July 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Rouse, H., Discharge characteristics of the free overfall. Civil Engineering (1936), ASCE, 6(4), 257-260.

Google Scholar

[2] Rand W., Flow geometry at straight drop spillways. Journal of Hydraulic Engineering, (1955), ASCE 81, 1-13.

Google Scholar

[3] Ferro, V., Flow measurement with rectangular free overfall. Journal of Irrigation and Drainage Engineering, (1992), 118(6), 956-964.

DOI: 10.1061/(asce)0733-9437(1992)118:6(956)

Google Scholar

[4] Chamani, M. R., Beirami, M.K., Flow characteristics at drop. Journal of Hydraulic Engineering. (2002), ASCE, 128(8), 788-791.

DOI: 10.1061/(asce)0733-9429(2002)128:8(788)

Google Scholar

[5] Hong Y.M., Huang H.S., and Wan S., Drop characteristics of free-falling nappe for aerated straight-drop spillway, Journal of Hydraulic Research, (2010), 48(1), 125 - 129.

DOI: 10.1080/00221680903568683

Google Scholar

[6] Finnie, G. R., Wittig G. E. & Desharnais, J-M., A comparison of software effort estimation techniques: Using function points with neural networks, case-based reasoning and regression models. Journal of Systems and Software, (1997), 281-289.

DOI: 10.1016/s0164-1212(97)00055-1

Google Scholar

[7] Raikar, R.V., Kumar, D. N., & Dey S., End depth computation in inverted semicircular channels using ANNs. Flow Measurement and Instrumentation, (2004), 15, 285–293.

DOI: 10.1016/j.flowmeasinst.2004.06.003

Google Scholar

[8] Baylar, A., Hanbay, D., & Ozpolat, E., An expert system for predicting aeration performance of weirs by using ANFIS. Expert Systems with Applications, (2008), 35, 1214–1222.

DOI: 10.1016/j.eswa.2007.08.019

Google Scholar

[9] Chanson, H., Hydraulic design of stepped cascades, channels, weirs and spillways. Pergamon, Oxford, UK. (1995).

Google Scholar

[10] Kantardzic M., Data mining-concepts, models, methods, and algorithms, IEEE, Wiley-interscience, USA, (2003), 196-217.

Google Scholar

[11] Howard D., and Mark B., Neural network toolbox- for use with MATLAB. The MathWorks, Inc. (2004).

Google Scholar