Open Access Open Access  Restricted Access Subscription or Fee Access

Estimation of Discharge Over the Compound Sharp-Crested Weir using Artificial Neural Networks and Genetic Programming

Akram Abbaspour

Abstract


Truncated sharp crested weirs are used to measure flow rate and to control water surface upstream, in irrigation canals and laboratory flumes. The main advantages of such weirs are, ease of construction and capability of measuring a wide range of flows with sufficient accuracy. Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for the estimation of hydraulic data. In this study, they were used as alternative tools to estimate the discharge of flow over truncated weirs. The hydraulic parameter, including water flow rate Q was determined as functions of the width of crest b, upstream head h, weir height P1, the height of triangular weir P2 and width of flume B. The estimations of the ANN and GP models were found to be in good agreement with the measured data. The results of the ANN model were compared with those of the GP1, GP2, GP3 and GP4 models, showing that the proposed ANN models are much more accurate than the GP models and GP4 model has better performance than GP1, GP2 and GP3 models.


Full Text:

PDF

References


Bos MG. Discharge Measurement Structures. International Institute for Land Reclamation and Improvement) ILRI). The Netherlands: Publication 20, Wageningen; 1989.

United States Department of the Interior, Bureau of Reclamation (USBR). Water Measurement Manual. 3rd Edn. Denver; 1997.

Ackers P, White WR, Harrison AJM. Weirs and Flumes for Flow Measurement. New York: John Wiely and Sons; 1978.

Jan CD, Chang CJ, Lee MH. Discussion of Design and Calibration of Compound Sharp-Crested Weir. J Hydraul Eng, ASCE. 2006; 132(8): 868–72p.

Martinez J, Reca J, Morillas MT, et al. Design and Calibration of a Compound Sharp-Crested Weir. J Hydraul Eng. 2005; 131(2): 112–16p.

Abbaspour A, Yasi M. Flow over Truncated-Triangular Weirs. MSc. Thesis, Department of Water Engineering, University of Urmia; 2001 (in Persian).

Piratheepan M, Winston NEF, Pathirana KPP. Discharge Measurements in Open Channels using Compound Sharp-Crested Weir. J Inst Eng. 2006; (3): 31–8p.

Kambekar AR, Deo MC. Estimation of Pile Group using Neural Networks. Appl Ocean Res. 2003; 25(4): 225–34p.

Azmathullah HM, Deo MC, Deolalikar PB. Alternative Neural Networks to Estimate the Scour below Spillways. Adv Eng Softw. 2008; 39(8): 689–98p.

Mahjoobi J, Etemad-Shahidi A, Kazeminezhad MH. Hindcasting of Wave Parameters using Different Soft Computing Methods. Appl Ocean Res. 2008; 30(1): 28–36p.

Gaur S, Deo MC. Real-Time Wave Forecasting using Genetic Programming. Ocean Eng. 2008; 35(11–12): 1166–72p.

Kalra R, Deo MC. Genetic Programming for Retrieving Missing Information in Wave Records Along the West Coast of India. Appl Ocean Res. 2007; 29(3): 99–111p.

Singh AK, Deo MC, Sanil Kumar V. Neural Network-Genetic Programming for Sediment Transport. Proceedings of the ICE, Maritime Engineering. 2007; 160(3): 113–19p.

Anonymous. Matlab 7.5. User’s Guide. The Math Works Inc; 2007.

Koza JR. Genetic Programming: on the Programming of Computers by Means of Natural Selection. Cambridge: A Bradford Book; 1992.




DOI: https://doi.org/10.3759/jowrem.v2i3.1820

Refbacks

  • There are currently no refbacks.