Investigation of flow resistance in smooth open channels using artificial neural networks

Küçük Resim Yok

Tarih

2008

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

ELSEVIER SCI LTD

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

An accurate prediction of the friction coefficient is very important in hydraulic engineering since it directly affects the design of water structures, the calculation of velocity distribution, and an accurate determination of energy losses. However, conventional approaches that are profoundly based on empirical methods lack in providing high accuracy for the prediction of the friction coefficient. Consequently, new and accurate techniques are still highly demanded. This study introduces an efficient approach to estimate the friction coefficient via an artificial neural network, which is a promising computational tool in civil engineering. The estimated value of the friction coefficient is used in Manning Equation to predict the open channel flows in order to carry out a comparison between the proposed neural networks based approach and the conventional ones. Results show that the proposed approach is in good agreement with the experimental results when compared to the conventional ones. (C) 2008 Elsevier Ltd. All rights reserved.

Açıklama

Anahtar Kelimeler

Open channel, Friction coefficient, Artificial neural networks, Manning equation

Kaynak

FLOW MEASUREMENT AND INSTRUMENTATION

WoS Q Değeri

Q2

Scopus Q Değeri

Q2

Cilt

19

Sayı

6

Künye