Raikar, RV and Kumar, D Nagesh and Dey, Subhasish (2004) End depth computation in inverted semicircular channels using ANNs. In: Flow Measurement and Instrumentation, 15 (5-6). pp. 285-293.
39.pdf - Published Version
Restricted to Registered users only
Download (305Kb) | Request a copy
The paper presents the application of artificial neural network (ANN) to determine the end-depth-ratio (EDR) for a smooth inverted semicircular channel in all flow regimes (subcritical and supercritical). The experimental data were used to train and validate the network. In subcritical flow, the end depth is related to the critical depth, and the value of EDR is found to be 0.705 for a critical depth-diameter ratio up to 0.40, which agrees closely with the value of 0.695 given by Dey [Flow Meas. Instrum. 12 (4) (2001) 253]. On the other hand, in supercritical flow, the empirical relationships for EDR and non-dimensional discharge with the non-dimensional streamwise slope of the channel are established.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Elsevier.|
|Keywords:||Artificial neural network;One-dimensional flow;Open channels;Steady flow|
|Department/Centre:||Division of Mechanical Sciences > Civil Engineering|
|Date Deposited:||18 Dec 2008 12:35|
|Last Modified:||19 Sep 2010 04:54|
Actions (login required)