Published Papers
     Search Papers (Springer,
   After 2008)
     Search Papers (Dbpia,
   Until 2007)
     Search Papers (JMST
   own data base)
       - Classification By Year   
       - Classification By Topic
     Special Issues
   
           
   
 
 
Subject Keyword Abstract Author
 
 
Predicting the impact of vegetations in open channels with different distributaries¡¯ operations on water surface profile using artificial neural networks

Mostafa A. M. Abdeen
The Journal of Mechanical Science and Technology, vol. 22, no. 9, pp.1830-1842, 2008

Abstract : Most of the open water irrigation channels in Egypt suffer from the infestation of aquatic weeds, especially the submerged ones that cause numerous hydraulic problems for the open channels themselves and their water distributaries such as increasing water losses, obstructing water flow, and reducing channels¡¯ water distribution efficiencies. Accurate simulation and prediction of flow behavior in such channels is very essential for water distribution decision makers. Artificial neural networks (ANN) have proven to be very successful in the simulation of several physical phenomena, in general, and in the water research field in particular. Therefore, the current study aims towards introducing the utilization of ANN in simulating the impact of vegetation in main open channel, which supplies water to different distributaries, on the water surface profile in this main channel. Specifically, the study, presented in the current paper utilizes ANN technique for the development of various models to simulate the impact of different submerged weeds¡¯densities, different flow discharges, and different distributaries operation scheduling on the water surface profile in an experimental main open channel that supplies water to different distributaries. In the investigated experiment, the submerged weeds were simulated as branched flexible elements. The investigated experiment was considered as an example for implementing the same methodology and technique in a real open channel system. The results showed that the ANN technique is very successful in simulating the flow behavior of the pre-mentioned open channel experiment with the existence of the submerged weeds. In addition, the developed ANN models were capable of predicting the open channel flow behavior in all the submerged weeds¡¯cases that were considered in the ANN development process

Keyword : Artificial neural network; Open channel hydraulics modeling; Open channel infested by submerged weeds

 
 
 
JMST Editorial Office: #702 KSTC New Bldg, 22 7-gil, Teheran-ro, Gangnam-gu, Seoul 06130, Korea
TEL: +82-2-501-3605, E-mail: editorial@j-mst.org
JMST Production Office: #702 KSTC New Bldg, 22 7-gil, Teheran-ro, Gangnam-gu, Seoul 06130, Korea
TEL: +82-2-501-6056, FAX: +82-2-501-3649, E-mail: editorial@j-mst.org