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Parviz Fathi

Parviz Fathi

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId: 16052387100
Faculty: Faculty of Agriculture
Address:
Phone:

Research

Title
Intelligent estimation of length of recirculating flow in a sudden expansion by artificial neural network.
Type
Presentation
Keywords
Shallow recirculating, Sudden expansion, Neural nerwork, Dimensional analysis
Year
2004
Researchers Amir ahmad Dehghani ، Parviz Fathi ، Masoud Ghodsian

Abstract

The length of recirculating flow depends on: bed friction, velocity of flow, with of channel, with of channel expansion and water depth. by dimensional analysis, dimensionless parameters were obtained and then multilayer perseptron neural network is used for estimation of the recirculating length. The estimated results by neural netwok are in agreement with the exprimental analysis