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- Title
PREDICTION OF PHASE BEHAVIOR OF MIXED REFRIGERANTS HFC125-HFC134a BY USING RADIAL BASIS FUNCTION ARTIFICIAL NEURAL NETWORK.
- Authors
ZareNezhad, Bahman
- Abstract
A Normalized Radial Basis Function (NRBF) neural network has been presented for accurate prediction of the vapor liquid equilibrium (VLE) of pentafluoroethane (HEC125) and 1,1,1,2-tetrafluoroethane (HEC134a) mixed refrigerants According to the network's training, validation and testing results, a network with sixteen hidden nodes is selected as the best architecture. The presented model is very accurate over wide ranges of experimental pressure and temperature values. The predicted VLE of the refrigerant mixture is accurate enough to be employed in the design of refrigeration cycles.
- Subjects
REFRIGERANTS; RADIAL basis functions; ARTIFICIAL neural networks; TETRAFLUOROETHANE; FLUOROHYDROCARBONS
- Publication
Journal of Chemical Technology & Metallurgy, 2016, Vol 51, Issue 1, p85
- ISSN
1314-7471
- Publication type
Article