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Sustainable refrigerant selection in binary blends of the R1234yf: hydrofluoroethers.

Author(s) : ARTEMENKO S., NIKITIN D., HADDAD S., et al.

Summary

Analytical expressions of azeotrope boundaries in the global phase diagram for the Peng-Robinson equation of state (EoS) are used to recognize the azeotropic and near azeotropic pairs in the R1234yf + hydrofluoroethers (HFE) binary blends. It is shown that R1234yf-HFE blends form azeotrope practically for all HFEs with critical temperatures less than 400 K. It is predicted that adding HFE allows obtaining the equal thermodynamic properties with R134a. The artificial neural networks (ANN) correlations for COP and pressure ratio (outputs) as function of critical temperature, critical pressure, and acentric factor-(input) are considered. The ANN architecture for prediction of pressure ratio includes the 2 layers with 6 and 1 neurons, correspondingly. The ANN for COP prognosis considers 3 layers with 2, 6 and 1 neurons, correspondingly. The accuracy of ANN prediction for the cycle characteristics does not exceed 3%. Finally, the sustainable decision is defined by the Bellman-Zadeh model decision making in a fuzzy environment as the intersection of membership functions.

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Pages: 2010-1

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Details

  • Original title: Sustainable refrigerant selection in binary blends of the R1234yf: hydrofluoroethers.
  • Record ID : 2010-0389
  • Languages: English
  • Source: 1st IIR International Conference on Sustainability and the Cold Chain
  • Publication date: 2010/03/29

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