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Neural network azeotropic prognosis in binary refrigerant mixtures.

[In Russian. / En russe.]

Author(s) : ARTEMENKO S. V.

Type of article: Article

Summary

This article presents a neural network model applied to the prediction of azeotropic phenomena in binary mixtures from pure component critical parameters. This approach does not require intensive calculations of vapour-liquid equilibria. The overall phase diagram technique, which provides a comprehensive set of phase behaviour criteria for binary mixtures, has been used as an azeotropic classifier. The simple analytical expressions for azeotropic state membership definition using the Peng-Robinson equation of state model have been obtained. The neural network, applied to a limited set of available data on refrigerant mixtures, provides a reliable prediction of azeotropic states for 1770 binary combinations of known artificial and natural refrigerants.

Details

  • Original title: [In Russian. / En russe.]
  • Record ID : 2005-1643
  • Languages: Russian
  • Source: Holodil'na Tehnika i Tehnologiâ - n. 2
  • Publication date: 2004

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