1998Industrial & Engineering Chemistry ResearchRequires access

Group-Contribution Equation of State for the Prediction of Vapor−Liquid Equilibria of Mixtures Containing Hydrofluorocarbons and Alkanes

Nicola Elvassore, Massimiliano Barolo, Alberto Bertucco

Open publisher page 5 citations

Abstract

This work is aimed to present and validate a thermodynamic model that enables the prediction of vapor−liquid equilibria of refrigerant mixtures of alkanes and hydrofluorocarbons, in the temperature and pressure ranges of interest for refrigeration cycles and heat pump applications. A modified Redlich−Kwong−Soave equation of state is used with Huron−Vidal mixing rules and a modified UNIFAC group-contribution approach for calculating the component infinite-pressure activity coefficients. A new classification of functional groups is suggested, and the values of interaction parameters between groups are provided. These parameters are regressed from selected binary vapor−liquid equilibrium data. A good regression is obtained for all group pairs, with a maximum root-mean-square deviation on relative pressure residuals of 1.86%. The proposed method is totally predictive since only the structure, critical constants, and vapor pressure of pure components are needed in order to calculate thermodynamic properties of refrigerant mixtures. Results for a number of binary and ternary mixtures are reported and compared to available experimental data.

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What this paper is about

This work is aimed to present and validate a thermodynamic model that enables the prediction of vapor−liquid equilibria of refrigerant mixtures of alkanes and hydrofluorocarbons, in the temperature and pressure ranges of interest for refrigeration cycles and heat pump applications. A modified Redlich−Kwong−Soave equation of state is used with Huron−Vidal mixing rules and a modified UNIFAC group-contribution approach for calculating the component infinite-pressure activity coefficients. A new classification of functional groups is suggested, and the values of interaction parameters between groups are provided. These parameters are regressed from selected binary vapor−liquid equilibrium data. A good regression is obtained for all group pairs, with a maximum root-mean-square deviation on relative pressure residuals of 1.86%. The proposed method is totally predictive since only the structure, critical constants, and vapor pressure of pure components are needed in order to calculate thermodynamic properties of refrigerant mixtures. Results for a number of binary and ternary mixtures are reported and compared to available experimental data.

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Available abstract

This work is aimed to present and validate a thermodynamic model that enables the prediction of vapor−liquid equilibria of refrigerant mixtures of alkanes and hydrofluorocarbons, in the temperature and pressure ranges of interest for refrigeration cycles and heat pump applications. A modified Redlich−Kwong−Soave equation of state is used with Huron−Vidal mixing rules and a modified UNIFAC group-contribution approach for calculating the component infinite-pressure activity coefficients. A new classification of functional groups is suggested, and the values of interaction parameters between groups are provided. These parameters are regressed from selected binary vapor−liquid equilibrium data. A good regression is obtained for all group pairs, with a maximum root-mean-square deviation on relative pressure residuals of 1.86%. The proposed method is totally predictive since only the structure, critical constants, and vapor pressure of pure components are needed in order to calculate thermodynamic properties of refrigerant mixtures. Results for a number of binary and ternary mixtures are reported and compared to available experimental data.

Key concepts: Refrigerant, UNIFAC, Thermodynamics, Chemistry, Group contribution method, Ternary operation, Equation of state, Vapor–liquid equilibrium

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Group-Contribution Equation of State for the Prediction of Vapor−Liquid Equilibria of Mixtures Containing Hydrofluorocarbons and Alkanes — Research Paper | ScholarLens