1. INTRODUCTION In order to overcome the problem of locating azeotropic point that arises in the field of refrigeration and distillation. Diverse methods are used: experimental and thermodynamic model (Peng–Robinson equation of state; Mathias–Copeman alpha function; Wong–Sandler mixing rules; NRTL model, etc.). The repeated condensation and evaporation processes in refrigeration process modify the composition of the azeotropic mixtures and their thermodynamic properties. So, this causes a lag in the boiling and condensation temperature at constant pressure. The heat capacity and heat of vaporization change, this leads to changing the refrigeration process performances. Our interest is to correctly predict the azeotropic property of binary mixtures. As an illustration of this idea, we presented simple model for predicting the azeotropic behavior in refrigeration binary mixtures and for establish the best composition for the best performance. Besides, we try to find refrigerant blends compatible with existing refrigerating machines and having similar characteristics similar characteristics to the use CFCs. This method based on experimental data and thermodynamic model. We have applied them to binary mixtures R152a + R600 [2], R744 + R152a [1] and R134a + R152a [3]. 2. METHODS Here, we predict the azeotropic location for refrigerant binary mixtures by the combination of approach which is based on experimental data and an accurate thermodynamic model is necessary, to validate the obtained results. This model focuses on two approaches. A schematic diagram of our model is presented in Figure 1. In the first approach, we use the experimental data of binary mixtures, with calculated volatility (α12) to find the most volatile component. Afterwards, we utilize Microsoft Excel as a powerful tool to meet the major needs of data analysis and modeling. In the second approach, in order to estimate and describe the behavior of both azeotropic and critical point, it is important to carefully consider the choice of equations namely, the Peng-Robinson [4], with Mathias–Copeman alpha function [5]. For excellent representation of vapor- liquid equilibrium, we used Wong–Sandler [6] mixing rules with NRTL [7] excess free energy (G E ) model. The aim is to develop reliable prediction methods, which can predict the azeotropic point and determine the critical point. Because, it is rare to find experimental data covering a wide range of operating conditions for refrigerants used in industrial refrigeration with air conditioning and which can be measured. MATHEMATICAL MODELLING OF ENGINEERING PROBLEMS ISSN: 2369-0739 (Print), 2369-0747 (Online) Vol. 4, No. 1, March 2017, pp. 38-42 DOI: 10.18280/mmep.040108 Licensed under CC BY-NC 4.0 A publication of IIETA http://www.iieta.org/Journals/MMEP Azeotropic points with relative volatility-prediction and calculation Saida Fedali * , Hakim Madani Department of Mechanics, Faculty of Technology, Laboratory of Studies of the Industrial Energy Systems (LESEI), University of Batna, Algeria Email: saida_fedali@yahoo.fr ABSTRACT In this study, we predict the locus of azeotropes for binary mixtures by using the relative volatility is presented. A simple method is used in binary mixtures: At first we applied the method which is based on experimental data and then we evaluated by thermodynamic model. The model composed: • Peng-Robinson equation of state • Mathias-Copeman alpha function • Wong-Sandler mixing rules • NRTL model 1,1-difluoroethane (R152a) + n-butane (R600) , carbon dioxide (R744) + 1,1-difluoroethane (R152a) and 1,1,1,2-Tétrafluoroéthane (R134a) + 1,1-difluoroethane (R152a) are the binary mixtures used in this work. The results confirm that there is a good agreement between the predicted values and the experimental data and the relative error does not exceed 1% for the molar fraction and 0.5% for the pressure. In conclusion, this method is considered able to predict the azeotropic location. Keywords: Equation of State, Mixing Rules, Excess Free Energy, Azeotrope, Relative Volatility. 38