بهينه سازي پارامترهاي معادله حالت آماري SSAFT در تعادل فازي پارافين هاي سبك و سنگين در فشارهاي بالا

Light and Heavy Alkanes at High Pressures by Nelder-Mead Algorithm

Prediction of phase behavior of light and heavy hydrocarbons at high pressures has found many applications in industries and academic purposes, recently. In contrast with the classical equation of states, statistyal EOS can better predict the phase behavior of hydrocarbons at critical and supercritical conditions, because of their theoretyal base approach in thermodynamys. In this study, at first, SAFT EOS was studied and investigated, then by modification of dispersion term the Simplified SAFT equation was introduced. By correlation of vapor pressure and liquid density data of pure alkanes and C02, the model parameters of SAFT and SSAFT equations were obtained using the direct search optimization method of Nelder-Mead algorithm. The correlated parameters such as number of segments (m), interaction energy of the segments (u°/k) and segment diameter (Sigma), were predicted by minimizing the objective function, whyh is the sum of relative error of vapor pressures and liquid densities. The results shows better fitness with experiments in SSAFT rather than SAFT equation ,and in comparison to Peng-Robinson EOS, they both presents better agreement with vapor pressures and liquid densities. In study of the mixtures, vapor liquid equilibria of some non- homogeneous binary mixtures are determined by SSAFT equation using pure component parameters in a broad range of temperatures to estimate binary interaction parameters (k1). Using P-T-X experimental data, this parameter have been optimized by Nelder-Mead algorithm at different temperatures. It is concluded that a quadratic function of temperature can better predict the phase behavior of the studied binary mixtures rather than a constant parameter in broad range of temperatures.