Representation and Prediction of Vapor–Liquid Equilibrium Using the Peng–Robinson Equation of State and UNIQUAC Activity Coefficient Model

Abstract

Many important processes in the oil and gas industry (e.g., distillation, absorption, extraction) involve contact between liquid and vapor phases. The reliable design of these industrial processes requires accurate thermodynamic models to describe the vapor−liquid equilibrium (VLE) of the mixtures of interest. Two common approaches, γ−ϕ and ϕ−ϕ, are utilized to describe such VLE behavior. In this study, we present a comprehensive assessment of the representation and predictive capability of these two approaches, utilizing the UNIQUAC model to determine the activity coefficients and the Peng−Robinson (PR) equation of state to calculate the fugacity coefficients. The assessment was completed using a diverse binary VLE database consisting of 916 binary systems involving 140 compounds belonging to 31 chemical classes. Both the overall results and the results categorized for highly nonideal systems and for aqueous systems are presented within the context of internal and external consistency tests. Specifically, regressed and generalized parameters are utilized in internal and external consistency tests, respectively. Further, the phase behavior of sample systems was analyzed using Danner's molecular classification method based on the mNRTL1 parameter and G E /RT values. For the systems considered, the regression results show that the γ−ϕ approach represents the VLE behavior more precisely compared to the ϕ−ϕ approach. The overall results using the γ−ϕ approach exhibit an absolute average deviation (% AAD) of 1.6, 0.1, 4.5, and 5.7 for the pressure, temperature, mole fraction, and equilibrium constant (K), respectively. The ϕ−ϕ approach regression results are within 3 times the error of the γ−ϕ approach. A similar trend was observed for the quantitative structure−property relationship generalized predictions. The γ−ϕ approach predicts the VLE behavior more accurately compared to the ϕ−ϕ approach. The overall results based on the γ−ϕ approach exhibit % AADs of 5.1, 0.4, 5.9, and 8.1 for the pressure, temperature, mole fraction, and K, respectively. The ϕ−ϕ approach generalized predictions are within 2 times the error obtained from the γ−ϕ approach. The results of Danner's molecular classification of the phase behavior indicated that systems with similar components are more likely to produce nearly ideal mixture behavior and systems involving dissimilar components are more likely to produce nonideal mixture behavior. Further, the quality of the representations for the ϕ−ϕ approach are generally good for most system classifications with the exception of adequate or poor fits observed for strongly polar−strongly polar and aqueous−strongly polar systems.

Application of Modified NRTL Models for Binary LLE Phase Characterization

“…To reduce the parameter correlation and narrow down the range of acceptable values in the NRTL model parameters, two modified NRTL models, mNRTL1 and mNRTL2, were developed in our previous work. 21,22 Equations 8 and 9 present the model parameters for the modified NRTL:…”

“…22,23 Further, it was observed that the new proposed parameters, g ij and R ij , are less correlated than the original NRTL parameters a 12 and a 21 . 21,22 The interaction ratio, R ij , in the proposed mNRTL2 model was generalized in terms of pure-fluid properties, acentric factor, and critical pressure, to develop the one-parameter NRTL model (mNRTL1). 3 Pertinent equations and derivatives of the original NRTL and modified NRTL models are presented in the Supporting Information (Appendices A and B).…”

Modeling of Hydrate Dissociation Curves with a Modified Cubic-Plus-Association Equation of State

“…The former tends to be more frequently applied due to the high dissociation pressures of gas hydrates. 9 While most process simulators use cubic equations of state, activity coefficient models or CPA 10 to describe the fluid phases, some recent studies have also considered some SAFT variants. For the representation of noninhibited hydrates of light gases and hydrocarbons some of these studies include those of Fouad et al 11 and el Meragawi et al 12 with PC-SAFT and that of Waseem and Alsaifi 13 with the SAFT-VR Mie.…”

“…Generally, for industrial applications, these fall into two categories: Equations of state or activity coefficient models. The former tends to be more frequently applied due to the high dissociation pressures of gas hydrates …”

Modeling Hydrate Dissociation Curves in the Presence of Hydrate Inhibitors with a Modified CPA EoS

“…In most industrial software, fluid phases are either described by an equation of state or by an activity coefficient model (or both, using excess Gibbs energy mixing rules). For the case of hydrate calculations, the first is more commonly applied because of the high dissociation pressures involved …”