Prediction of pure and mixture thermodynamic properties and phase equilibria using an optimized equation of state – part 1: Parameter estimation

Abstract

This study presents a novel three-parameter equation of state (EOS) wherein attraction parameter polynomial coefficients are optimized to enhance predictive capabilities. The performance of the proposed EOS is systematically compared with established models including Peng-Robinson, Patel-Teja, and Twu-Coon-Cunningham equations. Through comprehensive evaluation, it is demonstrated that the proposed EOS exhibits superior accuracy in vapor pressure and latent enthalpy predictions, while maintaining comparable precision in liquid density estimations. Notably, the fugacity expression of the proposed EOS closely resembles that of a two-parameter equation, resulting in significantly reduced computational overhead. Additionally, a comprehensive table of equation of state parameters for all four equations is available in an online repository, facilitating easy implementation and comparison. Furthermore, a reliable generalized polynomial correlation is provided for the proposed EOS parameters against the true compressibility factor and acentric factor, leveraging data accessibility and enhancing its applicability and versatility. These findings underscore the potential of the optimized attraction parameter polynomial coefficients approach in advancing the accuracy and efficiency of EOS modeling, thereby offering promising avenues for diverse applications in thermodynamics and process engineering.