Application of Multiobjective Optimization in the Analysis of the Performance of Different Temperature Functions for a Generalized Cubic Equation of State

Abstract

Since the emergence of van der Waals equation of state, several equations have been proposed to represent the behavior of pure compounds and mixtures, such as GEOS, which is a new generalized cubic equation of state form that employs a temperature function dependent on two or three adjustable parameters. Recently, multiobjective optimization has started to be applied in equations of state for parameters estimation, due to the conflicting nature of the objective functions. This methodology is attractive because it can be used to compare different models or variants of the same problem, through the trade-off analysis of the so-called Pareto front. In this context, the multiobjective PSO algorithm, based on the Pareto dominance principle, is used in this work for estimating the parameters of the generalized cubic equation of state, by fitting its results to synthetic experimental data of vapor pressure and saturated liquid volume. The performance of the new estimated parameters of the three temperature functions is investigated through the calculation of thermodynamic properties of interest in industry and academia. In addition, comparisons against real experimental data available in the literature are performed.