Resumo. Este trabalho apresenta um estudo analítico sobre a acurácia dos parâmetros estimados por Mota [10] para a equação de estado de Patel-Teja no cálculo das propriedades termodinâmicas, volume de líquido saturado e entalpia de vaporização. Com o objetivo de avaliar o poder preditivo dessas propriedades termodinâmicas para tal equação foram utilizados dados experimentais, bem como os parâmetros da proposta original de Patel-Teja.

Since the emergence of the van der Waals model, a lot of equations of state have been proposed to represent the pressure-volume-temperature (PVT) behavior of pure compounds, as is the case with GEOS3C, which is a form of generalized cubic equation of state that uses a temperature function dependent on three adjustable parameters. As the predictive capacity of an equation of state is directly related to the use of adequate and efficient methods for estimating the model's parameters, it is advised to use the multiobjective optimization in this class of problems, due to the conflicting nature of the objective functions. In this context, a MOPSO algorithm, based on the Pareto dominance principle, is used to estimate the parameters of the GEOS3C, through the minimization of the deviations in the prediction of different thermodynamic properties: saturation pressure, saturated liquid volume, enthalpy of vaporization and isobaric heat capacity, in order to assess whether it is possible to obtain a model parameterization that is adequate to represent the different properties simultaneously. Comparisons with experimental data available in the literature are performed showing that multiobjective optimization offers new perspectives for improvements in the parameters estimation of equations of state compared to traditional methods.

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.