Modelling of Supercritical Fluid Extraction by Hybrid Peng–Robinson Equation of State and Genetic Algorithms

In this paper, a hybrid model is developed for supercritical fluid extraction, where the genetic algorithm is used to generate the non-linear binary interaction parameter of the Peng–Robinson equation. Various temperatures, pressures, and solubility are used to test the proposed model. The correlation and the mean square errors of the proposed hybrid model and the conventional Peng–Robinson model are given in the paper. The predictions of the proposed hybrid model are compared to those of the Peng–Robinson model. Generally, the results using the proposed model are better than those using the conventional model because the genetic algorithm used in this paper can provide a better binary interaction parameter to fit the experimental data. The effectiveness of the proposed hybrid approach is demonstrated by simulation and comparison studies.