Inverse Problem Applied to Antoine Equation for Acetone and Ethanol

Abstract

Evolutionary Algorithms (AEs) are non-deterministic optimization methods widely used in the literature and find great relevance and wide use in problems involving non-linear, non-differentiable or multimodal functions. Differential Evolution (DE) is an algorithm that has elements of the AEs, such as the mutation, crossing and selection operator, but differs in the generation of new individuals. In this work, the DE algorithm was used to solve the inverse problem of determining the coefficients of the Antoine equation for acetone and ethanol. To this end, temperature and pressure data available in the Dortmund Data Bank (DDB) were used and 30 simulations were performed for each parameter of disturbance rate (F) and crossover probability (CR). The pressure predictions calculated using the parameters obtained by the stochastic process showed greater agreement with the experimental data when compared with the predictions obtained through the parameters consulted in the literature.