This paper presents the utilization of a stochastic global optimization method for the problem of parameter estimation in thermodynamic models. The method is based on an adaptation of the simulated annealing method to continuous variables. The proposed approach is applied to a vapor-solid equilibrium with supercritical carbon dioxide as solvent. Numerical results indicate that the simulated annealing method calculated a set of parameter values associated with considerably smaller errors as compared with a traditional method of local optimization.
parameter estimation; global optimization; supercritical fluid
