A hybrid optimization approach to interaction parameter identification in thermodynamic model problems
Keywords:
hybrid optimization approach,, enetic algorithm, imulated annealing,, arameter estimationAbstract
The interaction parameter identification problem in thermodynamic models is an important requirement and a common
task in many areas of chemical engineering because these models form the basis for synthesis, design, optimization and
control of process. For bad starting values the use gradient based result in local optimal solutions. To overcome this
drawback, a global optimization approach, Simulated Annealing (SA) and genetic algorithm(GA), has been coupled with a
Nelder-Mead Simplex(
NMS) method. To improve the accuracy of the interaction parameter estimate. The experimental
ternary LLE data for extraction of 1-propanol from water with n-hexane were considered in the NRTL and UNIQUAC
activity coefficient model. In conclusion, the different obtained results of the prediction of liquid–liquid equilibrium are
compared. These results were obtained to justify that the process of optimization recommended is very practical to estimate
the interaction parameters of this ternary system
