Parametrization of the NRTL Model with a Multiobjective Approach: Implications in the Process Simulation

Abstract

Thermodynamics, as a scientific tool, advises on the control of variables involved in processes of different nature and is particularly useful in the design of equipment, or to obtain previous simulations. However, to generate more accurate models, an exact science is required. Thus, the thermodynamic–mathematical binomial is able to relate the fundamental variables of a system using the potential functions directing the process, although these relationships are not always completely satisfactory, as it is necessary to complete the modelling with a set of parameters, which depend on the experimentation. To ensure a better description of the behavior of a system, in this work a multi-objective optimization procedure (MOP) is applied to the NRTL model, comparing the results with other conventional procedures used to characterize the real properties of the binary methyl methanoate + pentane. The results obtained with the MOP confirmed a better representation of the experimental information with NRTL, analyzing its impact on the simulation/design processes. The set of optimal parametrizations obtained allow several options to be process engineered to select the most appropriate one depending on the specific problem to be designed.