Multi-criteria Optimization for Parametrizing Excess Gibbs Energy Models

Abstract

Thermodynamic models contain parameters which are adjusted to experimentaldata. Usually, optimal descriptions of different data sets require differentparameters. Multi-criteria optimization (MCO) is an appropriate wayto obtain a compromise. This is demonstrated here for Gibbs excess energy(GE) models. As an example, the NRTL model is applied to the three binarysystems (containing water, 2-propanol, and 1-pentanol). For each system,different objectives are considered (description of vapor-liquid equilibrium,liquid-liquid equilibrium, and excess enthalpies). The resulting MCO problemsare solved using an adaptive numerical algorithm. It yields the Paretofront, which gives a comprehensive overview of how well the given model candescribe the given conicting data. From the Pareto front, a solution that is particularly favorable for a given application can be selected in an instructedway. The examples from the present work demonstrate the benefits of theMCO approach for parametrizing GE-models.

Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

“…Professor Richard E. Smallley, Rice University [1], said, “Among the 10 major challenges facing human beings, there is no doubt that energy issues are in the first place.” If there is no energy that can be used reasonably, then other problems cannot be solved. It can be seen that energy is an indispensable prerequisite for the development of human society at present [2, 3].…”