A model-based framework assisting the design of vapor-liquid equilibrium experimental plans

In this paper we propose a framework for Model-based Sequential Optimal Design of Experiments to assist experimenters involved in Vapor-Liquid equilibrium characterization studies systematically construct thermodynamically consistent models. The approach uses an initial continuous optimal design obtained via semidefinite programming, and then iterates between two stages (i) model fitting using the information available; (ii) identification next experiment, so that content data is maximized. procedure stops when number experiments reaches maximum experimental program or dissimilarity parameter estimates during consecutive iterations below given threshold. This methodology exemplified with D-optimal isobaric experiments, characterizing binary mixtures NRTL UNIQUAC thermodynamic models liquid phase. Significant reductions confidence regions parameters are achieved compared plans where observations uniformly distributed over domain.