PARAMETER-ESTIMATION IN SIMULTANEOUS PHASE AND REACTION EQUILIBRIA

The estimation of parameters of models describing simultaneous phase and reaction equilibria is generally difficult to accomplish, due to strong correlation between the parameters. We show in this paper that these models possess intermediate properties between reduced and implicit models. This makes it convenient to develop ad-hoc algorithms for this class of problems which are of considerable importance in process design. We present a method for parameter estimation based on implicit differentiation, which makes it possible to use a gradient algorithm with respect to a reduced number of parameters, which greatly enhances global convergence. A numerical example is examined for comparison.