Crystallization

Advanced validation tools

gPROMS' state-of-the-art parameter estimation tools help extract accurate model parameters from experimental data, using mathematical optimisation techniques that take advantage of the information that is already contained in the model.

In addition, a confidence analysis generates information that can be used to provide an indication of the risks inherent in the parameter fit, and determine whether further experimentation is required.

If it is, model-based experiment design techniques can be used to design subsequent experiments with the maximum information content, thereby minimsing the number of experiments that need to be performed to obtain the desired parameter accuracy.

Measurement types

Data from the following instrument sources can be handled, among others:

laser diffraction
sieving
accoustic attenuation

Data can be steady-state and dynamic, and estimation is not limited to parameters of pre-defined models.

See the general page on model validation for more information.