Abstract
Mechanistic models for ethylene copolymerization with Ziegler–Natta catalysts contain many kinetic rate constants. Precise estimates of key parameters are required if the models are to be used to obtain reliable predictions of polymer properties for a specified catalyst over a range of polymerization conditions. In this paper, a novel method is developed to assist modelers in assessing whether their model parameters will be estimable from existing or proposed experimental data, and in determining subsets of influential parameters that can be estimated from the data when the complete set of model parameters cannot be estimated. The effects of using different types of data, varying the number of observations per experimental run, and increasing the number of experimental runs on the number of estimable parameters are considered. A method for comparison of the relative effectiveness of different experimental designs for estimating key parameters in gas‐phase ethylene copolymerization is also presented.
Acknowledgments
The authors would like to thank Drs. Dan Norman and Norman Rice of the Department of Mathematics and Statistics at Queen's University for helpful advice, and the Natural Sciences and Engineering Research Council of Canada, the Government of Ontario and Queen's University for financial support.