Modeling and Parameter Estimation for Gas‐Phase Polyethylene Product Properties Using Dynamic and Steady‐State Data

Models are developed for gas‐phase ethylene/1‐hexene copolymerization using a 3‐site hafnocene catalyst. The models accurately predict joint molecular weight distribution and copolymer composition data for 15 semibatch lab‐scale copolymerization runs and 6 steady‐state pilot‐plant copolymerization runs, respectively. Kinetic rate constants and activation energies, which are common to both models, are estimated for the three types of active sites for each reaction in the kinetic scheme. Using parameter subset selection and estimation techniques, it is found that 34 of the 61 parameters should be estimated from the data. Incorporating the pilot‐plant data allow for estimation of two parameters, a deactivation rate constant and a β‐hydride elimination activation energy, that are not estimable using the lab‐scale data alone. At the 95% confidence level, 25 of the 34 parameters are significantly different than zero, which is more than the 19 significant parameter estimates obtained from the lab‐scale data alone. Good fits to the data are obtained, as are reliable predictions for a validation run not used in parameter estimation. Models and estimated kinetic parameters are used to predict polymer properties from reactor operating conditions, making them valuable for faster and reliable scale‐up of new polymer grades. Models describing gas‐phase ethylene/hexene copolymerization using a three‐site metallocene catalyst are developed. The models accurately predict the joint molecular weight and copolymer composition distribution for semi‐batch lab‐scale copolymerization and steady‐state pilot‐plant copolymerization runs.