Data-Driven Estimation of Significant Kinetic Parameters Applied to the Synthesis of Polyolefins

Salas, Santiago D.; Brandão, Amanda L. T.; Soares, João B. P.; Romagnoli, José A.

doi:10.3390/pr7050309

Cited by 7 publications

(2 citation statements)

References 40 publications

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“…Brandão et al, [45] Salas et al [46] 1 Solution Ethylene/1,9-decadiene copolymerization using metallocene catalyst was modeled. Number-and weight-average MW and ethylene feed rate were used to estimate activation, propagation, chain-transfer, and deactivation rate constants along with their activation energies.…”

Section: Lab-scale Data and Experimental Set-upmentioning

confidence: 99%

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

Gibson

Yan

Boller

et al. 2023

Macro Reaction Engineering

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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.

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Section: Lab-scale Data and Experimental Set-upmentioning

confidence: 99%

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

Gibson

Yan

Boller

et al. 2023

Macro Reaction Engineering

View full text Add to dashboard Cite

show abstract

“…Salas et al [10] present a data-driven strategy for the online estimation of important kinetic parameters in copolymerization of ethylene. The kinetic parameters are chosen based on a global sensitivity analysis.…”

mentioning

confidence: 99%