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Applying Multidimensional Method of Moments for Modeling and Estimating Parameters for Arborescent Polyisobutylene Production in Batch Reactor
Author(s) -
Zhao Yutian R.,
Arriola Daniel J.,
Puskas Judit E.,
McAuley Kimberley B.
Publication year - 2017
Publication title -
macromolecular theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.37
H-Index - 56
eISSN - 1521-3919
pISSN - 1022-1344
DOI - 10.1002/mats.201600004
Subject(s) - computation , monte carlo method , weight estimation , biological system , monomer , isobutylene , moment (physics) , estimation theory , method of moments (probability theory) , batch reactor , mathematics , algorithm , statistical physics , materials science , computer science , chemistry , statistics , physics , organic chemistry , classical mechanics , estimator , copolymer , catalysis , biology , polymer
A mathematical model is developed for the arborescent polyisobutylene system in a batch reactor, using multidimensional method of moments, to predict the concentrations of monomer and inimer as well as number and weight average molecular weight. This model is significantly efficient in computation, making parameter estimation practical. Simulation results agree with results obtained by Monte Carlo simulations. Parameter estimation results show that using the weight average molecular weight data provide better overall fit than leaving them out in the previous model.