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Received May 10, 2021
Accepted August 25, 2021
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
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Molecular weight distribution modeling of LDPE in a continuous stirred-tankreactor using coupled deterministic and stochastic approach
School of Chemical and Biological Engineering, Seoul National University, Seoul 08826, Korea
jongmin@snu.ac.kr
Korean Journal of Chemical Engineering, March 2022, 39(3), 798-810(13), 10.1007/s11814-021-0943-9
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Abstract
A hybrid approach that combines the method of moments and Monte Carlo simulation to predict the_x000D_
molecular weight distribution of low-density polyethylene for a continuous stirred tank reactor system is proposed. A ‘Block’, which is repeating reaction group, is introduced for the calculation cost-effective simulation. This model called the ‘block Kinetic Monte Carlo’ is ~10 to 32 times faster than Neuhaus’s model. The model can be applied to any steady state system and provide a calculation cost reduction effect, where one reaction is much faster than others, for example, the propagation reaction. Furthermore, we performed a case study on the effects of the system temperature and initiator concentration on the MWD and reaction rate ratio. Based on the simulation results of 180 case studies, we determined a quantitative guideline for the appearance of shoulder, which is a function of the rate ratio of reactions to the propagation reaction.
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Yaghini N, Iedema PD, Chem. Eng. Sci., 116, 144 (2014)
Meimaroglou D, Pladis P, Baltsas A, Kiparissides C, Chem. Eng. Sci., 66, 1685 (2011)
Kim DM, Busch M, Hoefsloot HC, Iedema PD, Chem. Eng. Sci., 59, 699 (2004)
Kiparissides C, Krallis A, Meimaroglou D, Pladis P, Baltsas A, Chem. Eng. Technol., 33, 1754 (2010)
Iedema PD, Hoefsloot HC, Macromol. Theory Simul., 10, 855 (2001)
Kim DM, Iedema PD, Chem. Eng. Sci., 59, 2039 (2004)
Kim DM, Iedema PD, Chem. Eng. Sci., 63, 2035 (2008)
Yaghini N, Iedema PD, Chem. Eng. Sci., 130, 310 (2015)
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Tobita H, Macromol. Theory Simul., 5, 129 (1996)
Tobita H, Macromol. React. Eng., 7, 181 (2013)
Tobita H, Macromol. Theory Simul., 23, 182 (2014)
Rogosic M, Mencer HJ, Gomzi Z, Eur. Polym. J., 32, 1337 (1996)
Neuhaus E, Herrmann T, Vittorias I, Lilge D, Mannebach G, Gonioukh A, Busch M, Macromol. Theory Simul., 23, 415 (2014)
Sch?tte C, Wulkow M, Macromol. React. Eng., 4, 562 (2010)
Eckes D, Busch M, Macromol. Symp., 360, 23 (2016)
Meimaroglou D, Kiparissides CA, Macromolecules, 43, 5820 (2010)
Feucht P, Tilger B, Luft G, Chem. Eng. Sci., 40, 1935 (1985)
Tobita H, Processes, 3, 731 (2015)
Chien IL, Kan TW, Chen BS, Comput. Chem. Eng., 31, 233 (2007)
Kotliar AM, J. Polym. Sci., Part A: Gen. Pap., 2, 4303 (1964)
Krallis A, Pladis P, Kiparissides C, Macromol. Theory Simul., 16, 593 (2007)
Kolhapure NH, Fox RO, Chem. Eng. Sci., 54, 3233 (1999)
Marini L, Georgakis C, Chem. Eng. Commun., 30, 361 (1984)
