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HERO ID
9090229
Reference Type
Journal Article
Title
Kinetic modeling and dynamic optimization of a commercial dichloroethane thermal cracker
Author(s)
Raoof, M; Farsi, M; Setoodeh, P
Year
2021
Is Peer Reviewed?
1
Journal
Reaction Kinetics, Mechanisms and Catalysis
ISSN:
1878-5190
Publisher
SPRINGER
Location
DORDRECHT
Volume
134
Issue
1
Page Numbers
331-346
Language
English
DOI
10.1007/s11144-021-02069-7
Web of Science Id
WOS:000696411400001
URL
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115064189&doi=10.1007%2fs11144-021-02069-7&partnerID=40&md5=532200b1f05124f1761c7a87cbde0883
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Abstract
In the current research, a mathematical model is developed to simulate a commercial ethylene dichloride thermal cracker assuming pseudo-steady state condition. The considered reaction network includes 19 elementary and reversible reactions, 14 molecules, and 6 radical species. To prove the validity of the proposed model, the simulation results are compared with the available plant data. The results show that the coke build-up and deposition on the inner surface of the coil tube increases the heat transfer resistance during the process run time and has a negative effect on the production rate and pressure drop. Afterward, a sensitivity analysis is performed to investigate the effects of the feed and firebox temperatures on the ethylene dichloride cracking severity and selectivity. The results show that increasing the firebox and feed temperatures enhance the vinyl chloride monomer production rate. In the next step, a dynamic optimization problem is formulated and considered to calculate the optimal dynamic trajectory of the feed and furnace temperatures to achieve the maximum vinyl chloride monomer production rate. The programmed optimization problem is solved by the genetic algorithm method. The results show that applying the optimal trajectory of the decision variables can enhance the VCM production rate by 2.5%. © 2021, Akadémiai Kiadó, Budapest, Hungary.
Keywords
Coke deposition; Dynamic optimization; EDC thermal cracking; Process modeling; Sensitivity analysis
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