LAPSE:2020.0216
Published Article

LAPSE:2020.0216
Thermal Cracking Furnace Optimal Modeling Based on Enriched Kumar Model by Free-Radical Reactions
February 12, 2020
Abstract
The Kumar model as a molecular model has achieved successful application. However, only 22 reactions limit its veracity and adaptability for feedstocks. A series of models with different degrees of integration of the free radical model and the molecular model has been proposed to enhance feedstock adaptability and simulation accuracy. An improved search engine algorithm, namely Improved PageRank (IPR), is provided and applied to calculate the importance of substances in Kumar model to screen the free-radical reaction network for efficient model selection. A methodology of optimal structure and model parameters chosen is applied to the target to improve the adaptability of the material and the accuracy of the model. Then, two cases with different feedstocks are demonstrated with industrial data to verify the correctness of the proposed approach and its wide feedstock adaptability. The proposed model demonstrates good performance: (1) The mean relative errors (MRE) of the K-R (Kumar and free-radical) model have reached an order of magnitude less than 0.1% compared with 5% in the Kumar model. Further, (2) the K-R model can be implemented to model some feedstocks which Kumar model can’t simulate successfully. The K-R model can be applied in simulation of extensive feedstocks with high accuracy.
The Kumar model as a molecular model has achieved successful application. However, only 22 reactions limit its veracity and adaptability for feedstocks. A series of models with different degrees of integration of the free radical model and the molecular model has been proposed to enhance feedstock adaptability and simulation accuracy. An improved search engine algorithm, namely Improved PageRank (IPR), is provided and applied to calculate the importance of substances in Kumar model to screen the free-radical reaction network for efficient model selection. A methodology of optimal structure and model parameters chosen is applied to the target to improve the adaptability of the material and the accuracy of the model. Then, two cases with different feedstocks are demonstrated with industrial data to verify the correctness of the proposed approach and its wide feedstock adaptability. The proposed model demonstrates good performance: (1) The mean relative errors (MRE) of the K-R (Kumar and free-radical) model have reached an order of magnitude less than 0.1% compared with 5% in the Kumar model. Further, (2) the K-R model can be implemented to model some feedstocks which Kumar model can’t simulate successfully. The K-R model can be applied in simulation of extensive feedstocks with high accuracy.
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Keywords
improved pagerank algorithm (IPR), K-R model, kinetics, model-fitting, reaction network enrichment
Subject
Suggested Citation
Mu P, Gu X. Thermal Cracking Furnace Optimal Modeling Based on Enriched Kumar Model by Free-Radical Reactions. (2020). LAPSE:2020.0216
Author Affiliations
Mu P: College of Information Science & Technology, Beijing University of Chemical Technology, Beijing 100029, China; Engineering Research Center of Intelligent PSE, Ministry of Education of China, Beijing 100029, China
Gu X: College of Information Science & Technology, Beijing University of Chemical Technology, Beijing 100029, China; Engineering Research Center of Intelligent PSE, Ministry of Education of China, Beijing 100029, China; Sinopec Engineering (Group) Co., Ltd., Be
Gu X: College of Information Science & Technology, Beijing University of Chemical Technology, Beijing 100029, China; Engineering Research Center of Intelligent PSE, Ministry of Education of China, Beijing 100029, China; Sinopec Engineering (Group) Co., Ltd., Be
Journal Name
Processes
Volume
8
Issue
1
Article Number
E91
Year
2020
Publication Date
2020-01-09
ISSN
2227-9717
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Original Submission
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PII: pr8010091, Publication Type: Journal Article
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Published Article

LAPSE:2020.0216
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https://doi.org/10.3390/pr8010091
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[v1] (Original Submission)
Feb 12, 2020
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Feb 12, 2020
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https://psecommunity.org/LAPSE:2020.0216
Record Owner
Calvin Tsay
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