Theoretical analysis of double logistic distributed activation energy model for thermal decomposition kinetics of solid fuels
Theoretical analysis of double logistic distributed activation energy model for thermal decomposition kinetics of solid fuels
The distributed activation energy model (DAEM) has been widely used to analyze the thermal decomposition of solid fuels such as lignocellulosic biomass and its components, coal, microalgae, oil shale, waste plastics, and polymer etc. The DAEM with a single distribution of activation energies cannot describe those reactions well because the thermal decomposition normally involves multiple subprocesses of various components. The double DAEM employs a double distribution to represent the activation energies. The Gaussian distribution is usually used to represent the activation energies. However, it is not sufficiently accurate for addressing the activation energies in the initial and final stages of the thermal decomposition reactions of solid fuels. Compared to the Gaussian distribution, the logistic distribution is slightly thicker at the curve tail and suits better to describe the activation energy distribution. In this work, a theoretical analysis of the double logistic DAEM for the thermal decomposition kinetics of solid fuels has been systematically investigated. After the derivation of the double logistic DAEM, its numerical calculation method and the physical meanings of the model parameters have been presented. Three typical types of simulated double logistic DAEM processes have been obtained according to the overlapped situation of two derivative conversion peaks, namely separated, overlapped and partially overlapped processes. It is found that, for the partially overlapped process, the form of the minor peak (overlapped peak or peak shoulder) depends on the values of the frequency factor and heating rate. Considering the simulated processes and related examples from literature, the double logistic DAEM has been remarked as a more reliable tool with abundant flexibility to explain the thermal decomposition of various solid fuels. More accurate results are expected if the double logistic DAEM is coupled with the computational fluid dynamics (CFD) simulation for those reactions mentioned above.
7817-7825
Dong, Zhujun
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Yang, Yang
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Cai, Wenfei
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He, Yifeng
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Chai, Meiyun
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Liu, Biaobiao
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Yu, Xi
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Banks, Scott W.
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Zhang, Xingguang
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Bridgwater, Anthony V.
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Cai, Junmeng
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13 June 2018
Dong, Zhujun
2d1b6a22-68c9-4439-98a1-9ac182d92ead
Yang, Yang
4f250291-4405-49b3-a662-eb9810e00415
Cai, Wenfei
e86283fa-11d5-4c91-a6ae-4c317649465d
He, Yifeng
538895e7-b946-45bc-9391-c3dacb0aa425
Chai, Meiyun
1daa6ce6-e557-456d-b5cc-ea3e98dd8538
Liu, Biaobiao
2f88400c-94df-442d-be39-988bc9f079cd
Yu, Xi
7e4f553f-cc11-4c6e-ad6d-9fb5c3c07a60
Banks, Scott W.
a2fa7f01-1518-4014-9ddb-5793559a37d8
Zhang, Xingguang
98a45d36-518b-4f6f-ac05-b47b277ddc10
Bridgwater, Anthony V.
0bb8f904-9940-4063-a29c-4b8c006786b1
Cai, Junmeng
9e5ac5c2-f617-4571-a0f5-687670340568
Dong, Zhujun, Yang, Yang, Cai, Wenfei, He, Yifeng, Chai, Meiyun, Liu, Biaobiao, Yu, Xi, Banks, Scott W., Zhang, Xingguang, Bridgwater, Anthony V. and Cai, Junmeng
(2018)
Theoretical analysis of double logistic distributed activation energy model for thermal decomposition kinetics of solid fuels.
Industrial and Engineering Chemistry Research, 57 (23), .
(doi:10.1021/acs.iecr.8b01527).
Abstract
The distributed activation energy model (DAEM) has been widely used to analyze the thermal decomposition of solid fuels such as lignocellulosic biomass and its components, coal, microalgae, oil shale, waste plastics, and polymer etc. The DAEM with a single distribution of activation energies cannot describe those reactions well because the thermal decomposition normally involves multiple subprocesses of various components. The double DAEM employs a double distribution to represent the activation energies. The Gaussian distribution is usually used to represent the activation energies. However, it is not sufficiently accurate for addressing the activation energies in the initial and final stages of the thermal decomposition reactions of solid fuels. Compared to the Gaussian distribution, the logistic distribution is slightly thicker at the curve tail and suits better to describe the activation energy distribution. In this work, a theoretical analysis of the double logistic DAEM for the thermal decomposition kinetics of solid fuels has been systematically investigated. After the derivation of the double logistic DAEM, its numerical calculation method and the physical meanings of the model parameters have been presented. Three typical types of simulated double logistic DAEM processes have been obtained according to the overlapped situation of two derivative conversion peaks, namely separated, overlapped and partially overlapped processes. It is found that, for the partially overlapped process, the form of the minor peak (overlapped peak or peak shoulder) depends on the values of the frequency factor and heating rate. Considering the simulated processes and related examples from literature, the double logistic DAEM has been remarked as a more reliable tool with abundant flexibility to explain the thermal decomposition of various solid fuels. More accurate results are expected if the double logistic DAEM is coupled with the computational fluid dynamics (CFD) simulation for those reactions mentioned above.
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e-pub ahead of print date: 25 May 2018
Published date: 13 June 2018
Additional Information:
Funding Information:
Financial support from UK Global Challenges Research Fund (GCRF) Networking Grant (project title: Pyrolysis of Municipal Organic Waste for Renewable Road Construction Materials) is greatly acknowledged. Md. Maksudur Rahman, a master student from Biomass Energy Engineering Research Center, School of Agriculture and Biology, Shanghai Jiao Tong University, is greatly acknowledged for his valuable suggestions about language.
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Local EPrints ID: 481902
URI: http://eprints.soton.ac.uk/id/eprint/481902
ISSN: 0888-5885
PURE UUID: ad23e7f2-753b-45be-873b-a5e3043abdc6
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Date deposited: 12 Sep 2023 17:00
Last modified: 06 Jun 2024 02:19
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Author:
Zhujun Dong
Author:
Yang Yang
Author:
Wenfei Cai
Author:
Yifeng He
Author:
Meiyun Chai
Author:
Biaobiao Liu
Author:
Xi Yu
Author:
Scott W. Banks
Author:
Xingguang Zhang
Author:
Anthony V. Bridgwater
Author:
Junmeng Cai
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