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CLC number: TK16

On-line Access: 2012-05-04

Received: 2011-08-18

Revision Accepted: 2012-01-17

Crosschecked: 2012-04-04

Cited: 3

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Journal of Zhejiang University SCIENCE A 2012 Vol.13 No.5 P.344-352


Non-linear relationship between combustion kinetic parameters and coal quality

Author(s):  Jian-guo Yang, Xiao-long Zhang, Hong Zhao, Li Shen

Affiliation(s):  State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   zhaohong@zju.edu.cn

Key Words:  Kinetic parameter, Coal property, Thermo-gravimetry (TG), Support vector regression machine (SVR), Differential evolution

Jian-guo Yang, Xiao-long Zhang, Hong Zhao, Li Shen. Non-linear relationship between combustion kinetic parameters and coal quality[J]. Journal of Zhejiang University Science A, 2012, 13(5): 344-352.

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author="Jian-guo Yang, Xiao-long Zhang, Hong Zhao, Li Shen",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Non-linear relationship between combustion kinetic parameters and coal quality
%A Jian-guo Yang
%A Xiao-long Zhang
%A Hong Zhao
%A Li Shen
%J Journal of Zhejiang University SCIENCE A
%V 13
%N 5
%P 344-352
%@ 1673-565X
%D 2012
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1100232

T1 - Non-linear relationship between combustion kinetic parameters and coal quality
A1 - Jian-guo Yang
A1 - Xiao-long Zhang
A1 - Hong Zhao
A1 - Li Shen
J0 - Journal of Zhejiang University Science A
VL - 13
IS - 5
SP - 344
EP - 352
%@ 1673-565X
Y1 - 2012
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1100232

Combustion kinetic parameters (i.e., activation energy and frequency factor) of coal have been proven to relate closely to coal properties; however, the quantitative relationship between them still requires further study. This paper adopts a support vector regression machine (SVR) to generate the models of the non-linear relationship between combustion kinetic parameters and coal quality. Kinetic analyses on the thermo-gravimetry (TG) data of 80 coal samples were performed to prepare training data and testing data for the SVR. The models developed were used in the estimation of the combustion kinetic parameters of ten testing samples. The predicted results showed that the root mean square errors (RMSEs) were 2.571 for the activation energy and 0.565 for the frequency factor in logarithmic form, respectively. TG curves defined by predicted kinetic parameters were fitted to the experimental data with a high degree of precision.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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