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Pyrolysis of Medium Density Fibreboard: Optimized Search for Kinetics Scheme and Parameters via Genetic Algorithm Driven by Kissinger's Method
Li K 1 * #,Huang X 2,Fleischmann C M 3,Rein G 2,Ji J 4
1.State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230027
2.Department of Mechanical Engineering, Imperial College London, London SW7 2AZ
3.Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch 8140
4.State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230027
*Correspondence author
#Submitted by
Subject:
Funding: 安徽省自然科学基金资助项目（No.1408085QE93）, 高等学校博士学科点专项科研基金资助课题（No.20133402120009）
Opened online: 5 August 2014
Accepted by: none
Citation: Li K,Huang X,Fleischmann C M.Pyrolysis of Medium Density Fibreboard: Optimized Search for Kinetics Scheme and Parameters via Genetic Algorithm Driven by Kissinger's Method[OL]. [ 5 August 2014] http://en.paper.edu.cn/en_releasepaper/content/4605025
 
 
The pyrolysis kinetics of charring materials plays an important role in understanding material combustions especially for constructions materials with complex degradation chemistry. Thermogravimetric analysis (TGA) is frequently used to study the heterogeneous kinetics of solid fuels, however, there is no agreed method to determine the pyrolysis scheme and kinetic parameters for charring polymers with multiple components and competing reaction pathways. This study develops a new technique to estimate the possible numbers of species and sub-reactions in pyrolysis by analysing the second derivatives of TG (DDTG) curves. The pyrolysis of a medium density fibreboard (MDF) in nitrogen is studied in detail, and the DDTG curves are used to locate the temperature of peak mass-loss rate for each sub-reactions. Then, based on the TG data under multiple heating rates, the Kissinger's method is used to quickly find the possible range of values of the kinetic parameters (A and E). These ranges are used to accelerate the optimization of the inverse problem using genetic algorithm (GA) for the kinetic and stoichiometric parameters. The proposed method and the kinetic scheme found are shown to match the experimental data and are able to predict accurately results at different heating rate better than the Kissinger's method and faster than the regular GA search alone. The compensation effect and interdependence among kinetic parameters has been shown to weaken as the TG data available increases. Moreover, conducting TG experiment under multiple heating rates is crucial to obtain good kinetic parameters.
Keywords:fire engineering; pyrolysis; kinetics; thermogravimetry; optimization
 
 
 

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