Modelling spontaneous combustion liability of carbonaceous materials

作     者：M. Onifade B. Genc 

作者机构：The School of Mining Engineering University of the Witwatersrand Johannesburg 2050 South Africa 

出 版 物：《International Journal of Coal Science & Technology》 (国际煤炭科学技术学报（英文）)

年 卷 期：2018年第5卷第2期

页      面：191-212页

核心收录：

学科分类：081702[工学-化学工艺] 08[工学] 0817[工学-化学工程与技术] 

基　　金：This work was conducted in the context of coalshale spontaneous combustion in the Witbank coalfields South Africa and was financially sponsored by Coaltech.The authors wish to express gratitude to Coaltech and the staff of the selected coal mines for their supports.The work presented here is part of a Ph.D.research study in the School of Mining Engineering at the University of the Witwatersrand 

主　　题：Coals Coal-shales Statistical analysis Wits-Ehac Index Wits-CT Index Spontaneous combustion 

摘      要：This paper presents predictive models to determine spontaneous combustion liability of carbonaceous materials （coals and coal-shales） using statistical analysis. The intrinsic properties and spontaneous combustion liability index were determined by testing 14 coals and 14 coal-shales from Witbank coalfields, South Africa. The relationship between these intrinsic properties （obtained from proximate, ultimate and petrographic analysis） and spontaneous combustion liability indices （the Wits-Ehac Index and Wits-CT Index） were established. The influence of the intrinsic properties of coal-shales in relation to coal properties affecting spontaneous combustion has been established using a statistical method. The linear regression analysis indicates better linear relationships between some of the selected intrinsic properties and spontaneous combustion liability index and thus, identifies the major intrinsic factors affecting their liability toward spontaneous combustion. It was found that a definite positive or negative correlation coefficient exists between the intrinsic factors and spontaneous combustion liability. A set of models to predict the spontaneous combustion liability was derived. The best significant correlation along with the most appropriate model as indicated by R-squared values, the coefficient of corre- lations and standard error was used to predict the incident of spontaneous combustion.