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Journal of the Southern African Institute of Mining and Metallurgy

On-line version ISSN 2411-9717
Print version ISSN 2225-6253

Abstract

ONIFADE, M.  and  GENC, B.. Prediction of the spontaneous combustion liability of coals and coal shales using statistical analysis. J. S. Afr. Inst. Min. Metall. [online]. 2018, vol.118, n.8, pp.799-808. ISSN 2411-9717.  http://dx.doi.org/10.17159/2411-9717/2018/v118n8a2.

In this study we investigate the intrinsic factors influencing the propensity of coals and coal shales to undergo spontaneous combustion using statistical analysis. The intrinsic properties were determined by testing 14 in situ bituminous coals and 14 coal shales from the Witbank coalfield, South Africa. The relationships between these intrinsic properties (obtained from proximate and ultimate analysis) and spontaneous combustion liability indices (the Wits-Ehac Index and the Wits-CT Index) were established using linear and multiple regression analysis based on set criteria. The linear regression analyses indicate that moisture, volatile matter, ash, carbon, hydrogen, and nitrogen contents are the main factors affecting the spontaneous combustion liability of coals, while moisture, volatile matter, ash, carbon, hydrogen, nitrogen and total sulphur contents are the factors affecting the spontaneous combustion liability of coal shales. The regression analysis shows either a positive or a negative correlation coefficient between the intrinsic factors and the spontaneous combustion liability index. Multiple regression of the spontaneous combustion liability index on eight independent variables was used to develop acceptable and reliable predictive models as indicated by high R-squared values, high correlation coefficients, and low standard error of estimates. The use of the models derived from this study may enable the spontaneous combustion liability of coals and coal shales to be reliably predicted.

Keywords : spontaneous combustion; coal; coal shale; statistical analysis; Wits-Ehac Index; Wits-CT Index.

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