TGA/DSC study to characterise and classify coal seams conforming to susceptibility towards spontaneous combustion

Thermogravimetric analysis/differential scanning calorimeter (TGA/DSC) technique along with basic coal characteristics study is carried out for eighty coal samples of Indian coalfields, to determine spontaneous combustion propensity behaviour of coal. TGA study of coal samples indicates that there is an increase in the mass of coal samples in the temperature range 150-350 degrees C, which may be due to oxygen adsorption and absorption. The correlation and principal component analysis states that the component of proximate analysis (M-ad, V-Md, FR, and VR) have an acceptable correlation with the TGA experiments results i.e., T-gsh and T-gign. Multiple fixed nonlinear regression analysis shows that thermogravimetry (TG) experiment results T-gign may be the best index to categorise/classify the coal as per their susceptibility towards spontaneous combustion. The authors proposed four groups of classification as per their propensity towards spontaneous combustion depending upon the moisture (M-ad), volatile matter (VMd), and TG ignition temperature from differential thermogravimetric (DTG) curve (T-gign) using hierarchal clustering analysis. The coal samples of different seams from Indian coalfield may be classified into four different clusters, viz. very highly/extremely susceptible (T-gign < 260 degrees C), highly susceptible (260 degrees C <= T-gign <= 290 degrees C), moderately susceptible (290 degrees C <= T-gign <= 320 degrees C), and poorly susceptible (T-gign > 320 degrees C). The field observations and TGA/DSC experiment results with the following statistical analysis substantiate a similar assessment. (C) 2021 Published by Elsevier B.V. on behalf of China University of Mining & Technology.

Automated summary

Thermogravimetric analysis and differential scanning calorimeter (TGA/DSC) technique were used to study the spontaneous combustion propensity behavior of coal samples from Indian coalfields. The results showed an increase in mass in the temperature range of 150-350 degrees C, which could be attributed to the adsorption and absorption of oxygen. Correlation and principal component analysis indicated a good correlation between the proximate analysis components and TGA experimental results. Multiple fixed nonlinear regression analysis suggested that the T-gign parameter derived from TG experiments may be the best indicator for classifying coal samples based on their susceptibility to spontaneous combustion. Hierarchical clustering analysis was used to classify the coal samples into four groups based on moisture, volatile matter, and TG ignition temperature. Field observations and statistical analysis supported this classification. (C) 2021 Published by Elsevier B.V. on behalf of China University of Mining & Technology.