Abstract
Exploring the mechanism of coal dust explosions is essential for the development of safety techniques to prevent coal dust explosions. An explosion index can be used to estimate explosion severity. In this study, the moisture content pa- rameter, one of the intrinsic characteristics of coal dust, was used to estimate the explosion index. For this purpose, 32 samples of coal with different moisture content were collected from different mines in Iran and were prepared as coal rounds. The coal dust explosion process was carried out in a 2-litre closed chamber. After determining the most impor- tant and influential parameters, prediction models of the explosion index were presented using linear regression. For this purpose, 75 percent of data was randomly assigned for training and 25 percent of data was used for testing and vali- dation. The performance of these models was assessed through the root mean square error (RMSE), the proportion of variance accounted for (VAF), the mean absolute percentage error (MAPE) and the mean absolute error (MAE). Then the results of the laboratory method were compared with the results of the regression model. The results show that there is a good correlation between the laboratory results and the predictive model obtained through linear regression analysis.
Highlights
Coal floating dust is always produced in different locations of underground coal mines (Li et al, 2018a; Hu et al, 2010)
75 percent of data was randomly assigned for training and 25 percent of data was used for testing and validation. The performance of these models was assessed through the root mean square error (RMSE), the proportion of variance accounted for (VAF), the mean absolute percentage error (MAPE) and the mean absolute error (MAE)
The results show that there is a good correlation between the laboratory results and the predictive model obtained through linear regression analysis
Summary
Coal floating dust is always produced in different locations of underground coal mines (Li et al, 2018a; Hu et al, 2010). A coal dust explosion is usually triggered by a gas explosion (Zhang et al, 2009) This is known as the domino effect and is shown in Figure 1 (Cao et al, 2017). Kucuk et al, (2003) investigated the effect of moisture and particle size on the spontaneous combustion of coal. Evaluation of the effect of the moisture content of coal dust on the prediction of the coal dust explosion index sensitivity. Yuan et al (2014) studied the humidity of the three coal dust particle sizes According to their results, the maximum explosion pressure decreases sharply with an increasing humidity curve turning point. The effect of moisture content of coal dust has been investigated on the explosion index of coal dust
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
