Analysis of the impact of physicochemical parameters characterizing coal mine waste on the initialization of self-ignition process with application of cluster analysis
The subject of the research presented in this paper is the analysis of physicochemical parameters characterizing coal mine waste, in terms of their impact on the initialization of the self-ignition phenomenon.
The model was constructed with the application of Hierarchical Cluster Analysis complemented with a colour data map enabling the tracing of similarities between the samples of coal mine waste in the space of parameters and between the examined physicochemical parameters in the space of samples. The data set analysed included parameters characterizing coal mine waste collected from 12 various coal mine waste dumps, either in operation or closed, and where thermal effects either took place or were not reported.
The HCA model constructed and complemented with a colour data map revealed that the tendency of coal mine waste to self-ignite is primarily affected by the contents of moisture, ash, volatile matter, C and S, values of heat of combustion, calorific value and contents of SiO2, Al2O3, K2O, SO3, TiO2, Co, Ni and Rb.
One of the major environmental hazards associated with the storage of coal mine waste is the possibility of self-ignition. At present, there are no applicable methods of assessment of this risk. The application of Hierarchical Clustering Analysis complemented with a colour data map enabled the analysis of data structures organized in matrix X(m x n) by tracing the similarities between the examined objects in the parameter space and between the measured parameters in the object space, and therefore contributed to the development of procedures of coal mine waste self-ignition risk assessment.
The originality of the study presented in this paper comes from finding the parameters affecting the tendency of coal mine waste to self-ignite.