Analysis of the Impact of Physicochemical Parameters Characterizing Coal Mine Waste on the Initialization of Self-Ignition Process with Application of Cluster Analysis
Author(s) -
Adam Smoliński
Publication year - 2014
Publication title -
journal of sustainable mining
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.623
H-Index - 17
eISSN - 2543-4950
pISSN - 2300-3960
DOI - 10.7424/jsm140306
Subject(s) - initialization , coal mining , coal , ignition system , tracing , coal combustion products , environmental science , waste management , combustion , engineering , computer science , chemistry , operating system , organic chemistry , programming language , aerospace engineering
PurposeThe 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.MethodsThe 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.ResultsThe 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.Practical implicationsOne 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 × 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.Originality/valueThe originality of the study presented in this paper comes from finding the parameters affecting the tendency of coal mine waste to self-ignite
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