Prediction of top-coal caving and drawing characteristics by the analytic hierarchy process-fuzzy discrimination method in extra-thick coal seams

The cavability assessment of thick coal seams, which contain over half of the world coal reserves, is quite topical. However, assessment of top-coal caving and drawing characteristics (CDC) in extra-thick (over 20m) coal seams are addressed in scarce publications, due to the problem intricacy. In this study, the analytic hierarchy process (AHP)-fuzzy discrimination method is proposed for the top-coal CDC analysis as applied to extra-thick coal seam of the Laosangou mine field in China. For the AHP model elaboration, six factors were selected as secondary indicators, namely: coal burial depth, coal seam strength, caving ratio, fractures, roof conditions, gangues; whereas 13 more factors, including mechanical mining height, water absorption rate, porosity, etc., were used as tertiary indicators. For verification, this method was applied to the case studies of Tashan and Tongxin mines in China, for which the top-coal CDC calculations were made using the available experimental data under 36 particular conditions. The latter involved various combinations of caving ratios, gangue positions, and thickness values. The calculated results strongly indicate that the mechanical mining height and gangue position are the influencing factors controlling the top-coal CDC, as well as revealed certain particular patterns of their effect. Moreover, partitioning of the first mining area was performed based on the mechanical mining height criterion. This article successfully combines the fuzzy theory with mining engineering, which possesses high application prospects and academic merits.