A comprehensive risk assessment method for coal and gas outburst in underground coal mines based on variable weight theory and uncertainty analysis

Coal and gas outburst is one of the main disasters that seriously affect the underground safety production of coal. It is crucial to accurately assess the risk level of coal seam outbursts under different conditions and take effective prevention and control measures to avoid the occurrence of such disasters. To solve this problem, a new assessment method combining variable weight theory and unascertained theory is proposed. Based on qualitative and quantitative risk factors, eight indicators and four classification criteria are constructed. The constant weights (CW) are determined by the fuzzy analytic hierarchy process, while the variable weights (VW) of different parameters by constructing a partitioned variable weight model through the VW theory. Meanwhile, four membership functions of linear (L), parabolic (P), S, and Weibull (W) are proposed to measure the uncer-tainty level of risk. Based on the calculation of 45 sets of sample data, the differences between the maximum membership principle and the confidence criterion in risk identification were considered, and the optimal hybrid model for the risk evaluation of underground coal seam outburst was derived as VW-P-M. The reliability of the model was determined by further validation of the field data. Finally, the limitations of traditional identification approach are analyzed and the stability of the model under various indicators changes is examined with global sensitivity analysis (GSA). The model fully considers the uncertainty in the outburst risk assessment and the influence of index parameters change on the weight. In addition, it can well solve the risk misjudgment problem caused by low indicators parameters in the production process, providing a reasonable idea and method for the accurate assessment of outburst risk in the early stage of coal mining.