Microcracking evolution and clustering fractal characteristics in coal failure under multi step and cyclic loading

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During the deep mining process, coal mass encounter intricate geo-environmental stress, such as periodic weighting loading and repeatedly excavation unloading–reloading cycles, which weakens coal’s mechanical integrity and predisposing it to severe coalburst accidents. To investigate the microcracking damage mechanisms and predictive indicators in coal failure under in-situ stress analogs, the multistage step and cyclic loading experiments are conducted on cubic coal specimens. Acoustic emission (AE) technology is employed to track the spatiotemporal-energy evolution of stress-induced damages and discern the microcracking nature through AF/RA assessments, and the power-law scaling relation of AE activity near the catastrophic failure of coal is investigated. Then the clustering fractal structures of microcracking events in the stressed coal are quantified across temporal, spatial and energetic domains, utilizing correlation integral methodologies and b-value derivations from magnitude-frequency relation. Findings indicate that irrespective of the loading mode (step or cyclic), escalating stress triggers an intensification of irreversible fatigue deformations. AE characteristic parameters manifest a gradual rise, culminating in a precipitous peak coinciding with the critical failure point. This escalation adheres to a power-law correlation between AE occurrence frequency and time to failure, observable in the immediate pre-failure seconds, reflecting a universal attribute of coal fracture. Prior to ultimate failure, a marked increase in shear microcracks is discernible, despite tensile-dominated cracks (constituting about 80 % of total microcracks) prevailing as inferred from the variation of AF/RA values, aligning with an inferred “X” conjugate wedge splitting pattern from AE event density and energy mapping. The microcracking events in the loaded coal exhibit a clustering fractal structure that spans across temporal, spatial, and energetic (or magnitude) domains. Notably, the temporal fractal dimension, spatial fractal dimension, and b-value (i.e., a parameter characterized the energetic fractal dimension) all follow a parallel decrease pattern as the loading stress escalates, with a pronounced diminution becoming especially evident as the specimen approaches its catastrophic failure threshold. This insight offers fresh perspectives for predicting rock/coal dynamic disasters, emphasizing the necessity of concurrently monitoring the shift from diffuse microcracking to localized failure across time, space and energy domains. These research findings contribute to a deeper understanding of microcracking damage evolution and failure mechanism of loaded coal, and provide a foundational basis for early warning of rock failure such as the coalburst disasters.