Research on the Self-Organized Criticality and Fracture Predictability of Sandstone via Real-Time CT Scanning and AE Monitoring

Progressive damage evolution in rock masses serves as the fundamental mechanism driving geological hazards by controlling deformation patterns and failure predictability. To address the critical challenge of predicting fracture behaviors in heterogeneous geological media, this study pioneers the integration of real-time computed tomography (CT) scanning and acoustic emission (AE) monitoring to investigate self-organized criticality and fracture predictability in Cretaceous sandstone under uniaxial compression. By systematically analyzing internal structural evolution and damage parameters, this established a multiparameter framework to characterize self-organized processes and critical phase transitions during progressive fracturing. Key findings include the following: (1) Distinct critical thresholds emerge during yield-stage self-organization, marked by abrupt transitions in AE signals and crack metrics—from microdamage coalescence initiating volumetric expansion (first critical point) to macrocrack nucleation preceding peak strength (second critical point). (2) AE-crack evolution follows power–law statistics, where elevated scaling exponents (r > 0.85) correlate with intensified nonlinear damage, accelerated localization, and progressive rate enhancement. Yield-stage power–law acceleration provides quantifiable failure precursors. (3) Yield-stage damage patterns exhibit 85% similarity with terminal failure configurations, confirming yield-stage as the definitive precursor with critical temporal signatures for failure prediction. A conceptual framework integrating multiparameter responses (AE signals, crack metrics) was developed to decipher self-organized critical phase transitions during deformation-failure processes. This work establishes methodological foundations for investigating damage mechanisms and predictive strategies in heterogeneous rock systems.