## 1 Introduction
Advances in acoustic emission (AE) monitoring technology have enabled its widespread adoption in rock mechanics testing, leveraging its capabilities in damage localization and nondestructive sample monitoring [28]. Importantly, integrating AE measurements with mechanical loading and real-time CT scanning allows for spatiotemporal cross-validation of monitoring methods, maximizing the reliability of rock failure test results. Qualitative studies on mudstone failure processes [29] have demonstrated the feasibility of synchronous real-time CT and AE monitoring in rock mechanics research. Regrettably, current research lacks integration of mesostructural information derived from CT scans and AE signals. Presently, multisource monitoring data (e.g., CT, AE) lack integrated analysis [11], and synergy mechanisms during fracture processes remain unexplored. This deficiency significantly impedes structural damage and fracture prediction capabilities. Addressing this challenge, this study proposes an integrated approach combining real-time CT imaging [30] and AE monitoring [31] to quantify and visualize self-organized criticality in heterogeneous rock fracture processes. Traditional fracture theories (e.g., Griffith theory) [32] and failure criteria (e.g., Coulomb criterion) [33] overlook material internal disorder and precursory failure phenomena [34]. Such theories typically assume catastrophic global failure with a first-order phase transition from intact to failed states. Notably, natural rock heterogeneity profoundly impacts damage evolution [35; 36], especially strength variability and associated size effects [37]. Prior research conceptualized crack quasistatic propagation in heterogeneous rocks as a dynamic critical transition [6]. Experimental observations reveal that increasing strain/fracture rate induces power-law scaling of critical parameters--including energy release, damage scales, and maximum damage area--in rock specimens at failure thresholds [35; 38; 39]. Criticality concepts provide a framework for interpreting failure transitions and associated characteristics in heterogeneous rocks [40; 41]. Classical models exhibit significant shortcomings in interpreting/predicting damage processes in highly disordered rocks. Indeed, rock failure progresses through distinct precursor stages: microcrack nucleation, propagation, coalescence, and eventual macroscopic failure [42]. Damage precursor concepts have been applied to natural hazard forecasting (e.g., earthquakes; landslides; mine collapses; volcanic eruptions; rockburst) [43; 44; 45; 46; 47]. Heterogeneous media failure characteristics have been extensively validated through power-law analyses [48; 49], critical state theory [50], mechanical modeling [51], failure mechanism studies [52], and engineering applications [53]. Critical limitations remain: (1) precise identification of failure transition points; (2) incomplete understanding of self-organization-to-criticality transitions; (3) absence of methods for spatiotemporal-energy prediction during failure. To address the critical limitations outlined above, this study established an integrated testing platform employing sandstone specimens. Synchronized AE monitoring and X-ray CT scanning were conducted during compression experiments. Internal structural evolution and damage parameters of sandstone were systematically characterized, enabling detailed analysis of self-organized processes and critical phase transitions during progressive fracturing. Building on self-organized criticality (SOC) characteristics and phase transition predictions, we explored the application of self-organized damage processes for failure prediction in unstable stages. Key investigations include: (1) characterization of self-organized processes and critical points in sandstone damage evolution; (2) clarification of evolutionary principles governing damage self-organized criticality; (3) mechanistic interpretation of failure instabilities through self-organized critical phase transitions.