Key Takeaways & Executive Findings
- •• Coal damage exhibits heterogeneous evolutionary characteristics under mining-induced stress, with the proposed damage characterization equation effectively determining critical damage thresholds based on irreversible deformation theory. • The three-parameter EXP function model is more suitable for characterizing the time-dependent damage process of coal under mining-induced stress. • A new characterization method for the coal brittleness evaluation index reveals an 800 m burial depth boundary for the coal brittleness index. • At the microscopic level, quantitative characterization of the correlation between peak stress and the average reduction in functional groups during mining-induced failure of coal at different burial depths is achieved, establishing a mapping relationship between laboratory parameters and field monitoring indicators for early warning of dynamic disasters.
Abstract
Current quantitative characterization methods for the mechanical response and damage evolution of coal seams at different burial depths under mining-induced stress remains insufficient. To address this, this study establishes a quantitative characterization model for the evolution of mechanical properties in gas-bearing coal masses at varying burial depths. It innovatively introduces a dual damage quantification technique and develops a coupled damage evolution model that comprehensively considers energy evolution, effective mining-induced stress, permeability, and a damage sensitivity coefficient, followed by extensive analysis. Key findings include: coal damage exhibits heterogeneous evolutionary characteristics under mining-induced stress; based on the theory of irreversible deformation, the proposed damage characterization equation can effectively determine the critical damage threshold of coal; the three-parameter EXP function model is more suitable for characterizing the time-dependent damage process of coal under mining-induced stress; a new characterization method for the coal brittleness evaluation index is proposed, revealing an 800 m burial depth boundary for the coal brittleness index; at the microscopic level, achieving quantitative characterization of the correlation between peak stress and the average reduction in functional groups during mining-induced failure of coal at different burial depths. Finally, the mapping relationship between laboratory experimental parameters and field monitoring indicators for early warning of coal mine dynamic disasters is established.
1. Introduction
With the accelerated advancement of global industrialization, shallow mineral resources are increasingly unable to meet the rapidly growing demand, driving an irreversible shift in extraction focus toward the deep crust. This transition represents both a technology-driven industrial upgrade and an imperative response to an impending resource crisis [1,2]. The global field of deep rock engineering has shown a 'practice-led, theory-catch-up' development dynamic, which fundamentally reflects the intrinsic tension between the complexity of geological media and the urgency of engineering demands.
In deep mining operations, the physico-mechanical behavior of rock masses changes substantially with depth. In this context, mining-induced stress is a primary conduit for external energy input, yet its influence on coal damage and failure mechanisms remains markedly uncertain [3]. The evolution of the stress field induced by mining exhibits significant triple-coupling characteristics of 'method-path-depth'. This nonlinear relationship between 'process disturbance-geological response' has prompted a paradigm shift in deep-coal-mining safety control from traditional 'strength theory' toward 'whole-process energy regulation and control' [4,5]. In deep coal mining, improperly controlled mining-induced stresses can readily trigger dynamic hazards (e.g., rockbursts or coal bursts), endangering personnel and causing severe infrastructure damage [6]. For a long time, traditional constitutive models, elastoplastic theory, and limit-equilibrium theory have been widely applied in rock engineering; however, these frameworks have shown clear limitations when confronted with the complex conditions of deep coal bodies.
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WANG Zeqi, YUAN Liang, HU Bin, LI Bo, HUANG Laisheng (2025). Quantitative calibration method for the evolution of mechanical properties of gas-containing coal under mining-induced stress and microscopic failure evaluation. SinoTechIntel Verified Research. https://doi.org/10.1016/j.ijmst.2025.12.013
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Frequently Asked Questions
What is the main objective of this study?
The study aims to establish a quantitative characterization model for the evolution of mechanical properties in gas-bearing coal masses at varying burial depths under mining-induced stress, introducing a dual damage quantification technique and a coupled damage evolution model.
What are the key findings regarding coal damage under mining-induced stress?
Coal damage exhibits heterogeneous evolutionary characteristics, and the proposed damage characterization equation can effectively determine the critical damage threshold based on irreversible deformation theory. The three-parameter EXP function model is more suitable for characterizing time-dependent damage.
How does the study contribute to the evaluation of coal brittleness?
A new characterization method for the coal brittleness evaluation index is proposed, revealing an 800 m burial depth boundary for the coal brittleness index.
What is the significance of the microscopic failure evaluation?
At the microscopic level, the study achieves quantitative characterization of the correlation between peak stress and the average reduction in functional groups during mining-induced failure, establishing a mapping relationship between laboratory parameters and field monitoring indicators for early warning of dynamic disasters.
What is the practical application of this research?
The research provides a quantitative basis for early warning of coal mine dynamic disasters by linking laboratory experimental parameters to field monitoring indicators, thereby enhancing safety in deep coal mining.
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