Investigation on instability mechanism and control of abandoned roadways in coal pillars recovery face: A case study

Abstract

The abandoned roadways (ARs) in front of the longwall face catastrophic instability will seriously hamper mining progress, which is a complicated process related to the stress environment, the roadway section, and the mechanical properties of the surrounding rock. The cusp catastrophe theory is employed to establish a state identification model for the irregular coal pillar-roof system (CPRS) formed by the ARs and re-mining entries. To begin, the state discrimination equation (Δp) for the gradual CPRS is derived, and the critical value at which the system transitions into an unstable state under quasi-static conditions is determined. The results indicated that when 16.49 m ≤ L ≤ 22.63 m (L denotes the equivalent span of the intersection roof) and 0 < R_e ≤ 2.61 m (R_e denotes the width of the elastic zone within the triangular coal pillar), the triangular CPRS is inherently unstable. Similarly, for trapezoidal CPRS configurations where the length L_m (the span of the right-angled trapezoid roof in the propulsion direction) varies from 4.0 to 12.60 m, the system is unstable as well. Subsequently, the model was further enhanced by accounting for the impact of the P_c (advance stress increment load), where a critical criterion for the catastrophic instability of the CPRS was proposed, which represented the external energy required to transition the CPRS from an unstable state to catastrophic instability in different mining stages. After that, the stability degree of the irregular coal pillar was categorized, and a coupling zoning control technology was applied to CPR operations. Field monitoring results demonstrated the effectiveness of the zoning control technology, providing valuable guidance for similar mining practices.

Keywords

Abandoned roadways / Instability mechanism / Cusp catastrophe theory / Pier column support / Hydraulic fracture

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Dong Zhang: Writing - review & editing, Writing - original draft. Jianbiao Bai: Writing - review & editing, Supervision, Funding acquisition, Conceptualization. Rui Wang: Validation, Methodology, Funding acquisition. Min Deng: Visualization, Software, Data curation. Shui Yan: Methodology, Investigation, Formal analysis. Qiancheng Zhu: Writing - original draft, Software, Methodology. Hao Fu: Software, Investigation, Data curation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

The authors are thankful to the financial support from the Major Project of Regional Joint Foundation of China (Grant No. U21A20107), the Natural Science Foundation of China (Grant No. 52074239), Xinjiang Uygur Autonomous Region Key R&D Project Task Special - Department and Department Linkage Project (Grant No. 2022B01051), and the Xinjiang Uygur Autonomous Region Tianchi Introduction Plan (Grant No. 2024XGYTCYC03).

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