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Quantitative Assessment of Rock Burst Risk in Roadway Tunneling Considering Variation of Coal Mass Parameters.
- Source :
- Applied Sciences (2076-3417); Sep2024, Vol. 14 Issue 18, p8211, 14p
- Publication Year :
- 2024
-
Abstract
- To investigate the influence of varied mechanical parameters of coal mass on rock burst occurrence during deep roadway tunneling, the surrounding coal and rock mass of a deep roadway were taken as the research objects. A geometric model of roadway tunneling was developed using 3DEC numerical simulation software, and the failure characteristics of the coal mass in the roadway side were analyzed based on the rock burst mechanism and stress difference gradient theory for deep mining. The risk of rock burst during roadway tunneling was quantitatively assessed using the change rate of the stress difference gradient (D<subscript>gc</subscript>), thereby elucidating the burst failure patterns of the deep roadway under the influence of varied mechanical parameters. The findings indicate that the coal mass in the roadway side zone is more prone to burst failure due to stress disturbances during deep excavation compared to the coal and rock mass in the roof and floor zones, and that the released kinetic energy and the risk of burst failure are positively correlated with the magnitude of the ground stress. The variation of the mechanical properties of coal mass has a significant effect on the rock burst risk during roadway tunneling. The variation of both internal friction angle and cohesion significantly affects rock burst, with cohesion exerting a greater influence. Conversely, the elastic modulus does not significantly impact the risk. The tendency of bursting in the coal mass is positively correlated with the coefficient of variation (COV) in cohesion and negatively correlated with the COV in internal friction angle. These research findings offer valuable insights for the quantitative assessment of rock burst risk during roadway tunneling. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20763417
- Volume :
- 14
- Issue :
- 18
- Database :
- Complementary Index
- Journal :
- Applied Sciences (2076-3417)
- Publication Type :
- Academic Journal
- Accession number :
- 180047594
- Full Text :
- https://doi.org/10.3390/app14188211