The Effects of Caving of a Coal Mine’s Immediate Roof on Floor Strata Failure and Water Inrush

Abstract Mine water inrush is one of the important factors threatening safe production in mines. The accurate understanding of the mine groundwater flow field can effectively reduce the hazards of mine water inrush. Numerical simulation is an important method to study the groundwater flow field. This paper numerically simulates the groundwater seepage field in the GaoSong ore field. In order to ensure the accuracy of the numerical model, the research team completed 3,724 field fissure measurements in the study area. The fracture measurement results were analyzed using the GEOFRAC method and the whole-area fracture network data were generated. On this basis, the rock mass permeability coefficient tensor of the aquifer in the study area was calculated. The tensor calculation results are used in the numerical model of groundwater flow. After calculation, the obtained numerical model can better represent the groundwater seepage field in the study area. In addition, we designed three different numerical models for calculation, mainly to explore the influence of the tensor assignment of permeability coefficient on the calculation results of water yield of the mine. The results showed that irrational fathom tensor assignment would cause a significant deviation in calculation results.

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Soil-water inrush induced shield tunnel lining damage and its stabilization: A case study

Tunnelling and Underground Space Technology ◽

10.1016/j.tust.2020.103290 ◽

2020 ◽

Vol 97 ◽

pp. 103290 ◽

Cited By ~ 3

Author(s):

Linchong Huang ◽

Jianjun Ma ◽

Mingfeng Lei ◽

Linghui Liu ◽

Yuexiang Lin ◽

...

Keyword(s):

Soil Water ◽

Water Inrush ◽

Tunnel Lining ◽

Shield Tunnel

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Source identification of mine water inrush based on principal component analysis and grey situation decision

Environmental Earth Sciences ◽

10.1007/s12665-021-09459-z ◽

2021 ◽

Vol 80 (4) ◽

Author(s):

Qiding Ju ◽

Youbiao Hu

Keyword(s):

Principal Component Analysis ◽

Mine Water ◽

Source Identification ◽

Water Inrush ◽

Principal Component ◽

Component Analysis

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Evolution of delayed water inrush in fault fracture zone considering time effect

Arabian Journal of Geosciences ◽

10.1007/s12517-021-06469-w ◽

2021 ◽

Vol 14 (11) ◽

Author(s):

Jiwen Bai ◽

Shaolong Duan ◽

Rentai Liu ◽

Lin Xin ◽

Jiawei Tian ◽

...

Keyword(s):

Fracture Zone ◽

Water Inrush ◽

Time Effect ◽

Fault Fracture Zone

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Analysis of Tunnel Water Inrush Considering the Influence of Surrounding Rock Permeability Coefficient by Excavation Disturbance and Ground Stress

Applied Sciences ◽

10.3390/app11083645 ◽

2021 ◽

Vol 11 (8) ◽

pp. 3645

Author(s):

Helin Fu ◽

Pengtao An ◽

Long Chen ◽

Guowen Cheng ◽

Jie Li ◽

...

Keyword(s):

Permeability Coefficient ◽

Water Pressure ◽

Water Inrush ◽

Surrounding Rock ◽

Water Inflow ◽

Calculation Error ◽

External Water Pressure ◽

Ground Stress ◽

External Water ◽

Inflow Prediction

Affected by the coupling of excavation disturbance and ground stress, the heterogeneity of surrounding rock is very common. Presently, treating the permeability coefficient as a fixed value will reduce the prediction accuracy of the water inflow and the external water pressure of the structure, leading to distortion of the prediction results. Aiming at this problem, this paper calculates and analyzes tunnel water inflow when considering the heterogeneity of permeability coefficient of surrounding rock using a theoretical analysis method, and compares with field data, and verifies the rationality of the formula. The research shows that, when the influence of excavation disturbance and ground stress on the permeability coefficient of surrounding rock is ignored, the calculated value of the external water force of the tunnel structure is too small, and the durability and stability of the tunnel are reduced, which is detrimental to the safety of the structure. Considering the heterogeneity of surrounding rock, the calculation error of water inflow can be reduced from 27.3% to 13.2%, which improves the accuracy of water inflow prediction to a certain extent.

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