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Rock Mechanics and Rock Engineering

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26.09.2018 | Original Paper

Computational Modelling of Groundwater Inflow During a Longwall Coal Mining Advance: A Case Study from the Shanxi Province, China

verfasst von: Yuedu Chen, A. P. S. Selvadurai, Weiguo Liang

Erschienen in: Rock Mechanics and Rock Engineering | Ausgabe 3/2019

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Abstract

The paper investigates groundwater inflow into a longwall working face of the Xiegou Coal Mine located in the northwest of the Shanxi province, China. Three modelling approaches, including basic Darcy modelling, full poroelastic modelling using Biot’s classical theory, and the full Biot poroelastic modelling that takes into account permeability alterations of the coal seam and strata due to alterations in the mining-induced stress state, are used to estimate the fluid flow into the underground longwall coal mine as the excavation progresses. Based on plausible assumptions of hydrogeological structure, boundary conditions and mining conditions, a three-dimensional finite element model of the simplified geological setting is developed using the COMSOL software. The permeability changes in both the strata and the coal seam due to the mining are associated with the mining-induced stress changes and water pressure, and the correlation between them accords with the exponential relationship. The differences in the modelling results of three approaches were analyzed, and the simulation results are compared with the field measurements.

Vorheriger Artikel Excavation Optimization and Stability Analysis for Large Underground Caverns Under High Geostress: A Case Study of the Chinese Laxiwa Project

Nächster Artikel An Innovative Sampling Method for Determining the Scale Effect of Rock Joints

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Titel: Computational Modelling of Groundwater Inflow During a Longwall Coal Mining Advance: A Case Study from the Shanxi Province, China
verfasst von: Yuedu Chen
A. P. S. Selvadurai
Weiguo Liang
Publikationsdatum: 26.09.2018
Verlag: Springer Vienna
Erschienen in: Rock Mechanics and Rock Engineering / Ausgabe 3/2019
Print ISSN: 0723-2632
Elektronische ISSN: 1434-453X
DOI: https://doi.org/10.1007/s00603-018-1603-1

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