Frontiers in Physics (Aug 2020)

Coal Mine Abutment Pressure Distribution Based on a Strain-Softening Model

  • Ang Li,
  • Ang Li,
  • Qiang Ma,
  • Qiang Ma,
  • Li Ma,
  • Li Kang,
  • Qian Mu,
  • Jianbo Chen

DOI
https://doi.org/10.3389/fphy.2020.00263
Journal volume & issue
Vol. 8

Abstract

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The coal in front of the mining face presents strain softening deformation characteristics. An analytical model is proposed to simulate the abutment pressure distribution over the coal in front of the mining face under elastic and inelastic conditions. A new theoretical formula is derived from calculating the abutment pressure distribution and its width in elastic and inelastic regions of the coal under the limit equilibrium condition. The influences of UCS, residual strength, mining height, softening modulus, and deformation angle on the abutment pressure distribution are discussed. The study results show that (1) the stress gradient in the plastic area is larger than that in the crushed zone; (2) the width of the plastic region is independent of the peak abutment pressure, but it is dependent on UCS, residual strength, mining height, softening modulus, and deformation angle; (3) the width of the crushed zone in the inelastic area is closely related to the peak abutment pressure, coal-floor interface cohesion, and friction coefficient; (4) the width of the elastic zone is dependent on the mining height, coefficient of horizontal pressure, coal-floor interface friction coefficient, and peak abutment pressure, where the coefficient of horizontal pressure has the highest impact, in that the width of the elastic zone undergoes logarithmic decrease with the increase in the coefficient of horizontal pressure. A case study was carried out at longwall panel 07 of No. 5 coal seam in Dongjiahe Coal Mine to verify the analytical model. The abutment pressure distribution and the widths of the elastic and inelastic zones under the limit equilibrium condition are calculated based on the relevant parameters. The theoretical results are compared with the field monitoring data and show a very good fit. It is proved that the proposed analytical model has high accuracy, and the feasibility of the model is verified. The study results can provide guidance for similar engineering applications.

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