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A Case Study of Optimization and Application of Soft-Rock Roadway Support in Xiaokang Coal Mine, China

Auteur(s): ORCID
ORCID
ORCID
ORCID
Médium: article de revue
Langue(s): anglais
Publié dans: Advances in Civil Engineering, , v. 2021
Page(s): 1-14
DOI: 10.1155/2021/3731124
Abstrait:

The roadway of S2S2 fully mechanized caving face (FMCF) in Xiaokang Coal Mine is one of the most typical deep-buried soft-rock roadways in China and had been repaired several times. In order to figure out the failure reasons of the original roadway support, the geological conditions were investigated, the surrounding rock stress was monitored, the rib displacement, roof separation, and floor heave were in situ measured, and the performance of the U-shaped steel support was simulated. The above analysis results indicated that the support failure was mainly caused by (1) the unreasonable arch roadway section, (2) the high and complex surrounding rock stress, (3) the failure control of the floor heave, and (4) the inadequate self-supporting capacity of the surrounding rock. For optimizing, the roadway section was changed to circle and a new full-section combined support system of “belt-cable-mesh-shotcrete and U-shaped steel-filling behind the support” was adopted, which could specifically control the floor heave, allow the roadway deformation in control, and improve the self-supporting ability and stress field of the surrounding rock. To determine the support parameters, the selected U-shaped steel support was verified by simulation, and various bolt-cable support schemes were simulated and compared. Finally, such an optimized support scheme was applied in the roadway of the next replacement FMCF. The in situ monitoring showed that the rib-to-rib convergence and roof-to-floor convergence were both controlled within 600 mm, which indicated that the roadway was effectively controlled. This case study has important reference value and guiding function for the optimal design of the soft-rock roadway support with similar geological conditions.

Copyright: © 2021 Shuai Guo et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10625395
  • Publié(e) le:
    26.08.2021
  • Modifié(e) le:
    17.02.2022
 
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