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

Autor(en): ORCID
ORCID
ORCID
ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Advances in Civil Engineering, , v. 2021
Seite(n): 1-14
DOI: 10.1155/2021/3731124
Abstrakt:

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.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10625395
  • Veröffentlicht am:
    26.08.2021
  • Geändert am:
    17.02.2022
 
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