0
  • DE
  • EN
  • FR
  • Base de données et galerie internationale d'ouvrages d'art et du génie civil

Publicité

Investigation of the Optimization of Unloading Mining Scheme in Large Deep Deposit Based on Vague Set Theory and Its Application

Auteur(s):





Médium: article de revue
Langue(s): anglais
Publié dans: Advances in Civil Engineering, , v. 2021
Page(s): 1-13
DOI: 10.1155/2021/6690861
Abstrait:

With the development of shallow surface mineral resources in metal mines, it is gradually turning to the stage of deep mining. According to the current mining depth and the average annual depth, during the period of “14th Five-Year Plan,” one-third of the underground metal mines will reach or exceed the mining depth of 1,000 m, with the deepest being 2,000 m. In the stage of deep mining, mines will face the conditions of high stress, high temperature, high well depth, and strong mining disturbance, which will greatly increase the difficulty of large-scale deep mining. Among them, the high ground stress environment is the principal problem of many technical problems in deep mining. The selection of mining method has become a prerequisite for solving the problem of efficient and safe mining of deep deposits. In this paper, the vague set theory was introduced into the selection of mining methods and a vague set model for deep unloading mining schemes was established. Taking the Jinchuan No. 2 mining area as the engineering background, four unloading schemes for deep mining were proposed, and the Vague set model was used for optimization. It is concluded that the mining approach with large-section unloading is the optimal unloading mining plan. The application shows that it has the advantages of high unloading efficiency, large production capacity, and low loss index. It has been fully promoted in the deep mining of the mining area. It is feasible and effective to use the vague set theory in the selection of deep unloading mining schemes, which provides a proper approach in the selection of deep unloading mining schemes.

Copyright: © Jia Sheng 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
    10561193
  • Publié(e) le:
    10.02.2021
  • Modifié(e) le:
    02.06.2021
 
Structurae coopère avec
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine