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Vol 238
Pages:
371
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Modern Mathematical Forecast Methods of Maintenance and Support Conditions for Mining Tunnel

Authors:
S. A. Ignatyev1
A. E. Sudarikov2
A. Zh. Imashev3
About authors
  • 1 — Saint-Petersburg Mining University
  • 2 — Saint-Petersburg Mining University
  • 3 — Karaganda State Technical University
Date submitted:
2019-03-13
Date accepted:
2019-05-07
Date published:
2019-08-25

Abstract

The research focuses on mathematical methods of mining pressure forecast to develop rational support patterns for mining tunnels and to ensure safety of mining operations. The purpose of research is to develop the methodology of applying advanced calculation methods and software solutions based on neural networks to reduce dispersion of factors influencing stability of mining tunnels, as well as to define rational parameters of mining tunnel support. The authors review the algorithm of geomechanical process examination, which is divided into several stages. First of all, it is proposed to use cluster analysis to examine location conditions of man-made outcrops, which allows to divide all the diversity of existing conditions for mining tunnel construction. Cluster analysis first allows to reduce the dispersion of factors that influence the stability of mining tunnels in various clusters, and then to determine rational parameters of tunnel support in each cluster. After the problem of cluster analysis is solved, it is proposed to use software programs that allow to study geomechanical processes in each cluster. At this stage, both standard methods (normative techniques, numerical modelling, analogies use, etc.) and the most advanced methods – neural networks – can be applied. Described algorithm of solving geomechanical problems, which utilizes advanced numerical methods and a software package based on neural networks, ensures an individual approach to estimation of mining pressure under varying conditions of man-made outcrop location in the rock mass.

10.31897/pmi.2019.4.371
Go to volume 238

References

  1. Borovikov V.P. STATISTICA Neural Networks: Translation from English. Moscow: Goryachaya liniya – Telekom, 2008, p. 392 (in Russian).
  2. Gal'yanov A.V. Historical Stages of Mining Art Development. Marksheideriya i nedropol'zovanie. 2011. N 1, p. 62-71
  3. (in Russian).
  4. Kolokolov S.B. The Mechanism of Fracture Zone Formation around Service Tunnels and Their Influence on the Supporting Timber: Avtoref. dis. … d-ra tekhn. nauk: 01.02.07. Akademiya nauk Resp. Kazakhstan. In-t matematiki i mekhaniki. Alma-Ata, 1992, p. 35 (in Russian).
  5. Stavrogin A.N., Protosenya A.G. Rock Plasticity. Moscow: Nedra, 1979, p. 304 (in Russian).
  6. Sudarikov A.E., Leonov V.V. To the Question of Market Segmentation Based on Advanced In-formation Technologies.
  7. Trudy Karagandinskogo universiteta biznesa, upravleniya i prava. 2004. N 1 (X), p. 93-96 (in Rus-sian).
  8. Sudarikov A.E. Neural Networks – a Theory of Complex Systems in Economics. Trudy univer-siteta. Karagandinskii
  9. gosudarstvennyi tekhnicheskii un-t (Karaganda). 2008. N 2, p. 69-72 (in Russian).
  10. Sudarikov A.E., Musin R.A. Numerical Modelling of Geomechanical Processes and Graphic Packages of Applied Software. Aktual'nye problemy gorno-metallurgicheskogo kompleksa Kazakh-stana: Trudy Mezhdunarodnoi nauchno-prakticheskoi konferentsii. Karaganda: Izd-vo KarGTU, 2005, p. 29-31 (in Russian).
  11. Sudarikov A.E. Econometrics. Karaganda: Karagandinskii universitet biznesa, upravleniya i prava, 2002, p. 198.
  12. (in Russian).
  13. Litvinenko V. Advancement of geomechanics and geodynamics at the mineral ore mining and underground space development. Geomechanics and Geodynamics of Rock Masses: Proceedings of the 2018 European Rock Mechanics Symposium.
  14. St. Peterburg, 22 May 2018. Taylor and Francis Group, London, UK, 2018. Vol. 1, p. 3-16.
  15. Protosenya A.G., Karasev M.A., Belyakov N.A. Elastoplastic problem for noncircular open-ings under Coulomb’s criterion. Journal of Mining Science. 2016. Vol. 52. Iss. 1, p. 53-61.
  16. Protosenia A., Karasev M.A., Ochkurov V. Introduction of the method of finite-discrete ele-ments into the Abaqus/Explicit software complex for modeling deformation and fracture of rocks. Eastern European Journal of Enterprise Technologies. 2017. Vol. 6. № 7(90), p. 11-18.
  17. Trushko V.L., Protosenia A.G., Verbilo P.E. Predicting strength of pillars in fractured rock mass during development of apatite-nephelinic ores. ARPN Journal of Engineering and Applied Sci-ences. 2018. Vol. 13 (8), p. 2864-2872.

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