Geomechanics and Engineering

  • 제15권6호
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  • Pages.1153-1160
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  • 2018
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  • 2005-307X(pISSN)
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  • 2092-6219(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Experimental investigation of predicting rockburst using Bayesian model

  • Wang, Chunlai (Faculty of Resources and Safety Engineering, China University of Mining and Technology Beijing) ;
  • Chuai, Xiaosheng (Faculty of Resources and Safety Engineering, China University of Mining and Technology Beijing) ;
  • Shi, Feng (Faculty of Resources and Safety Engineering, China University of Mining and Technology Beijing) ;
  • Gao, Ansen (Faculty of Resources and Safety Engineering, China University of Mining and Technology Beijing) ;
  • Bao, Tiancai (Faculty of Resources and Safety Engineering, China University of Mining and Technology Beijing)
  • 투고 : 2017.08.15
  • 심사 : 2018.04.04
  • 발행 : 2018.08.30
⟨ 이전 논문 다음 논문 ⟩

초록

Rockbursts, catastrophic events involving the violent release of elastic energy stored in rock features, remain a worldwide challenge for geoengineering. Especially at deep-mining sites, rockbursts can occur in hard, high-stress, brittle rock zones, and the associated risk depends on such factors as mining activity and the stress on surrounding rocks. Rockbursts are often sudden and destructive, but there is still no unified standard for predicting them. Based on previous studies, a new Bayesian multi-index model was introduced to predict and evaluate rockbursts. In this method, the rock strength index, energy release index, and surrounding rock stress are the basic factors. Values from 18 rock samples were obtained, and the potential rockburst risks were evaluated. The rockburst tendencies of the samples were modelled using three existing methods. The results were compared with those obtained by the new Bayesian model, which was observed to predict rockbursts more effectively than the current methods.

키워드

과제정보

연구 과제 주관 기관 : National Natural Science Foundation of China, Central Universities

참고문헌

  1. Adoko, A.C., Gokceoglu, C., Wu, L. and Zuo, Q.J. (2013), "Knowledge-based and data-driven fuzzy modeling for rockburst prediction", Int. J. Rock Mech. Min. Sci., 61, 86-95. https://doi.org/10.1016/j.ijrmms.2013.02.010
  2. Blake, W. and Hedley, D.G.F. (2003), "Rockbursts: case studies from North American hard-rock mines. Society for mining, metallurgy, and exploration", Englewood, Colo.
  3. Canadian Rockburst Research Program (1996), Rockburst Research Handbook: A Comprehensive Summary of Five Years of Collaborative Research on Rockbursting in Hard Rock Mines, CAMIRO Mining Division, CRRP.
  4. Chen, H.J., Li, N.H., Nie, D.X. and Shang, Y.Q. (2002), "Artificial neural network model for prediction of rockburst", Chin. J. Geotech. Eng., 24(2), 229-232. (in Chinese)
  5. Cook, N.G.W. (1965), "The failure of rock", Int. J. Rock Mech. Min. Sci. Geomech. Abstr., 2(4), 389-403. https://doi.org/10.1016/0148-9062(65)90004-5
  6. Dou, L.M., Lu, C.P., Mu, Z.L. and Gao, M.S. (2009), "Prevention and forecasting of rock burst hazards in coal mines", Int. J. Min. Sci. Technol., 19(5), 585-591.
  7. Gao, H.X. (1999), Multivariate Statistical Analysis Application. Beijing University Press, Beijing, China. (in Chinese)
  8. Heckerman, D. (1990), "Probabilistic similarity networks", Network., 20(5), 607-636. https://doi.org/10.1002/net.3230200508
  9. Hedley, D.G.F. (1992), "Rockburst handbook for Ontario hardrock mines", CANMET, SP92-1E.
  10. Hoek, E. and Brown, E.T. (1980), "Empirical strength criterion for rock masses", J. Geotech. Geoenviron. Eng., 106, 1013-1035.
  11. Hua, A.Z. and You, M.Q. (2001), "Rock failure due to energy release during unloading and application to underground rock burst control", Tunn. Undergr. Sp. Tech., 16(3), 241-246. https://doi.org/10.1016/S0886-7798(01)00046-3
  12. Jensen, F.V., Kjaerulff, U., Kristiansen, B., Langseth, H., Skaanning, C., Vonlel, J. and Vomlelova, M. (2001), "The SACSO methodology for troubleshooting complex systems", AI EDAM, 15(4), 321-333.
  13. Jiang, Q., Feng, X.T., Xiang, T.B. and Su, G.S. (2010), "Rockburst characteristics and numerical simulation based on a new energy index: a case study of a tunnel at 2,500 m depth", Bull. Eng. Geol. Environ., 69(3), 381-388. https://doi.org/10.1007/s10064-010-0275-1
  14. Kemmerer, B., Mishra, S. and Shenoy, P.P. (2002), "Bayesian casual maps as decision aids in venture capital decision making: Methods and applications", Acad. Manage. Proc., 2002(1), C1-C6. https://doi.org/10.5465/apbpp.2002.7519521
  15. Kidybinski, A. (1981), "Bursting liability indices of coal", Int. J. Rock Mech. Min. Sci. Geomech. Abstr., 18(4), 295-304. https://doi.org/10.1016/0148-9062(81)91194-3
  16. Li, N., Feng, X. and Jimenez, R. (2017), "Predicting rock burst hazard with incomplete data using Bayesian networks", Tunn. Undergr. Sp. Tech., 61, 61-70. https://doi.org/10.1016/j.tust.2016.09.010
  17. Li, X., Wang, E., Li, Z., Bie, X., Chen, L., Feng, J. and Li, N. (2016), "Blasting wave pattern recognition based on Hilbert-Huang transform", Geomech. Eng., 11(5), 607-624. https://doi.org/10.12989/gae.2016.11.5.607
  18. Marek, U. (2009), "Monitoring of methane and rockburst hazards as a condition of safe coal exploitation in the mines of Kompania Weglowa SA", Procedia Earth Planet Sci., 1(1), 54-59. https://doi.org/10.1016/j.proeps.2009.09.011
  19. Marian, T. (2011), "Directions of changes of hard coal output technologies in Poland", Min. Sci. Tech. (China), 21(1), 1-5. https://doi.org/10.1016/j.mstc.2009.08.001
  20. Muller, L. (2007), Fundamentals of Rock Mechanics, Blackwell, London.
  21. Patynska, R. and Kabiesz, J. (2009), "Scale of seismic and rock burst hazard in the Silesian companies in Poland", Min Sci. Tech (China), 19(5), 604-608. https://doi.org/10.1016/S1674-5264(09)60112-5
  22. Pytlik, A., Prusek, S. and Masny, W. (2016), "A methodology for laboratory testing of rockbolts used in underground mines under dynamic loading conditions", J. South. Afri. Inst. Min. Metal., 116(12), 1101-1110. https://doi.org/10.17159/2411-9717/2016/v116n12a2
  23. Russenes, B.F. (1974), "Analyses of rockburst in tunnels in valley sides", Norwegian Institute of Technology, Trondheim Google Scholar.
  24. Sainoki, A., Mitri, H.S., Yao, M. and Chinnasane, D. (2016), "Discontinuum modelling approach for stress analysis at a seismic source: Case study", Rock Mech. Rock Eng., 49(12), 4749-4765. https://doi.org/10.1007/s00603-016-1089-7
  25. Shokouhi, P., Riviere, J., Bas, P.Y.L. and Ulrich, T.J. (2017), "Nonlinear acoustic testing for concrete materials evaluation", Mater. Eval., 75(1), 84-93.
  26. Singh, S.P. (1988), "Burst energy release index", Rock Mech. Rock Eng., 21(2), 149-155. https://doi.org/10.1007/BF01043119
  27. Singh, S.P. (1989), "Classification of mine workings according to their rockburst proneness", Min Sci. Tech., 8(3), 253-262. https://doi.org/10.1016/S0167-9031(89)90404-0
  28. Sun, J., Wang, L.G., Zhang, H.L. and Shen, Y.F. (2009), "Application of fuzzy neural network in predicting the risk of rock burst", Proc. Earth Planet Sci., 1(1), 536-543. https://doi.org/10.1016/j.proeps.2009.09.085
  29. Turchaninov, I.A. and Markov, G.A. (1981), "Conditions of changing of extra-hard rock into weak rock under the influence of tectonic stresses of massifs", ISRM International Symposium, International Society for Rock Mechanics.
  30. Wang, C.L. (2014), "Identification of early-warning key point for rockmass instability using acoustic emission/microseismic activity monitoring", Int. J. Rock Mech. Min. Sci., 71, 171-175. https://doi.org/10.1016/j.ijrmms.2014.06.009
  31. Wang, C.L., Bao, T.C., Lu, H., Liu, L., Li, W.Q. and Yu, Q.W. (2015b), "Variation regulation of the acoustic emission energy parameter during the failure process of granite under uniaxial compression", Mater. Test., 57(9), 755-760. https://doi.org/10.3139/120.110776
  32. Wang, C.L., Lu, H., Wang, F.L., Zuo, J.P., An, Z.Y., Bao, T.C., Liu, L., Lu, Z.J., Li, W.Q. and Luo, M. (2014), "Characteristic point of the relatively quiet period for limestone failure under uniaxial compression", J. Test Eval., 43(6), 1296-1307.
  33. Wang, C.L., Lu, Z.J., Liu, L., Chuai, X.S. and Lu, H. (2016), "Predicting points of the infrared precursor for limestone failure under uniaxial compression", Int. J. Rock Mech. Min. Sci., 88, 34-43. https://doi.org/10.1016/j.ijrmms.2016.07.004
  34. Wang, C.L., Wu, A.X., Lu, H., Bao, T.C. and Liu, X.H. (2015a), "Predicting rockburst tendency based on fuzzy matter-element model", Int. J. Rock Mech. Min. Sci., 75, 224-232. https://doi.org/10.1016/j.ijrmms.2015.02.004
  35. Weidl, G., Madsen, A.L. and Dahlquist, E. (2003), "Object oriented Bayesian networks for industrial process operation", First Bayesian Applications Modeling Workshop, http://www.intel.com/research/events/UAI03_workshop.
  36. Wiebols, G.A. and Cook, N.G.W. (1968), "An energy criterion for the strength of rock in polyaxial compression", Int. J. Rock Mech. Min. Sci. Geomech. Abstr., 5(6), 529-549. https://doi.org/10.1016/0148-9062(68)90040-5
  37. Zhang, C., Feng, X.T., Zhou, H., Qiu, S. and Wu, W. (2013), "Rockmass damage development following two extremely intense rockbursts in deep tunnels at Jinping II hydropower station, southwestern China", Bull. Eng. Geol. Environ., 72(2), 237-247. https://doi.org/10.1007/s10064-013-0470-y
  38. Zhao, T.B., Guo, W.Y., Tan, Y.L., Lu, C.P. and Wang, C.W. (2017), "Case histories of rock bursts under complicated geological conditions", Bull. Eng. Geol. Environ., 1-17.

피인용 문헌

  1. Research on Structural Characteristics of Dynamic Nuclear Zone in Dynamic System of Coal and Rock vol.2019, pp.None, 2018, https://doi.org/10.1155/2019/4815236
  2. Quantitative Calculation of Critical Depth in Typical Rockburst Mine vol.2020, pp.None, 2018, https://doi.org/10.1155/2020/7968160