Geomechanics and Engineering

  • 제23권1호
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  • Pages.61-69
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  • 2020
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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

Energy analysis-based core drilling method for the prediction of rock uniaxial compressive strength

  • Qi, Wang (State Key Laboratory for Geo-mechanics and Deep Underground Engineering, China University of Mining & Technology (Beijing)) ;
  • Shuo, Xu (State Key Laboratory for Geo-mechanics and Deep Underground Engineering, China University of Mining & Technology (Beijing)) ;
  • Ke, Gao Hong (State Key Laboratory for Geo-mechanics and Deep Underground Engineering, China University of Mining & Technology (Beijing)) ;
  • Peng, Zhang (State Key Laboratory for Geo-mechanics and Deep Underground Engineering, China University of Mining & Technology (Beijing)) ;
  • Bei, Jiang (State Key Laboratory for Geo-mechanics and Deep Underground Engineering, China University of Mining & Technology (Beijing)) ;
  • Hong, Liu Bo (State Key Laboratory for Geo-mechanics and Deep Underground Engineering, China University of Mining & Technology (Beijing))
  • 투고 : 2019.02.22
  • 심사 : 2020.09.10
  • 발행 : 2020.10.10
⟨ 이전 논문 다음 논문 ⟩

초록

The uniaxial compressive strength (UCS) of rock is a basic parameter in underground engineering design. The disadvantages of this commonly employed laboratory testing method are untimely testing, difficulty in performing core testing of broken rock mass and long and complicated onsite testing processes. Therefore, the development of a fast and simple in situ rock UCS testing method for field use is urgent. In this study, a multi-function digital rock drilling and testing system and a digital core bit dedicated to the system are independently developed and employed in digital drilling tests on rock specimens with different strengths. The energy analysis is performed during rock cutting to estimate the energy consumed by the drill bit to remove a unit volume of rock. Two quantitative relationship models of energy analysis-based core drilling parameters (ECD) and rock UCS (ECD-UCS models) are established in this manuscript by the methods of regression analysis and support vector machine (SVM). The predictive abilities of the two models are comparatively analysed. The results show that the mean value of relative difference between the predicted rock UCS values and the UCS values measured by the laboratory uniaxial compression test in the prediction set are 3.76 MPa and 4.30 MPa, respectively, and the standard deviations are 2.08 MPa and 4.14 MPa, respectively. The regression analysis-based ECD-UCS model has a more stable predictive ability. The energy analysis-based rock drilling method for the prediction of UCS is proposed. This method realized the quick and convenient in situ test of rock UCS.

키워드

과제정보

This work was supported by the Natural Science Foundation of China (Nos. 51874188, 51704125 and 51927807), the Major Scientific and Technological Innovation Project of Shandong Province, China (Nos. 2019SDZY04 and 2018GGX109001), the Project of Shandong Province Higher Educational Youth Innovation Science and Technology Program, China (No. 2019KJG013).

참고문헌

  1. Arora, S. and Mishra, B. (2015), "Investigation of the failure mode of shale rocks in biaxial and triaxial compression tests", Int. J. Rock Mech. Min. Sci., 79, 109-123. https://doi.org/10.1016/j.ijrmms.2015.08.014.
  2. Barzegar, R., Sattarpour, M., Nikudel, M.R. and Moghaddam, A.A. (2016), "Comparative evaluation of artificial intelligence models for prediction of uniaxial compressive strength of travertine rocks, Case study: Azarshahr area, NW Iran", Model Earth Syst. Environ., 2(2), 1-13. https://doi.org/10.1007/s40808-016-0132-8.
  3. Burges, C.J.C. (1998), "A tutorial on support vector machines for pattern recognition", Knowledge Discovery Data Min., 2(2), 121-167. https://doi.org/10.1023/A:1009715923555.
  4. Chai, Z.Y., Bai, J.B. and Sun, Y.H. (2019), "Change of pore structure and uniaxial compressive strength of sandstone under electrochemical coupling", Geomech. Eng., 17(2), 157-164. https://doi.org/10.12989/gae.2019.17.2.157.
  5. Cristianini, N. and Shawe-Taylor, J. (2000), Support Vector Machines and Other Kernel-Based Learning Methods, Cambridge University Press, Oxford city, U.K.
  6. Ghosh, R., Gustafson, A. and Schunnesson, H. (2018), "Development of a geological model for chargeability assessment of borehole using drill monitoring technique", Int. J. Rock Mech. Min. Sci., 109, 9-18. https://doi.org/10.1016/j.ijrmms.2018.06.015.
  7. Heidari, M., Khanlari, G.R., Kaveh, M.T. and Kargarian, S. (2012), "Predicting the uniaxial compressive and tensile strengths of gypsum rock by point load testing", Rock Mech. Rock Eng., 45(2), 265-273. https://doi.org/10.1007/s00603-012-0264-8.
  8. Huang, W.Y., Tong, M.M. and Ren, Z.H. (2009), "Nonlinear combination forecast of gas emission amount based on SVM", J. China U. Min. Technol., 38(2), 234-239. https://doi.org/10.3321/j.issn:1000-1964.2009.02.017.
  9. Kahraman, S. and Yeken, T. (2010), "Electrical resistivity measurement to predict uniaxial compressive and tensile strength of igneous rocks", B. Mater. Sci., 33(6), 731-735. https://doi.org/10.1007/s12034-011-0137-x.
  10. Kalantari, S., Hashemolhosseini, H. and Baghbanan, A. (2018), "Estimating rock strength parameters using drilling data", Int. J. Rock Mech. Min. Sci., 104, 45-52. https://doi.org/10.1016/j.ijrmms.2018.02.013.
  11. Kilic, A. and Teymen, A. (2008), "Determination of mechanical properties of rocks using simple methods", B. Eng. Geol. Environ., 67, 237-244. https://doi.org/10.1007/s10064-008-0128-3.
  12. Kumar, B.R., Vardhan, H. and Govindaraj, M. (2011), "Prediction of uniaxial compressive strength, tensile strength and porosity of sedimentary rocks using sound level produced during rotary drilling", Rock Mech. Rock Eng., 44(5), 613-620. https://doi.org/10.1007/s00603-011-0160-7.
  13. Kun, M. and Onargan, T. (2013), "Influence of the fault zone in shallow tunneling: A case study of Izmir Metro Tunnel", Tunn. Undergr. Sp. Tech., 33(1), 34-45. https://doi.org/10.1016/j.tust.2012.06.016.
  14. Langford, J.C., Vlachopoulos, N. and Diederichs, M.S. (2016), "Revisiting support optimization at the Driskos tunnel using a quantitative risk approach", J. Rock Mech. Eng., 8(2), 147-163. https://doi.org/10.1016/j.jrmge.2015.11.003.
  15. Lei, G.F., Liu, Q.S., Peng, X.X. and Wei, L. (2020), "Experimental study on mechanical properties of fractured rock mass under different anchoring modes", Eur. J. Environ. Civ. Eng., 24(7), 931-948. https://doi.org/10.1080/19648189.2018.1429321.
  16. Li, W. and Tan, Z.Y. (2016), "Prediction of uniaxial compressive strength of rock based on P-wave modulus", Rock Soil Mech., 37(S2), 381-387 (in Chinese). https://doi.org/10.16285/j.rsm.2016.S2.049.
  17. Li, Y., Zhou, H., Zhang, L., Zhu, W.S., Li, S.C. and Liu, J. (2016), "Experimental and numerical investigations on mechanical property and reinforcement effect of bolted jointed rock mass", Constr. Build. Mater., 126, 843-856. https://doi.org/10.1016/j.conbuildmat.2016.09.100.
  18. Momeni, E., Armaghani, D.J., Hajihassani, M. and Amin, M.F.M. (2015), "Prediction of uniaxial compressive strength of rock samples using hybrid particle swarm optimization-based artificial neural networks", Measurement, 60, 50-63. https://doi.org/10.1016/j.measurement.2014.09.075.
  19. Mostofi, M., Rasouli, V. and Mawuli, E. (2011), "An estimation of rock strength using a drilling performance model: A case study in blacktip field, Australia", Rock Mech. Rock Eng., 44(3), 305-316. https://doi.org/10.1007/s00603-011-0142-9.
  20. Munoz, H., Taheri, A. and Chanda, E.K. (2016), "Rock drilling performance evaluation by an energy dissipation based rock brittleness index", Rock Mech. Rock Eng., 49(8), 3343-3355. https://doi.org/10.1007/s00603-016-0986-0.
  21. Qian, D.Y., Zhang, N., Pan, D.J., Xie, Z.Z., Shimada, H., Wang, Y., Zhang, C.H. and Zhang, N.C. (2017), "Stability of deep underground openings through large fault zones in argillaceous rock", Sustainability, 9(12), 2153. https://doi.org/10.3390/su9112153.
  22. Su, H.J., Jing, H.W., Zhao, H.H., Yu, L.Y. and Wang, Y.C. (2017), "Strength degradation and anchoring behavior of rock mass in the fault fracture zone", Environ. Earth Sci., 76(4), 179. https://doi.org/10.1007/s12665-017-6501-4.
  23. Vapnik V.N. (1995), The Nature of Statistical Learning Theory, Springer, New York, U.S.A.
  24. Vyacheslav, P. (2018), "Applicability of exponential stress-strain models for carbonate rocks", Geomech. Eng., 15(3), 915-929. https://doi.org/10.12989/gae.2018.15.3.919.
  25. Wan, Z., Dong, H. and Liu, B.C. (2010), "On choice of hyperparameters of support vector machines for time series regression and prediction with orthogonal design", Rock Soil Mech., 32(2), 503-508, 515 (in Chinese). https://doi.org/10.16285/j.rsm.2010.02.007.
  26. Wang, Q., Pan, R., Jiang, B., Li, S.C., He, M.C., Sun, H.B., Wang, L., Qin, Q., Yu, H.C. and Luan, Y.C. (2017), "Study on failure mechanism of roadway with soft rock in deep coal mine and confined concrete support system", Eng. Fail. Anal., 81, 155-177. https://doi.org/10.1016/j.engfailanal.2017.08.003.
  27. Wang, Q., Gao, H.K., Jiang, Z.H., Li, S.C. and Jiang, B. (2020a), "Development and application of a surrounding rock digital drilling test system of underground engineering", Chin. Rock Mech. Eng., 39(2), 301-310 (in Chinese). https://doi.org/10.13722/j.cnki.jrme.2019.0744.
  28. Wang, Q., He, M.C., Yang, J., Gao, H.K., Jiang, B. and Yu H.C. (2018a), "Study of a no-pillar mining technique with automatically formed gob-side entry retaining for longwall mining in coal mines", Int. J. Rock Mech. Min. Sci., 110, 1-8. https://doi.org/10.1016/j.ijrmms.2018.07.005.
  29. Wang, Q., Jiang, B., Pan, R., Li, S.C., He, M.C., Sun, H.B., Qin, Q., Yu, H.C. and Luan, Y.C. (2018b), "Failure mechanism of surrounding rock with high stress and confined concrete support system", Int. Ji. Rock Mech. Min. Sci., 102, 89-100. https://doi.org/10.1016/j.ijrmms.2018.01.020.
  30. Wang, Q., Jiang, Z.H., Jiang, B., Gao, H.K., Huang, Y.B. and Zhang, P. (2020b), "Research on an automatic roadway formation method in deep mining areas by roof cutting with high-strength bolt-grouting", Int. J. Rock Mech. Min. Sci., 128, 104264. https://doi.org/10.1016/j.ijrmms.2020.104264.
  31. Wang, Y. and Aladejare, A.E. (2016), "Bayesian characterization of correlation between uniaxial compressive strength and Young's modulus of rock", Int. J. Rock Mech. Min. Sci., 85, 10-19. https://doi.org/10.1016/j.ijrmms.2016.02.010.
  32. Wang. Q., Gao. H.K., Yu. H.C., Jiang. B. and Liu. B.H. (2019), "Method for measuring rock mass characteristics and evaluating the grouting-reinforced effect based on digital drilling", Rock Mech. Rock Eng., 52(3), 841-851. https://doi.org/10.1007/s00603-018-1624-9.
  33. Wu, X., Jiang, Y. and Li, B. (2018), "Influence of joint roughness on the shear behaviour of fully encapsulated rock bolt", Rock Mech. Rock Eng., 51(3), 953-959. https://doi.org/10.1007/s00603-017-1365-1.
  34. Xu, J.C., Ren, Q.W. and Shen, Z.Z. (2017), "Sensitivity analysis of the influencing factors of slope stability based on LS-SVM", Geomech. Eng., 13(3), 447-458. https://doi.org/10.12989/gae.2017.13.3.447.
  35. Yahiaoui, M., Paris, J.Y., Delbe, K., Denape, J., Gerbaud, L. and Dourfaye, A. (2016), "Independent analyses of cutting and friction forces applied on a single polycrystalline diamond compact cutter", Int. J. Rock Mech. Min. Sci., 85, 20-26. https://doi.org/10.1016/j.ijrmms.2016.03.002.
  36. Yasar, E., Ranjith, P.G. and Viete, D.R. (2011), "An experimental investigation into the drilling and physico-mechanical properties of a rock-like brittle material", J. Petrol. Sci. Eng., 76, 185-193. https://doi.org/10.1016/j.petrol.2011.01.011.
  37. Yong, R., Ye, J., Li, B. and Du, S.G. (2018), "Determining the maximum sampling interval in rock joint roughness measurements using Fourier series", Int. J. Rock Mech. Min. Sci., 101, 78-88. https://doi.org/10.1016/j.ijrmms.2017.11.008.
  38. Yu, J., Liu, GY., Cai, Y.Y., Zhou, J.F., Liu, S.Y. and Tu, B.X. (2020), "Time-dependent deformation mechanism for swelling soft-rock tunnels in coal mines and its mathematical deduction", Int. J. Geomech., 20(3), 04019186. https://doi.org/10.1061/(asce)gm.1943-5622.0001594.
  39. Zhang, B., Li, S.C., Yang, X.Y., Xia, K.W., Liu, J.Y., Guo, S. and Wang, S.G. (2019), "The coalescence and strength of rock-like materials containing two aligned X-type flaws under uniaxial compression", Geomech. Eng., 17(1), 47-56. https://doi.org/10.12989/gae.2019.17.1.047.
  40. Zhang, B., Li, S.C., Yang, X.Y., Zhang, D.F., Wang, Q., Cai, W., Yang, C.X. and Deng, Z.Q. (2015), "Mechanical property of rock-like material with intersecting multi-flaws under uniaxial compression", Chin. J. Rock Mech. Eng., 34(9), 1777-1785 (in Chinese). https://doi.org/10.13722/j.cnki.jrme.2014.0876.
  41. Zhang, C.S., Ji, J., Gui, Y.L., Kodikara, J., Yang, S.Q. and He, L. (2016), "Evaluation of soil-concrete interface shear strength based on LS-SVM", Geomech. Eng., 11(3), 361-372. https://doi.org/110.12989/gae.2016.11.3.361.
  42. Zhao, X.G., Cai, M., Wang, J. and Li, P.F. (2015), "Strength comparison between cylindrical and prism specimens of Beishan granite under uniaxial compression", Int. J. Rock Mech. Min. Sci., 766, 10-17. https://doi.org/10.1016/j.ijrmms.2015.02.009.
  43. Zhou, Y., Zhang, W., Gamwo, I. and Lin, J.S. (2017), "Mechanical specific energy versus depth of cut in rock cutting and drilling", Int. J. Rock Mech. Min. Sci., 100, 287-297. https://doi.org/10.1016/j.ijrmms.2017.11.004.