DOI QR코드

DOI QR Code

Geostatistical algorithm for evaluation of primary and secondary roughness

  • Nasab, Hojat (Department of Mining Engineering, Shahid Bahonar University of Kerman) ;
  • Karimi-Nasab, Saeed (Department of Mining Engineering, Shahid Bahonar University of Kerman) ;
  • Jalalifar, Hossein (Department of Oil Engineering, Shahid Bahonar University of Kerman)
  • 투고 : 2020.09.13
  • 심사 : 2021.01.29
  • 발행 : 2021.02.25

초록

Joint roughness is combination of primary and secondary roughness. Ordinarily primary roughness is a geostatistical part of a joint surface that has a periodic nature but secondary roughness or unevenness is a statistical part of that which have a random nature. Using roughness generating algorithms is a useful method for evaluation of joint roughness. In this paper after determining geostatistical parameters of the joint profile, were presented two roughness generating algorithms using Mount-Carlo method for evaluation of primary (GJRGAP) and secondary (GJRGAS) roughness. These based on geostatistical parameters (range and sill) and statistical parameters (standard deviation of asperities height, SDH, and standard deviation of asperities angle, SDA) for generation two-dimensional joint roughness profiles. In this study different geostatistical regions were defined depending on the range and SDH. As SDH increases, the height of the generated asperities increases and asperities become sharper and at a specific range (a specific curve) relation between SDH and SDA is linear. As the range in GJRGAP becomes larger (the base of the asperities) the shape of asperities becomes flatter. The results illustrate that joint profiles have larger SDA with increase of SDH and decrease of range. Consequencely increase of SDA leads to joint roughness parameters such Z2, Z3 and RP increases. The results showed that secondary roughness or unevenness has a great influence on roughness values. In general, it can be concluded that the shape and size of asperities are appropriate parameters to approach the field scale from the laboratory scale.

키워드

참고문헌

  1. Asadi, M.S., Rasouli, V. and Barla, G. (2012), "A bonded particle model simulation of shear strength and asperity degradation for rough rock fractures", Rock Mech. Rock Eng., 45(5), 649-675. https://doi.org/10.1007/s00603-012-0231-4.
  2. Atapour, H. and Moosavi, M. (2014), "The influence of shearing velocity on shear behavior of artificial joints", Rock Mech. Rock Eng., 47(5), 1745-1761. https://doi.org/10.1007/s00603-013-0481-9.
  3. Babanouri, N. and Karimi-Nasab, S. (2015), "Modeling spatial structure of rock fracture surfaces before and after shear test: A method for estimating morphology of damaged zones", Rock Mech. Rock Eng., 48(3), 1051-1065. https://doi.org/10.1007/s00603-014-0622-9.
  4. Babanouri, N., Nasab, S.K. and Sarafrazi, S. (2013), "A hybrid particle swarm optimization and multi-layer perceptron algorithm for bivariate fractal analysis of rock fractures roughness", Int. J. Rock Mech. Min. Sci., 60, 66-74. https://doi.org/10.1016/j.ijrmms.2012.12.028.
  5. Barton, N. and Choubey, V. (1977), "The shear strength of rock joints in theory and practice", Rock Mech., 10(1-2), 1-54. https://doi.org/10.1007/BF01261801.
  6. Chen, S.J., Zhu, W.C., Yu, Q.L. and Liu, X.G. (2016), "Characterization of anisotropy of joint surface roughness and aperture by variogram approach based on digital image processing technique", Rock Mech. Rock Eng., 49(3), 855-876. https://doi.org/10.1007/s00603-015-0795-x.
  7. Fathi, A., Moradian, Z., Rivard, P., Ballivy, G. and Boyd, A.J. (2016), "Geometric effect of asperities on shear mechanism of rock joints", Rock Mech. Rock Eng., 49(3), 801-820. https://doi.org/10.1007/s00603-015-0799-6.
  8. Fecker, E. (1978), "Geotechnical description and classificatioin of joint surfaces", B. Int. Assoc. Eng. Geol., 18(1), 111-120. https://doi.org/10.1007/BF02635356.
  9. Grasselli, G. (2001), "Shear strength of rock joints based on quantified surface description", Ph.D. Thesis, Swiss Federal Institute of Technology Lausanne, Lausanne, Switzerland.
  10. Grasselli, G. and P. Egger (2003), "Constitutive law for the shear strength of rock joints based on three-dimensional surface parameters", Int. J. Rock Mech. Min. Sci., 40(1), 25-40. https://doi.org/10.1016/S1365-1609(02)00101-6.
  11. Gravanis, E. and Pantelidis, L. (2019), "Determining of the joint roughness coefficient (JRC) of rock discontinuities based on the theory of random fields", Geosciences, 9(7), 295. https://doi.org/10.3390/geosciences9070295.
  12. He, Z.M., Xiong, Z.Y., Hu, Q.G. and Yang, M. (2014), "Analytical and numerical solutions for shear mechanical behaviors of structural plane", J. Central South Univ., 21(7), 2944-2949. https://doi.org/10.1007/s11771-014-2261-4.
  13. Huan, J.Y., He, M.M., Zhang, Z.Q. and Li, N. (2019), "A new method to estimate the joint roughness coefficient by back calculation of shear strength", Adv. Civ. Eng. https://doi.org/10.1155/2019/7897529.
  14. Kulatilake, P.H.S.W., Um, J. and Pan, G. (1998), "Requirements for accurate quantification of self-affine roughness using the variogram method", Int. J. Solids Struct. 35(31-32), 4167-4189. https://doi.org/10.1016/S0020-7683(97)00308-9.
  15. Le, H.K., Huang, W.C., Liao, M.C. and Weng, M.C. (2018), "Spatial characteristics of rock joint profile roughness and mechanical behavior of a randomly generated rock joint", Eng. Geol., 245, 97-105. https://doi.org/10.1016/j.enggeo.2018.06.017.
  16. Lotfi, M. and Tokhmechi, B. (2019), "Fractal-wavelet-fusionbased re-ranking of joint roughness coefficients", J. Min. Environ., 10(4), 1121-1133. https://doi.org/10.22044/JME.2019.7489.1614.
  17. Matheron, G. (1963), "Principles of geostatistics", Econ. Geol., 58(8), 1246-1266. https://doi.org/10.2113/gsecongeo.58.8.1246.
  18. Mechanics, I.S.F.R. (1978), Suggested Methods for the Quantitative Description of Discontinuities in Rock Masses, Pergamon Press.
  19. Park, J.W., Lee, Y.K., Song, J.J. and Choi, B.H. (2013), "A constitutive model for shear behavior of rock joints based on three-dimensional quantification of joint roughness", Rock Mech. Rock Eng., 46(6), 1513-1537. https://doi.org/10.1007/s00603-012-0365-4.
  20. Rasouli, V. and Harrison, J. (2010), "Assessment of rock fracture surface roughness using Riemannian statistics of linear profiles", Int. J. Rock Mech. Min. Sci., 47(6), 940-948. https://doi.org/10.1016/j.ijrmms.2010.05.013.
  21. Tatone, B.S. and Grasselli, G. (2010), "A new 2D discontinuity roughness parameter and its correlation with JRC", Int. J. Rock Mech. Min. Sci., 47(8), 1391-1400. https://doi.org/10.1016/j.ijrmms.2010.06.006.
  22. Walck, C. (1996), Hand-book on Statistical Distributions for Experimentalists.
  23. Wang, M., Chen, Y.F., Ma, G.W., Zhou, J.Q. and Zhou, C.B. (2016), "Influence of surface roughness on nonlinear flow behaviors in 3D self-affine rough fractures: Lattice Boltzmann simulations", Adv. Water Resour., 96, 373-388. https://doi.org/10.1016/j.advwatres.2016.08.006.
  24. Wittke, W. (2014), Rock Mechanics based on an Anisotropic Jointed Rock Model (AJRM), John Wiley & Sons.
  25. Yong, R., Gu, L., Ye, J., Du, S.G., Huang, M., Hu, G. and Liu, J. (2019), "Neutrosophic function with nns for analyzing and expressing anisotropy characteristic and scale effect of joint surface roughness", Math. Prob. Eng. https://doi.org/10.1155/2019/8718936.
  26. Zhao, L., Zhang, S., Huang, D., Zuo, S. and Li, D. (2018), "Quantitative characterization of joint roughness based on semivariogram parameters", Int. J. Rock Mech. Min. Sci., 109, 1-8. https://doi.org/10.1016/j.ijrmms.2018.06.008.