DOI QR코드

DOI QR Code

Probabilistic Q-system for rock classification considering shear wave propagation in jointed rock mass

  • Kim, Ji-Won (Disposal Performance Demonstration Research Division, Korea Atomic Energy Research Institute) ;
  • Chong, Song-Hun (Department of Civil Engineering, Sunchon National University) ;
  • Cho, Gye-Chun (Department of Civil and Environmental Engineering, KAIST)
  • 투고 : 2022.02.23
  • 심사 : 2022.08.13
  • 발행 : 2022.09.10

초록

Safe underground construction in a rock mass requires adequate ground investigation and effective determination of rock conditions. The estimation of rock mass behavior is difficult, because rock masses are innately anisotropic and heterogeneous at different scales and are affected by various environmental factors. Quantitative rock mass classification systems, such as the Q-system and rock mass rating, are widely used for characterization and engineering design. The measurement of rock classification parameters is subjective and can vary among observers, resulting in questionable accuracy. Geophysical investigation methods, such as seismic surveys, have also been used for ground characterization. Torsional shear wave propagation characteristics in cylindrical rods are equal to that in an infinite media. A probabilistic quantitative relationship between the Q-value and shear wave velocity is thus investigated considering long-wavelength wave propagation in equivalent continuum jointed rock masses. Individual Q-system parameters are correlated with stress-dependent shear wave velocities in jointed rocks using experimental and numerical methods. The relationship between the Q-value and the shear wave velocity is normalized using a defined reference condition. This relationship is further improved using probabilistic analysis to remove unrealistic data and to suggest a range of Q-values for a given wave velocity. The proposed probabilistic Q-value estimation is then compared with field measurements and cross-hole seismic test data to verify its applicability.

키워드

과제정보

This research was supported by the Institute for Korea Spent Nuclear Fuel (iKSNF) and the National Research Foundation of Korea (NRF) grant funded by the Korea Ministry of Science and ICT (MSIT) (2017R1A5A 1014883 and 2021M2E1A1085193).

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