Geomechanics and Engineering

  • 제37권2호
  • /
  • Pages.179-187
  • /
  • 2024
  • /
  • 2005-307X(pISSN)
  • /
  • 2092-6219(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Dynamic evolution characteristics of water inrush during tunneling through fault fracture zone

  • Jian-hua Wang (Transportation College, Southeast University) ;
  • Xing Wan (Transportation College, Southeast University) ;
  • Cong Mou (Transportation College, Southeast University) ;
  • Jian-wen Ding (Transportation College, Southeast University)
  • 투고 : 2022.05.29
  • 심사 : 2024.04.04
  • 발행 : 2024.04.25
⟨ 이전 논문 다음 논문 ⟩

초록

In this paper, a unified time-dependent constitutive model of Darcy flow and non-Darcy flow is proposed. The influencing factors of flow velocity are discussed, which demonstrates that permeability coefficient is the most significant factor. Based on this, the dynamic evolution characteristics of water inrush during tunneling through fault fracture zone is analyzed under the constant permeability coefficient condition (CPCC). It indicates that the curves of flow velocity and hydrostatic pressure can be divided into typical three stages: approximate high-velocity zone inside the fault fracture zone, velocity-rising zone near the tunnel excavation face and attenuation-low velocity zone in the tunnel. Furthermore, given the variation of permeability coefficient of the fault fracture zone with depth and time, the dynamic evolution of water flow in the fault fracture zone under the variable permeability coefficient condition (VPCC) is also studied. The results show that the time-related factor (α) affects the dynamic evolution distribution of flow velocity with time, the depth-related factor (A) is the key factor to the dynamic evolution of hydrostatic pressure.

키워드

과제정보

This work was supported by the International Postdoctoral Exchange Fellowship Program from China Postdoctoral Council (PC2021016). The authors would like to express appreciation to the reviewers for their valuable comments and suggestions that helped to improve the quality of the paper.

참고문헌

  1. Aalianvari, A. (2017), "Combination of engineering geological data and numerical modeling results to classify the tunnel route based on the groundwater seepage", Geomech. Eng., 13(4), 671-683. https://doi.org/10.12989/gae.2017.13.4.671.
  2. Ameli, A.A., McDonnell, J.J. and Bishop, K. (2016), "The exponential decline in saturated hydraulic conductivity with depth: a novel method for exploring its effect on water flow paths and transit time distribution", Hydrol. Process, 30, 2438-2450. https://doi.org/10.1002/hyp.10777.
  3. Baghbadorani, A.A., Hole, J.A., Baggett, J. and Ripepi, N. (2021), "Radar imaging of fractures and voids behind the walls of an underground mine", Geophysics, 86(4), 27-41. https://doi.org/10.1190/GEO2020-0763.1.
  4. Brinkman, H.C. (1949), "A calculation of the viscous force exerted by flowing fluid on a dense swam of particles", Appl. Sci. Res., 1(1), 27-34. https://doi.org/10.1007/BF02120313.
  5. Eftekhari, A. and Aalianvari, A. (2019), "An overview of several techniques employed to overcome squeezing in mechanized tunnels; A case study", Geomech. Eng., 18(2), 215-224. https://doi.org/10.12989/gae.2019.18.2.215.
  6. Giese, M., Reimann, T., Bailly-Comte, V., Marechal, J.C., Sauter, M. and Geyer, T. (2018), "Turbulent and laminar flow in karst conduits under unsteady flow conditions: interpretation of pumping tests by discrete conduit-continuum modeling", Water Resour. Res., 54(3), 1918-1933. https://doi.org/10.1002/2017WR020658.
  7. Golfier, F., Lasseux, D. and Quintard, M. (2015), "Investigation of the effective permeability of vuggy or fractured porous media from a Darcy-Brinkman approach", Computat. Geosci., 19, 63-78. https://doi.org/10.1007/s10596-014-9448-5.
  8. Hwang, J.H. and Lu, C.C. (2007), "A semi-analytical method for analyzing the tunnel water inflow", Tunn. Undergr. Sp. Tech., 22, 39-46. https://doi.org/10.1016/j.tust. 2006.03.003.
  9. Jiang, X.W., Li, W., Wang, X.S., Ge, S.M. and Liu, J. (2009), "Effect of exponential decay in hydraulic conductivity with depth on regional groundwater flow", Geophys. Res. Lett., 36, L24402. https://doi.org/10.1029/2009GL041251.
  10. Khoei, A.R., Sichani, A.S. and Hosseini, N. (2020), "Modeling of reactive acid transport in fractured porous media with the Extended-FEM based on Darcy-Brinkman-Forchheimer framework", Comput. Geotech., 128, 103778. https://doi.org/10.1016/j.compgeo.2020.103778.
  11. Kim, Y. and Moon, J.S. (2020), "Change of groundwater inflow by cutoff grouting thickness and permeability coefficient", Geomech. Eng., 21(2), 165-170. https://doi.org/10.12989/gae.2020.21.2.165.
  12. Kolymbas, D., and Wagner, P. (2007), "Groundwater ingress to tunnels-The exact analytical solution", Tunn. Undergr. Sp. Tech., 22(1), 23-27. https://doi.org/10.1016/j.tust.2006.02.001.
  13. Li, S.C., Gao, C.L., Zhou, Z.Q., Li, L.P., Wang, M.X., Yuan, Y.C. and Wang, J. (2019), "Analysis on the precursor information of water inrush in karst tunnels: a true triaxial model test study", Rock Mech. Rock Eng., 52(2), 373-384. https://doi.org/10.1007/s00603-018-1582-2.
  14. Ovalle-Villamil, W. and Sasanakul, l. (2019), "Investigation of non-Darcy flow for fine grained materials", Geotech. Geol. Eng., 37, 413-429. https://doi.org/10.1007/s10706-018-0620-x.
  15. Rumynin, V.G., Leskova, P.G. and Nikulenkov, A.M. (2019), "Effect of depth-dependent hydraulic conductivity and anisotropy on transit time distributions", J. Hydrol., 579, 124161. https://doi.org/10.1016/j.jhydrol.2019.124161.
  16. Shahbazi, A., Chesnaux, R. and Saeidi, A. (2021), "A new combined analytical-numerical method for evaluating the inflow rate into a tunnel excavated in a fractured rock mass", Eng. Geol., 283, 106003. https://doi.org/10.1016/j.enggeo.2021.106003.
  17. Shi, W.H., Yang, T.H., Liu, H.L. and Yang, B. (2018), "Numerical modeling of non-Darcy flow behavior of groundwater outburst through fault using the Forchheimer equation", J. Hydrol. Eng., 23(2), 04017062. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001617.
  18. Shiau, J. and Al-Asadi, F. (2020), "Two-dimensional tunnel heading stability factors Fc, Fs and Fγ", Tunn. Undergr. Sp. Tech., 97, 103293. https://doi.org/10.1016/j.tust.2020.103293.
  19. Song, Q., Xue, Y.G., Li, G.K., Su, M.X., Qiu, D.H., Kong, F.M. and Zhou, B.H. (2021), "Using Bayesian network and intuitionistic fuzzy analytic hierarchy process to assess the risk of water inrush from fault in subsea tunnel", Geomech. Eng., 27(6), 605-614. https://doi.org/10.12989/gae.2021.27.6.605.
  20. Wang, Y., Qin, F., Xia, Z.H. and Ni, X.D. (2012), "Non-Darcy flow model and numerical simulation for prediction water inflow in deep tunnel", Chin. J. Rock Mech. Eng., 31(9), 1862-1868.
  21. Williamson, K., Burda, P. and Sousedik, B. (2019), "A posteriori error estimates and adaptive mesh refinement for the Stokes-Brinkman problem", Math. Comput. Simulat., 166, 266-282. https://doi.org/10.1016/j.matcom.2019.05.015.
  22. Yang, G.Y., Che, C.H. and Liu, S.C. (2010), "Numerical simulation of forecasting water inrush volume from fault", J. Min. Saf. Eng., 27(3), 351-355.