Geomechanics and Engineering

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Combination of engineering geological data and numerical modeling results to classify the tunnel route based on the groundwater seepage

  • Aalianvari, A. (Mining Engineering Department, Faculty of Engineering, University of Kashan)
  • Received : 2016.12.10
  • Accepted : 2017.04.29
  • Published : 2017.10.25
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Abstract

Groundwater control is a significant issue in most underground construction. An estimate of the inflow rate is required to size the pumping system, and treatment plant facilities for construction planning and cost assessment. An estimate of the excavation-induced drawdown of the initial groundwater level is required to evaluate potential environmental impacts. Analytical and empirical methods used in current engineering practice do not adequately account for the effect of the jointed-rock-mass anisotropy and heterogeneity. The impact of geostructural anisotropy of fractured rocks on tunnel inflows is addressed and the limitations of analytical solutions assuming isotropic hydraulic conductivity are discussed. In this paper the unexcavated Zagros tunnel route has been classified from groundwater flow point of view based on the combination of observed water inflow and numerical modeling results. Results show that, in this hard rock tunnel, flow usually concentrates in some areas, and much of the tunnel is dry. So the remaining unexcavated Zagros tunnel route has been categorized into three categories including high Risk, moderately risk and low risk. Results show that around 60 m of tunnel (3%) length can conduit the large amount of water into tunnel and categorized into high risk zone and about 45% of tunnel route has moderately risk. The reason is that, in this tunnel, most of the water flows in rock fractures and fractures typically occur in a clustered pattern rather than in a regular or random pattern.

Keywords

References

  1. Aalianvari, A., Tehrani, M. M. and Soltanimohammadi, S. (2013), "Application of geostatistical methods to estimation of water flow from upper reservoir of Azad pumped storage power plant", Arab. J. Geosci., 6(7), 2571-2579. https://doi.org/10.1007/s12517-012-0528-3
  2. Aalianvari, A. (2014), "Optimum depth of grout curtain around pumped storage power cavern based on geological conditions", Bull. Eng. Geol. Environ., 73(3), 775-780. https://doi.org/10.1007/s10064-013-0550-z
  3. Barton, N., Lien, R. and Lunde, J. (1974), "Engineering classification of rock masses for the design of tunnel support", Rock Mech. 6(4), 189-236. https://doi.org/10.1007/BF01239496
  4. Berkowitz, B. and Balberg, I. (1993), "Percolation theory and its application to groundwater hydrology", Water Resour. Res., 29(4), 775-794. https://doi.org/10.1029/92WR02707
  5. El Tani, M. (1999), "Water inflow into tunnels", Proceedings of the World Tunnel Congress ITA-AITES 1999, Oslo, Norway, May-June.
  6. El Tani, M. (2003), "Circular tunnel in a semi-infinite aquifer", Tunn. Undergr. Sp. Tech., 18(1), 49-55. https://doi.org/10.1016/S0886-7798(02)00102-5
  7. Heuer, R.E. (1995), "Estimating rock-tunnel water inflow", Proceedings of the Rapid Excavation and Tunneling Conference, San Francisco, California, U.S.A., June.
  8. Jurado, A., De Gaspari, F., Vilarrasa, V., Bolster, D., Sanchez-Vila, X., Fernandez-Garcia, D. and Tartakovsky, D.M. (2012), "Probabilistic analysis of groundwater-related risks at subsurface excavation sites", Eng. Geol., 125, 35-44. https://doi.org/10.1016/j.enggeo.2011.10.015
  9. Karlsrud, K. (2001), "Water control when tunnelling under urban areas in the Olso region", NFF pub., 12(4), 27-33.
  10. Katibeh, H. and Aalianvari, A. (2009), "Development of a new method for tunnel site rating from groundwater hazard point of view", J. Appl. Sci., 9(8), 1496-1502. https://doi.org/10.3923/jas.2009.1496.1502
  11. Li, L.P., Lei, T., Li, S.C., Xu, Z.H., Xue, Y.G. and Shi, S.S. (2015), "Dynamic risk assessment of water inrush in tunnelling and software development", Geomech. Eng., 9(1), 57-81. https://doi.org/10.12989/gae.2015.9.1.057
  12. Raymer, J.H. (2003), "Predicting groundwater inflow into hard-rock tunnels: Estimating the high-end of the permeability distribution", Proceedings of the 2001 Rapid Excavation and Tunneling Conference, San Diego, California, U.S.A., June.
  13. Wickham, G.E., Tiedemann, H. and Skinner, E.H. (1972), "Support determination based on geologic predictions", Proceedings of the Conference on Rapid Excavation and Tunneling, Chicago, Illinois, U.S.A., June.
  14. Yang, X.L. and Yan, R.M. (2015), "Collapse mechanism for deep tunnel subjected to seepage force in layered soils", Geomech. Eng., 8(5), 741-756. https://doi.org/10.12989/gae.2015.8.5.741
  15. Yuan, Y.C., Li, S.C., Zhang, Q.Q., Li, L.P., Shi, S.S. and Zhou, Z.Q. (2016), "Risk assessment of water inrush in karst tunnels based on a modified grey evaluation model: Sample as Shangjiawan tunnel", Geomech. Eng., 11(4), 493-513 https://doi.org/10.12989/gae.2016.11.4.493
  16. Lee, Y.J. (2016), "Determination of tunnel support pressure under the pile tip using upper and lower bounds with a superimposed approach", Geomech. Eng., 11(4), 587-605. https://doi.org/10.12989/gae.2016.11.4.587
  17. Zhou, Z.Q., Li, S.C., Li, L.P., Shi, S.S. and Xu, Z.H. (2015), "An optimal classification method for risk assessment of water inrush in karst tunnels based on the grey system", Geomech. Eng., 8(5), 631-647. https://doi.org/10.12989/gae.2015.8.5.631
  18. Zarei, H.R., Uromeihy, A. and Sharifzadeh, M. (2013), "A new tunnel inflow classification (TIC) system through sedimentary rock masses", Tunn. Undergr. Sp. Tech., 34, 1-12. https://doi.org/10.1016/j.tust.2012.09.005

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