Risk assessment of water inrush and karst tunnels based on the efficacy coefficient method

• Autorzy: Wang Y. , Yin X. , Geng F. , Jing H. , Su H. , Liu R.
• Języki publikacji: EN

Abstrakty

EN

Water inrush is one of the typical geological hazards of tunnel construction in karst areas. It is necessary to predict water inrush more accurately for karst tunnels. Firstly, we created a model on risk evaluation of water inrush based on the efficacy coefficient method. Then karst hydrologic and engineering geological conditions were considered in detail, and several typical factors were selected as evaluation indexes, including formation lithology, unfavorable geology, groundwater level, and so on. Moreover, the weight coefficients of the selected evaluation indices were calculated using the analytic hierarchy process method. Furthermore, the total efficacy coefficient was presented to specify the risk grade of the evaluation samples. Finally, the risk grade of water inrush for karst tunnels is divided into four levels: severe (red), high (orange), elevated (yellow), and guarded (blue). Additionally, the model of risk assessment of water inrush was applied to Jigongling tunnel along the Fanba Expressway in China. The results show that the present evaluation results agree well with the construction situation, which also agree with the relative analysis results of attribute mathematical theory. The presented work with the efficacy coefficient method is relatively simple with strong operability, which has potential for predicting water inrush in karst tunnels.

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2017
• Tom: 26
• Numer: 4
• Opis fizyczny: p.1765-1775,fig.,ref.

Twórcy

autor

Wang Y.

• State Key laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, Jangsu, 221116, China

autor

Yin X.

• State Key laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, Jangsu, 221116, China
• School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, Jangsu, 221116, China

autor

Geng F.

• School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou, Jangsu, 221116, China

autor

Jing H.

• State Key laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, Jangsu, 221116, China
• School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, Jangsu, 221116, China

autor

Su H.

• State Key laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, Jangsu, 221116, China

autor

Liu R.

• State Key laboratory for Geomechanics and Deep Underground Engineering, China University of Mining and Technology, Xuzhou, Jangsu, 221116, China

Bibliografia

• 1. An Z., Di Q., Wu F., Wang G., Wang R. Geophysical exploration for a long deep tunnel to divert water from the Yangtze to the Yellow River [J]. China. B Eng Geol Environ, 711, 2012.
• 2. Huang R., Huang J., Ju N., Li Y. Automated tunnel rock classification using rock engineering systems [J]. Eng Geol, 156, 2013.
• 3. Zhang C., Feng X.T., Zhou H. Estimation of in situ stress along deep tunnels buried in complex geological conditions [J]. Int J Rock Mech Min, 52, 2012.
• 4. Li L., Lei T., Li S., Zhang Q., Xu Z., Shi S., Zhou Z. Risk assessment of water inrush in karst tunnels and software development [J]. Arab J Geosci, 8, 2014.
• 5. Lin C.N., LI L.P., HAN X.R. Research on forecast method of tunnel water inrush in complex karst areas [J]. Chin J Rock Soil Mech, 27, 2008.
• 6. Li S.C., Zhou Z.Q., Li L.P., Xu Z.H., Zhang Q.Q., Shi S.S. Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system [J]. Tunn Undergr Space Technol, 38, 2013.
• 7. Hwang J.H., Lu C.C. A semi-analytical method for analyzing the tunnel water inflow [J]. Tunn Undergr Space Technol, 22, 2007.
• 8. Lu Y.L., Wang L.G. Numerical simulation of mining-induced fracture evolution and water flow in coal seam floor above a confined aquifer [J]. Comput Geotech, 67, 2015.
• 9. Yao B.H., Bai H.B., Zhang B.Y. Numerical simulation on the risk of roof water inrush in Wuyang Coal Mine [J]. Int J Min Sci Technol, 22, 2012.
• 10. Wang Y., Yang W.F., Li M., Liu X. Risk assessment of floor water inrush incoal mines based on secondary fuzzy comprehensive evaluation [J]. Int J Rock Mech Min, 52, 2012.
• 11. Chen J.M., Yang R.S. Analysis of mine water inrush accident based on FTA [J]. Procedia Environmental Sciences, 11, 2011.
• 12. Olga Š., Jirˇí.Š., Daniel S. Probabilistic assessment of tunnel construction performance based on data [J]. Tunn Undergr Space Technol, 37, 2013a.
• 13. Olga Š., Eva N., Michal Š, Jirˇí.Š. Probabilistic models for tunnel construction risk assessment [J]. Adv Eng Softw, 62-63, 2013b.
• 14. Fouladgar M.M., Yazdani-Chamzini A., Zavadskas E.K. Risk evaluation of tunneling projects [J]. Arch Civ Mech Eng, 12, 2012.
• 15. Hodlur G., Prakash R.M, Deshmukh, S. Singh V. Role of some salient geo-physical, geochemical, and hydrogeological parameters in the exploration of fresh groundwater in a brackish terrain [J]. Environ Geol, 41, 2002.
• 16. Bukowski P. Water hazard assessment in active shafts in Upper Silesian Coal Basin mines [J]. Mine Water Environ, 30, 2011.
• 17. Li Z.L., Wang X.H., Xie L.Z. Risk evaluation and comprehensive geological prediction based on fuzzy wavelet neural network during tunneling in karst area [J]. Electron J Geotech Eng, 17, 2012.
• 18. Shi L.Q., Qiu M., Wei W.X., Xu D.J., Han J. Water inrush evaluation of coal seam floor by integrating the water inrush coefficient and the information of water abundance [J]. Int J Rock Mech Min, 24, 2014.
• 19. Meng Z.P., Li G.Q., Xie X.T. A geological assessment method of floor water inrush risk and its application [J]. Eng Geol, 143-144, 2012.
• 20. Li X.P., Li Y.N. Research on risk assessment system for water inrush in the karst tunnel construction based on GIS: Case study on the diversion tunnel groups of the Jinping II Hydropower Station [J]. Tunn Undergr Space Technol, 40, 2014.
• 21. Matthias S., Niels P.H., Arild R., Harald B. Risk assessment of road tunnels using Bayesian networks [J]. Procedia - Social and Behavioral Sciences, 48, 2012.
• 22. WANG Y.C., YIN X., JING H.W., LIU R.C., SU H.J. A novel model of the cloud for risk analysis of water inrush in karst tunnels. ENVIRON EARTH SCI, 75, 2016.
• 23. WANG Y.C., JING H.W., YU L.Y., SU H.J., LUO N. Set pair analysis for risk assessment of water inrush in karst tunnels[J]. B ENG GEOL ENVIRON, 7, 2016.
• 24. WANG Y.C., JING H.W., HAN L.J., YU L.Y., ZHANG Q. Risk analysis on swell -shrink capacity of expansive soils with efficacy coefficient method and entropy coefficient method[J]. APPL CLAY SCI, 99, 2014.
• 25. WANG Y.C., JING H.W., ZHANG Q., LUO N., YIN X. Prediction of Collapse Scope of Deep-Buried Tunnels Using Pressure Arch Theory[J]. Math Probl Eng, 3-4, 2016.
• 26. WANG Y.C., JING H.W., SU H.J., XIE J.Y. Effect of a Fault Fracture Zone on the Stability of Tunnel-Surrounding Rock[J]. INT J GEOMECH, 04016135, 2016.
• 27. WANG Y.C., ZHAO N., JING H.W., Meng B., Yin X. A novel model of the ideal point method coupled with objective and subjective weighting method for evaluation of surrounding rock stability[J]. Math Probl Eng, 12, 2016.
• 28. Xu J., Zhang Q., Wu J. Application of efficient method to determination of rock preferred structural plane [J]. Chin J Geotech Eng, 30, 2008.
• 29. Wang Y.C., Shang Y.Q., Sun H.Y. Study of prediction of rockburst intensity based on efficacy coefficient method [J]. Chin J Rock Soil Mech, 31, 2010.
• 30. Saaty T.L. Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World [M]. Pittsburgh, Pennsylvania: RWS Publications. ISBN 0-9620317-8-X, 2008.
• 31. Zhou Z.Q., Li S.C., Li L.P., Shi S.S., Song S.G., Wang K. Attribute recognition model and its application of fatalness assessment of water inrush in karst tunnels [J]. Rock Soil Mech, 34, 2013.

Identyfikatory

DOI

10.15244/pjoes/65839