Risk assessment of water inrush in karst tunnels excavation based on normal cloud model

Water inrush in karst tunnels is a dynamic process in which internal and external factors are involved. The evaluation of this process is fuzzy, complex, and uncertain. In the current research, few articles give full consideration to the fuzziness and randomness of the water inrush evaluation with useful dynamic feedback. A new assessment method has been proposed for the water inrush evaluation based on a combination of the weighting method and normal cloud model. Specifically, an evaluation index system is forged and each index is quantitatively classified into four grades. A synthetic weighted algorithm combining the analytic hierarchy process, entropy method, and statistical methods is proposed to assign the index weight rationally. Based on the cloud generator algorithm, three numerical characteristics are calculated and a sufficient number of cloud droplets are generated. The membership degree of each index belonging to each grade is constructed and the integrated certain grades are determined. In this paper, the multi-factor normal cloud assessment method is applied to the risk assessment of the Qiyueshan tunnel. The assessment result of the risk grade is accurate, that is, the water inrush risk of different samples at the same risk grade can be reflected in figures. The results not only show high consistency with other assessment methods but are also in good agreement with the excavation results. The proposed cloud model method demonstrates good practical reference for risk assessment of tunnel construction in karst areas and can be applied to tunneling, mining, and other engineering practices in the future.

[1]  Shangxian Yin,et al.  A study of mine water inrushes by measurements of in situ stress and rock failures , 2015, Natural Hazards.

[2]  Weiwen Zhou,et al.  Risk Assessment of Water Inrush in Tunnel through Water-Rich Fault , 2017, Geotechnical and Geological Engineering.

[3]  Sungkwon Woo,et al.  Study on the issues of the lowest bidding through the analysis of working budget ratio of Korean construction companies , 2017 .

[4]  Ming Li,et al.  Risk assessment of floor water inrush in coal mines based on secondary fuzzy comprehensive evaluation , 2012 .

[5]  Zhenhao Xu,et al.  Unascertained measure model of water and mud inrush risk evaluation in karst tunnels and its engineering application , 2017 .

[6]  S. Shen,et al.  Ground Response to Multiple Parallel Microtunneling Operations in Cemented Silty Clay and Sand , 2016 .

[7]  Thomas L. Saaty,et al.  Decision-making with the AHP: Why is the principal eigenvector necessary , 2003, Eur. J. Oper. Res..

[8]  Huai-Na Wu,et al.  Longitudinal structural modelling of shield tunnels considering shearing dislocation between segmental rings , 2015 .

[9]  Joon-Shik Moon,et al.  Effect of Excavation-Induced Groundwater Level Drawdown on Tunnel Inflow in a Jointed Rock Mass , 2010 .

[10]  S. Shen,et al.  Long-term settlement behaviour of metro tunnels in the soft deposits of Shanghai , 2014 .

[11]  Robert Hack,et al.  Preparation of land use planning model using GIS based on AHP : case study Adana-Turkey , 2013 .

[12]  Qing Wang,et al.  Susceptibility analysis of large-scale debris flows based on combination weighting and extension methods , 2013, Natural Hazards.

[13]  H. Lyu,et al.  Flood risk assessment in metro systems of mega-cities using a GIS-based modeling approach. , 2018, The Science of the total environment.

[14]  A. McLachlan,et al.  Beach erosion along Al Batinah coast, Sultanate of Oman , 2016, Arabian Journal of Geosciences.

[15]  Mohammad-Javad Khanjani,et al.  Significant wave height modelling using a hybrid Wavelet-genetic Programming approach , 2017 .

[16]  J. H. Shin.  Analytical and combined numerical methods evaluating pore water pressure on tunnels , 2010 .

[17]  Hu-Chen Liu,et al.  A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method , 2015, Appl. Soft Comput..

[18]  Xie Li-zhao.  Risk Evaluation and Comprehensive Geological Prediction Based on Fuzzy Wavelet Neural Network during Tunneling in Karst Area , 2013 .

[19]  Huai-Na Wu,et al.  Chinese karst geology and measures to prevent geohazards during shield tunnelling in karst region with caves , 2015, Natural Hazards.

[20]  Przemyslaw Jakiel,et al.  FAHP model used for assessment of highway RC bridge structural and technological arrangements , 2015, Expert Syst. Appl..

[21]  Wanfang Zhou,et al.  Application of the Analytic Hierarchy Process to Assessment of Water Inrush: A Case Study for the No. 17 Coal Seam in the Sanhejian Coal Mine, China , 2013, Mine Water and the Environment.

[22]  Nobuya Narita,et al.  Hydrogeochemistry of tunnel seepage water along the contact of zone of metasedimentary and granitic rock within the Pahang–Selangor Raw Water Transfer Tunnel Project, Malaysia , 2016, Arabian Journal of Geosciences.

[23]  Shucai Li,et al.  Application of the comprehensive forecast system for water-bearing structures in a karst tunnel: a case study , 2019, Bulletin of Engineering Geology and the Environment.

[24]  Xin-li Hu,et al.  Deformation characteristics and failure mode of the Zhujiadian landslide in the Three Gorges Reservoir, China , 2015, Bulletin of Engineering Geology and the Environment.

[25]  Shi Shao-shuai,et al.  Risk assessment of water or mud inrush of karst tunnels based on analytic hierarchy process , 2011 .

[26]  Linjian Ma,et al.  Uncertainty Analysis on Risk Assessment of Water Inrush in Karst Tunnels , 2016 .

[27]  Shi Shao-shuai,et al.  Construction permit mechanism of karst tunnels based on dynamic assessment and management of risk , 2011 .

[28]  Deyi Li,et al.  A new cognitive model: Cloud model , 2009, Int. J. Intell. Syst..

[29]  Binbin Xu,et al.  Reliability Evaluation of NC Machine Tools considering Working Conditions , 2016 .

[30]  Kai Zhang,et al.  Mechanism of water inrush and quicksand movement induced by a borehole and measures for prevention and remediation , 2015, Bulletin of Engineering Geology and the Environment.

[31]  Guoyin Wang,et al.  Generic normal cloud model , 2014, Inf. Sci..

[32]  Shucai Li,et al.  Risk Assessment of Rockfall Hazardsin a Tunnel Portal Section Basedon Normal Cloud Model , 2017 .

[33]  Huang Bin-ren.  Analysis of Water Leakage during Construction of Qing-shan-gang Tunnel and Study of Leakage Treatment Measures , 2008 .

[34]  Zhen Huang,et al.  Identification of geological structure which induced heavy water and mud inrush in tunnel excavation: A case study on Lingjiao tunnel , 2017 .

[35]  Shucai Li,et al.  Risk assessment of water inrush in karst tunnels and software development , 2015, Arabian Journal of Geosciences.

[36]  Shucai Li,et al.  Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system , 2013 .

[37]  Hongwen Jing,et al.  Set pair analysis for risk assessment of water inrush in karst tunnels , 2017, Bulletin of Engineering Geology and the Environment.

[38]  Shi Shaoshuai,et al.  CONSTRUCTION LICENSE MECHANISM AND ITS APPLICATION BASED ON KARST WATER INRUSH RISK EVALUATION , 2011 .

[39]  H. Lyu,et al.  Assessment of Geohazards and Preventative Countermeasures Using AHP Incorporated with GIS in Lanzhou, China , 2018 .

[40]  Abdolreza Yazdani-Chamzini,et al.  Proposing a new methodology based on fuzzy logic for tunnelling risk assessment , 2014 .

[41]  Xueping Li,et al.  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 , 2014 .

[42]  Qiang Sun,et al.  Experimental research on water inrush in tunnel construction , 2016, Natural Hazards.