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Attribute recognition model for risk assessment of water inrush

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Abstract

An attribute recognition model of water inrush risk evaluation is established based on attribute mathematic theory and software is developed for risk assessment in a tunnel. In our model, the entropy weight method is applied to analyze the weights of evaluation indexes. Considering karst hydrologic and engineering geological conditions of a tunnel under construction, eight major influencing factors of water inrush (formation lithology, unfavorable geology, groundwater level, attitude of rocks, contact zone of dissolvable and insoluble rocks, layer and interlayer fissures, catchment ability and surrounding rock mass classification) are selected as the evaluation indexes, and an index system of water inrush risk assessment is constituted. The tunnel is divided into 26 sections, and 340 evaluation objects are selected from these 26 sections in order to construct a judgment matrix. The water inrush risk of the whole tunnel is evaluated by using the proposed software. The results indicate that the attribute recognition model of water inrush risk evaluation is scientific and reasonable and that the software is convenient for use in calculations and is easy to master.

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References

  • Bukowski P (2011) Water hazard assessment in active shafts in upper Silesian Coal Basin mines. Mine Water Environ 30(4):302–311

    Article  Google Scholar 

  • Chu XJ, Yan HF, Zhou RJ et al (2007) Application of entropy coefficient based attribute recognition model in comprehensive evaluation for grid company. Journal of electric power science and technology 22(4):56–59 (in Chinese)

    Google Scholar 

  • Cover TM, Thomas JA (2012) Elements of information theory. Wiley, Hoboken, NJ, USA

    Google Scholar 

  • Dong X, Lu H, Xia YP et al (2016) Decision-making model under risk assessment based on entropy. Entropy 18(404):1–15

    Google Scholar 

  • Haitao L, Chao Y, Zongmin C et al (2015) Risk assessment of security systems based on entropy theory and the Neyman-Pearson criterion. Reliab Eng Syst Saf 142:68–77

    Article  Google Scholar 

  • Huang HW (2006) State of the art of the research on risk management in construction of tunnel and underground works. Chinese journal of underground space and engineering 2(1):13–20 (in Chinese)

    Google Scholar 

  • Li XP, Li YN (2014) 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. Tunn Undergr Space Technol 40:182–191

    Article  Google Scholar 

  • Li SC, Zhou ZQ, Li LP et al (2013) Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system. Tunn Undergr Space Technol 38:50–58

    Article  Google Scholar 

  • Liu F, Zhao SZ, Weng MC et al (2017) Fire risk assessment for large-scale commercial buildings based on structure entropy weight method. Saf Sci 94:26–40

    Article  Google Scholar 

  • Lu Q, Sun HY, Bak KL (2011) Reliability analysis of ground-support interaction in circular tunnels using the response surface method. International journal of rock mechanics & mining sciences 48:1329–1343

    Article  Google Scholar 

  • Lv HT, Yin C, Cui ZM et al (2015) Risk assessment of security systems based on entropy theory and the Neyman-Pearson criterion. Reliab Eng Syst Saf 142:68–77

    Article  Google Scholar 

  • Xu ZH, Li SC, Li LP et al (2011) Risk assessment of water or mud inrush of karst tunnels based on analytic hierarchy process. Rock Soil Mech 32(6):1757–1766 (in Chinese)

    Google Scholar 

  • Yao BH, Bai HB, Zhang BY (2012) Numerical simulation on the risk of roof water inrush in Wuyang coal mine. Int J Min Sci Technol 22(2):273–277

    Article  Google Scholar 

  • Zhang WG, Anthony TC (2012) Reliability assessment on ultimate and serviceability limit states and determination of critical factor of safety for underground rock caverns. Tunn Undergr Space Technol 32:221–230

    Article  Google Scholar 

  • Zhang XQ, Liang C, Liu HQ (2005) Application of attribute recognition model based on coefficient of entropy to comprehensive evaluation of groundwater quality. Journal of Sichuan University: engineering science edition 37(3):28–31 (in Chinese)

    Google Scholar 

  • Zhang QS, Li SC, Han HW (2009) Study on risk evaluation and water inrush disaster preventing technology during construction of karst tunnels. Journal of Shandong University: Engineering Science 39(3):106–110 (in Chinese)

    Google Scholar 

  • Zhang XQ, Wang CB, Li EK et al (2014) Assessment model of ecoenvironmental vulnerability based on improved entropy weight method. The science world journal 2014:1–7

    Google Scholar 

  • Zhou ZQ, Li SC, Li LP et al (2013) Attribute recognition model of fatalness assessment of water inrush in karst tunnels and its application. Rock Soil Mech 34(3):818–826 (in Chinese)

    Google Scholar 

Download references

Acknowledgments

The work is supported by National Basic Research Program of China (Grant No.2013CB036000), National Natural Science Foundation of China (Grant No. 51609129, 51479107), State Key Lab of Subtropical Building Science, South China University of Technology (2016ZB07), State Key Laboratory for GeoMechanics and Deep Underground Engineering, China University of Mining & Technology (Grant No. SKLGDUEK1515), Shandong Provincial Natural Science Foundation, China (Grant No. ZR2014EEQ002), China Postdoctoral Science Foundation (2017 T100492, 2017 M612273) and Shandong postdoctoral innovation project special Foundation (Grant No. 201502025).

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Authors and Affiliations

  1. Geotechnical and Structural Engineering Research Center, Shandong University, Jinan, Shandong, 250061, China

    Jing Wang, Shu-cai Li, Li-ping Li, Peng Lin, Zhen-hao Xu & Cheng-lu Gao

  2. State Key Lab of Subtropical Building Science, South China University of Technology, Guangzhou, Guangdong, 510005, China

    Li-ping Li

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  1. Jing Wang
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  2. Shu-cai Li
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  3. Li-ping Li
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  4. Peng Lin
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  5. Zhen-hao Xu
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  6. Cheng-lu Gao
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Correspondence to Jing Wang.

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Wang, J., Li, Sc., Li, Lp. et al. Attribute recognition model for risk assessment of water inrush. Bull Eng Geol Environ 78, 1057–1071 (2019). https://doi.org/10.1007/s10064-017-1159-4

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  • DOI: https://doi.org/10.1007/s10064-017-1159-4

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