Dynamic risk evaluation method of collapse in the whole construction of shallow buried tunnels and engineering application

Zhiqiang Li; Sheng Wang; Yupeng Cao; Ruosong Ding; Zhiqiang Li; Sheng Wang; Yupeng Cao; Ruosong Ding

doi:10.3934/mbe.2022199

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 4: 4300-4319. doi: 10.3934/mbe.2022199

Previous Article Next Article

Research article

Dynamic risk evaluation method of collapse in the whole construction of shallow buried tunnels and engineering application

1.
School of Civil Engineering and Architecture, Weifang University, Weifang 261061, China
2.
School of Civil Engineering, Yangtze Normal University, Chongqing 408100, China
3.
Geotechnical and Structural Engineering Research Center, Shandong University, Ji'nan 250061, China
4.
Shandong Hi-Speed Construction Management Group Co., Ltd, Jinan 250013, China

Academic Editor: Xiaodong Huang

Received: 13 November 2021 Revised: 29 January 2022 Accepted: 17 February 2022 Published: 25 February 2022

The collapse is the most frequent and harmful geological hazard during the construction of the shallow buried tunnel, which seriously threatens the life and property safety of construction personnel. To realize the process control of collapse in the tunnel construction, a three-stage risk evaluation method of collapse in the whole construction process of shallow tunnels was put forward. Firstly, according to the engineering geology and hydrogeology information obtained in the prospecting stage, a fuzzy model of preliminary risk evaluation based on disaster-pregnant environment factors was proposed to provide a reference for the optimization design of construction and support schemes in the design stage. Secondly, the disaster-pregnant environment factors were corrected based on the obtained information, such as advanced geological forecast and geological sketch, and the disaster-causing factors were introduced. An extension theory model of secondary risk evaluation was established to guide the reasonable excavation and primary support schemes. Finally, the disaster-pregnant and disaster-causing factors were corrected according to the excavation condition, an attribute model of final risk evaluation for the collapse was constructed combined with the mechanical response index of the surrounding rock. Meanwhile, the risk acceptance criteria and construction decision-making method of the collapse in the shallow buried tunnels were formulated to efficiently implement the multi-level risk control of this hazard. The proposed method has been successfully applied to the Huangjiazhuang tunnel of the South Shandong High-Speed Railway. The comparison showed that the evaluation results are highly consistent for these practical situations, which verify the application value of this study for guiding the safe construction of shallow buried tunnels.
- shallow buried tunnel,
- collapse,
- dynamic evaluation,
- construction decision-making,
- application
Citation: Zhiqiang Li, Sheng Wang, Yupeng Cao, Ruosong Ding. Dynamic risk evaluation method of collapse in the whole construction of shallow buried tunnels and engineering application[J]. Mathematical Biosciences and Engineering, 2022, 19(4): 4300-4319. doi: 10.3934/mbe.2022199

Related Papers:

Abstract

The collapse is the most frequent and harmful geological hazard during the construction of the shallow buried tunnel, which seriously threatens the life and property safety of construction personnel. To realize the process control of collapse in the tunnel construction, a three-stage risk evaluation method of collapse in the whole construction process of shallow tunnels was put forward. Firstly, according to the engineering geology and hydrogeology information obtained in the prospecting stage, a fuzzy model of preliminary risk evaluation based on disaster-pregnant environment factors was proposed to provide a reference for the optimization design of construction and support schemes in the design stage. Secondly, the disaster-pregnant environment factors were corrected based on the obtained information, such as advanced geological forecast and geological sketch, and the disaster-causing factors were introduced. An extension theory model of secondary risk evaluation was established to guide the reasonable excavation and primary support schemes. Finally, the disaster-pregnant and disaster-causing factors were corrected according to the excavation condition, an attribute model of final risk evaluation for the collapse was constructed combined with the mechanical response index of the surrounding rock. Meanwhile, the risk acceptance criteria and construction decision-making method of the collapse in the shallow buried tunnels were formulated to efficiently implement the multi-level risk control of this hazard. The proposed method has been successfully applied to the Huangjiazhuang tunnel of the South Shandong High-Speed Railway. The comparison showed that the evaluation results are highly consistent for these practical situations, which verify the application value of this study for guiding the safe construction of shallow buried tunnels.

References

[1]	Q. H. Qian, P. Lin, Safety risk management of underground engineering in China: progress, challenges and strategies, J. Rock Mech. Geotech. Eng., 8 (2016), 423–442. https://doi.org/10.1016/j.jrmge.2016.04.001 doi: 10.1016/j.jrmge.2016.04.001
[2]	S. Wang, L. P. Li, S. Cheng, J. Y. Yang, H. Jin, S. Gao, et al., Study on an improved real-time monitoring and fusion prewarning method for water inrush in tunnels, Tunnelling Underground Space Technol., 112 (2021), 103884. https://doi.org/10.1016/j.tust.2021.103884 doi: 10.1016/j.tust.2021.103884
[3]	W. Chen, G. H. Zhang, H. Wang, L. B. Chen, Risk assessment of mountain tunnel collapse based on rough set and conditional information entropy, Rock Soil Mech., 40 (2019), 1–10. https://doi.org/10.16285/j.rsm.2018.1290 doi: 10.16285/j.rsm.2018.1290
[4]	Q. J. Zuo, L. Wu, C.Y. Lin, C. M. Xu, B. Li, Z. L. Lu, et al., Collapse mechanism and treatment measures for tunnel in water-rich soft rock crossing fault, Chin. J. Rock Mech. Eng., 35 (2016), 369–377. https://doi.org/10.13722/j.cnki.jrme.2014.1632 doi: 10.13722/j.cnki.jrme.2014.1632
[5]	M. Fera, R. Macchiaroli, Proposal of a quali-quantitative assessment model for health and safety in small and medium enterprises, WIT Trans. Bulit Environ., 108 (2009), 117–126. https://doi.org/10.2495/SAFE090121 doi: 10.2495/SAFE090121
[6]	H. H. Einstein, Risk and risk analysis in rock engineering, Tunnelling Underground Space Technol., 11 (1996), 141–155. https://doi.org/10.1016/0886-7798(96)00014-4 doi: 10.1016/0886-7798(96)00014-4
[7]	B. Nilsen, A. Palmstrom, H. Stille, Quality control of a subsea tunnel project in complex ground conditions, in Proceedings of the ITA World Tunnel Congress Oslo, Norway, (1999), 137–144.
[8]	R. Sturk, L. Olsson, J. Johansson, Risk and decision analysis for large underground projects as applied to the stockholm ring road tunnels, Tunnelling Underground Space Technol., 11 (1996), 157–164. https://doi.org/10.1016/0886-7798(96)00019-3 doi: 10.1016/0886-7798(96)00019-3
[9]	S. V. Woude, U. Maidl, J. J. Honker, Risk management for the betuweroute shield driven tunnels, Claiming Underground Space, 2003 (2003), 1043–1049.
[10]	S. D. Eskesen, P. R. Tengborg, J. Kampmann, T. H. Veicherts, Guidelines for tunnelling risk management: international tunnelling association, working group No. 2, Tunnelling Underground Space Technol., 19 (2004), 217–237. https://doi.org/10.1016/j.tust.2004.01.001
[11]	H. H. Choi, H. N. Cho, J. W. Seo, Risk assessment methodology for underground construction projects, J. Constr. Eng. Manage., 130 (2004), 258–272. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:2(258) doi: 10.1061/(ASCE)0733-9364(2004)130:2(258)
[12]	H. S. Shin, Y. C. Kwon, Y. S. Jung, G. J. Bae, Y. G. Kim, Methodology for quantitative hazard assessment for tunnel collapses based on case histories in Korea, Int. J. Rock Mech. Min. Sci., 46 (2009), 1072–1087. https://doi.org/10.1016/j.ijrmms.2009.02.009 doi: 10.1016/j.ijrmms.2009.02.009
[13]	M. Fera, R. Macchiaroli, Use of analytic hierarchy process and fire dynamics simulator to assess the fire protection systems in a tunnel on fire, Int. J. Risk Assess. Manage., 14 (2010), 504–529.
[14]	I. Benekos, D. Diamantidis, On risk assessment and risk acceptance of dangerous goods transportation through road tunnels in Greece, Saf. Sci., 91 (2017), 1–10. http://dx.doi.org/10.1016/j.ssci.2016.07.013
[15]	A. N. Beard, Tunnel safety, risk assessment and decision-making, Tunnelling Underground Space Technol., 25 (2010), 91–94. https://doi.org/10.1016/j.tust.2009.07.006 doi: 10.1016/j.tust.2009.07.006
[16]	L. Chen, H. W. Huang, Risk analysis of rock tunnel engineering, Chin. J. Rock Mech. Eng., 24 (2005), 110–115. https://doi.org/10.3321/j.issn:1000-6915.2005.01.018 doi: 10.3321/j.issn:1000-6915.2005.01.018
[17]	S. C. Li, Z. Q. Zhou, L. P. Li, Z. H. Xu, Q. Q. Zhang, S. S. Shi, Risk assessment of water inrush in karst tunnels based on attribute synthetic evaluation system, Tunnelling Underground Space Technol., 38 (2013), 50–58. https://doi.org/10.1016/j.tust.2013.05.001 doi: 10.1016/j.tust.2013.05.001
[18]	J. J. Chen, F. Zhou, J. S. Yang, B. C. Liu, Fuzzy analytic hierarchy process for risk evaluation of collapseduring construction of mountain tunnel, Rock Soil Mech., 30 (2009), 2365–2370. https://doi.org/10.16285/j.rsm.2009.08.017 doi: 10.16285/j.rsm.2009.08.017
[19]	Y. C. Zhai, Y. S. Hu, X. H. Liao, Y. L. Sun, Renovated nonlinear fuzzy assessment method for casting the tunnel collapse risk based on the entropy weighting, J. Saf. Environ., 16 (2016), 41–45. https://doi.org/10.13637/j.issn.1009-6094.2016.05.008 doi: 10.13637/j.issn.1009-6094.2016.05.008
[20]	Y. C. Yuan, S. C. Li, L. P. Li, T. Lei, S. Wang, B. L. Sun, Risk evaluation theory and method of collapse in mountain tunnel and its engineering applications, J. Cent. South Univ. (Sci. Technol.), 47 (2016), 2406–2414. https://doi.org/10.11817/j.issn.1672-7207.2016.07.031 doi: 10.11817/j.issn.1672-7207.2016.07.031
[21]	C. L. Gao, S. C. Li, J. Wang, L. P. Li, P. Lin, The risk assessment of tunnels based on grey correlation and entropy weight method, Geotech. Geol. Eng., 36 (2018), 1621–1631. https://doi.org/10.1007/s10706-017-0415-5 doi: 10.1007/s10706-017-0415-5
[22]	G. Z. Ou, Y. Y. Jiao, G. H. Zhang, J. P. Zou, F. Tan, W. S. Zhang, Collapse risk assessment of deep-buried tunnel during construction and its application, Tunnelling Underground Space Technol., 115 (2021), 104019. https://doi.org/10.1016/j.tust.2021.104019 doi: 10.1016/j.tust.2021.104019
[23]	S. C. Li, S. S. Shi, L. P. Li, Z. Q. Zhou, M. Guo, T. Lei, Attribute recognition model and its application of mountain tunnel collapse risk assessment, J. Basic Sci. Eng., 21 (2013), 147–158. https://doi.org/10.3969/j.issn.1005-0930.2013.01.016 doi: 10.3969/j.issn.1005-0930.2013.01.016
[24]	Z. G. Xu, N. G. Cai, X. F. Li, M. T. Xian, T. W. Dong, Risk assessment of loess tunnel collapse during construction based on an attribute recognition model, Bull. Eng. Geol. Environ., 80 (2021), 6205–6220. https://doi.org/10.1007/s10064-021-02300-8 doi: 10.1007/s10064-021-02300-8
[25]	S. Wang, L. P. Li, S. Cheng, Risk assessment of collapse in mountain tunnels and software development, Arabian J. Geosci., 13 (2020), 1196. https://doi.org/10.1007/s12517-020-05520-6 doi: 10.1007/s12517-020-05520-6
[26]	S. Wang, L. P. Li, S. S. Shi, S. Cheng, H. J. Hu, T. Wen, Dynamic risk assessment method of collapse in mountain tunnels and application, Geotech. Geol. Eng., 38 (2020), 2913–2926. https://doi.org/10.1007/s10706-020-01196-7 doi: 10.1007/s10706-020-01196-7
[27]	W. G. Cao, Y. C. Zhai, J. Y. Wang, Y. J. Zhang, Method of set pair analysis for collapse risk during construction of mountain tunnel, Chin. J. Highway Transp., 25 (2012), 90–99. https://doi.org/10.19721/j.cnki.1001-7372.2012.02.013 doi: 10.19721/j.cnki.1001-7372.2012.02.013
[28]	W. Chen, G. H. Zhang, Y. Y. Jiao, H. Wang, Unascertained measure-set pair analysis model of collapse risk Evaluation in mountain tunnels and its engineering application, KSCE J. Civil Eng., 25 (2021), 451–467. https://doi.org/10.1007/s12205-020-0627-8 doi: 10.1007/s12205-020-0627-8
[29]	X. J. Guan, Evaluation method on risk grade of tunnel collapse based on extension connection cloud model, J Saf. Sci. Technol., 14 (2018), 186–192. https://doi.org/10.11731/j.issn.1673-193x.2018.11.030 doi: 10.11731/j.issn.1673-193x.2018.11.030
[30]	G. Yang, D. W. Liu, F. J. Chu, H. D. Peng, W. X. Huang, Evaluation on risk grade of tunnel collapse based on cloud model, J. Saf. Sci. Technol., 11 (2015), 95–101. https://doi.org/10.11731/j.issn.1673-193x.2015.06.015 doi: 10.11731/j.issn.1673-193x.2015.06.015
[31]	Y. L. An, L. M. Peng, B. Wu, F. Zhang, Comprehensive extension assessment on tunnel collapse risk, J. Cent. South Univ. (Sci. Technol.), 42 (2011), 514–520. https://doi.org/10.4028/www.scientific.net/AMR.211-212.106 doi: 10.4028/www.scientific.net/AMR.211-212.106
[32]	Z. Yang, X. L. Rong, H. Lu, X. Dong, Risk assessment on the tunnel collapse probability by the theory of extenics in combination with the entropy weight and matter-element model, J. Saf. Environ., 16 (2016), 15–19. https://doi.org/10.13637/j.issn.1009-6094.2016.02.003 doi: 10.13637/j.issn.1009-6094.2016.02.003
[33]	Y. C. Wang, X. Yin, F. Geng, H. W. Jing, H. J. Su, R. C. Liu, Risk assessment of water inrush in karst tunnels based on the efficacy coefficient method, Pol. J. Environ. Stud., 4 (2017), 1765–1775. https://doi.org/10.15244/pjoes/65839 doi: 10.15244/pjoes/65839
[34]	M. Caterino, M. Fera, R. Macchiaroli, A. Lambiase, Appraisal of a new safety assessment method using the petri nets for the machines safety, IFAC Papers Online, 51 (2018), 933–938. https://doi.org/10.1016/j.ifacol.2018.08.488 doi: 10.1016/j.ifacol.2018.08.488
[35]	Z. Q. Zhou, S. C. Li, L. P. Li, B. Sui, S. S. Shi, Q. Q. Zhang, Causes of geological hazards and risk control of collapse in shallow tunnels, Rock Soil Mech., 34 (2013), 1376–1382. https://doi.org/10.16285/j.rsm.2013.05.028 doi: 10.16285/j.rsm.2013.05.028
[36]	S. Wang, Regional Dynamic Risk Assessment and Early Warning of Tunnel Water Inrush and Application, Master thesis, Shandong University, 2016.

Reader Comments

Your name:*

Email:*
© 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)