Technical Papers
Jul 12, 2022

A Probabilistic Risk Assessment Approach for Surface Settlement Caused by Metro Tunnel Construction Using Credal Network

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 3

Abstract

The epistemic uncertainty of geological condition, hydrological condition, and human factors causes the risk assessment result of metro construction to be imprecise. To reveal the epistemic uncertainty, a probabilistic risk assessment approach for metro construction is proposed based on the credal network. The epistemic uncertainty of risk factors is described by prior probability and conditional probability. Based on the scarcity of available data, prior probability is quantified by interval probability and probability box, and conditional probability is qualified by imprecise leaky noisy-OR model and imprecise Dirichlet model. Taking the shield tunnel projects of Beijing Metro Line 14 as the research object, the proposed approach and the conventional approach without considering epistemic uncertainty were adopted to predict the risk probability of surface settlement caused by shield tunnel construction. The predicted results were compared with the statistical probability derived from Peck formula and the field monitoring data, which verifies the rationality and effectiveness of the proposed approach.

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Data Availability Statement

All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This work is supported by the National Natural Science Foundation of China (No. 51538001). The authors are grateful to H. D. Estrada-Lugo for his assistance in calculation by OpenCossan. We also wish to offer thanks for the engineering data support of Beijing Transit Design and Research Consultant Co., Ltd. and Beijing Agiletech Engineering Consultant Co., Ltd. The first author thanks Professor Xiuli Du and Beijing University of Technology for the financial support to enable this research to be conducted at the Department of Civil and Environmental Engineering, National University of Singapore.

References

Abellán, J. 2006. “Uncertainty measures on probability intervals from the imprecise Dirichlet model.” Int. J. Gen. Syst. 35 (5): 509–528. https://doi.org/10.1080/03081070600687643.
Al-Bittar, T., and A. Soubra. 2013. “Bearing capacity of strip footings on spatially random soils using sparse polynomial chaos expansion.” Int. J. Numer. Anal. Methods Geomech. 37 (13): 2039–2060. https://doi.org/10.1002/nag.2120.
Antonucci, A. 2011. “The imprecise noisy-OR gate.” In Proc., 14th Int. Conf. on Information Fusion, 709–715. New York: IEEE and International Society of Information Fusion.
Beer, M., S. Ferson, and V. Kreinovich. 2013. “Imprecise probabilities in engineering analyses.” Mech. Syst. Sig. Process. 37 (1–2): 4–29. https://doi.org/10.1016/j.ymssp.2013.01.024.
Chakeri, H., Y. Ozcelik, and B. Unver. 2013. “Effects of important factors on surface settlement prediction for metro tunnel excavated by EPB.” Tunnelling Underground Space Technol. 36 (Jun): 14–23. https://doi.org/10.1016/j.tust.2013.02.002.
Chen, C. H. 2020. “Report on 3 deaths caused by ground collapse of Guangzhou metro.” [In Chinese.] Accessed May 27, 2020. https://www.thepaper.cn/newsDetail_forward_7580110.
Chen, L., X. Gu, and X. Long. 2009. “Safety assessment of excavation with fault tree analysis.” Georisk. 3 (3): 126–133. https://doi.org/10.1080/17499510902896620.
Cozman, F. G. 2000. “Credal networks.” Artif. Intell. 120 (2): 199–233. https://doi.org/10.1016/S0004-3702(00)00029-1.
Cozman, F. G. 2005. “Graphical models for imprecise probabilities.” Int. J. Approximate Reasoning 39 (2–3): 167–184. https://doi.org/10.1016/j.ijar.2004.10.003.
Estrada-Lugo, H. D., S. Tolo, M. de Angelis, and E. Patelli. 2019. “Pseudo credal networks for inference with probability intervals.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part B: Mech. Eng. 5 (4): 41010. https://doi.org/10.1115/1.4044239.
Fargnoli, V., D. Boldini, and A. Amorosi. 2013. “TBM tunnelling-induced settlements in coarse-grained soils: The case of the new Milan underground line 5.” Tunnelling Underground Space Technol. 38 (Sep): 336–347. https://doi.org/10.1016/j.tust.2013.07.015.
Feng, X., J. C. Jiang, and W. F. Wang. 2020. “Gas pipeline failure evaluation method based on a noisy-OR gate Bayesian network.” J. Loss Prev. Process Ind. 66 (Jul): 104175. https://doi.org/10.1016/j.jlp.2020.104175.
He, L. X., A. T. Gomes, M. Broggi, and M. Beer. 2019. “Failure analysis of soil slopes with advanced Bayesian networks.” Period. Polytech. Civ. Eng. 63 (3): 763–774. https://doi.org/10.3311/PPci.14092.
MOHURD (Ministry of Housing and Urban-Rural Development). 2013. Code for monitoring measurement of urban rail transit engineering. GB 50911-2013. Beijing: MOHURD.
Namazian, A., and S. H. Yakhchali. 2018. “Modified Bayesian network-based risk analysis of construction projects: Case study of south pars gas field development projects.” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng. 4 (4): 5018003. https://doi.org/10.1061/AJRUA6.0000997.
O’Reilly, M. P., and B. M. New. 1982. “Settlements above tunnels in the United Kingdom—Their magnitude and prediction.” In Proc., 3rd Int. Sym., Inst. Mining and Metallurgy, 173–181. London: Institution of Mining & Metallurgy.
Park, H., J. Oh, D. Kim, and S. Chang. 2018. “Monitoring and analysis of ground settlement induced by tunnelling with slurry pressure-balanced tunnel boring machine.” Adv. Civ. Eng. 2018: 5879402. https://doi.org/10.1155/2018/5879402.
Patelli, E., S. Tolo, H. George-Williams, J. Sadeghi, R. Rocchetta, M. De Angelis, and M. Broggi. 2018. “Opencossan 2.0: An efficient computational toolbox for risk, reliability and resilience analysis.” In Proc., ICVRAM ISUMA Uncertainties Conf., 1–12. Sao Paulo, Brazil: Univ. of São Paulo.
Peck, R. B. 1969. “Deep excavations and tunneling in soft ground.” In Proc., 7th Int. Conf. Soil Mechanics and Foundation Engineering, 225–290. Mexico City: Sociedad Mexicana de Mecanica.
Phoon, K. K., J. Y. Ching, and T. Shuku. 2022. “Challenges in data-driven site characterization.” Georisk: Assess. Manage. Risk Eng. Syst. Geohazards 16 (1): 114–126. https://doi.org/10.1080/17499518.2021.1896005.
Phoon, K. K., and F. H. Kulhawy. 1999. “Characterization of geotechnical variability.” Can. Geotech. J. 36 (4): 612–624. https://doi.org/10.1139/t99-038.
Sousa, R. L. 2010. “Risk analysis for tunneling projects.” Ph.D. dissertation, Dept. of Civil and Environmental Engineering, Massachusetts Institute of Technology.
Sousa, R. L., and H. H. Einstein. 2012. “Risk analysis during tunnel construction using Bayesian networks: Porto metro case study.” Tunnelling Underground Space Technol. 27 (1): 86–100. https://doi.org/10.1016/j.tust.2011.07.003.
Špačková, O., E. Novotná, M. Šejnoha, and J. Šejnoha. 2013. “Probabilistic models for tunnel construction risk assessment.” Adv. Eng. Software 62–63 (Aug–Sep): 72–84. https://doi.org/10.1016/j.advengsoft.2013.04.002.
Sun, J. L., B. G. Liu, Z. F. Chu, L. Chen, and X. Li. 2018. “Tunnel collapse risk assessment based on multistate fuzzy Bayesian networks.” Qual. Reliab. Eng. Int. 34 (8): 1646–1662. https://doi.org/10.1002/qre.2351.
Tessem, B. 1992. “Interval probability propagation.” Int. J. Approximate Reasoning 7 (3): 95–120. https://doi.org/10.1016/0888-613X(92)90006-L.
Tolo, S., E. Patelli, and M. Beer. 2018. “An open toolbox for the reduction, inference computation and sensitivity analysis of credal networks.” Adv. Eng. Software 115 (Jan): 126–148. https://doi.org/10.1016/j.advengsoft.2017.09.003.
Utkin, L. V., and T. Augustin. 2007. “Decision making under incomplete data using the imprecise Dirichlet model.” Int. J. Approximate Reasoning 44 (3): 322–338. https://doi.org/10.1016/j.ijar.2006.07.016.
Walley, P. 1996. “Inferences from multinomial data: Learning about a bag of marbles.” J. R. Stat. Soc. B. 58 (1): 3–57. https://doi.org/10.1111/j.2517-6161.1996.tb02065.x.
Wang, Z., L. Qiao, S. Li, and L. Bi. 2016. “Risk assessment for stability and containment property of an underground oil storage facility in construction phase using fuzzy comprehensive evaluation method.” ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng. 2 (4): 4016009. https://doi.org/10.1061/AJRUA6.0000885.
Weber, P., G. Medina-Oliva, C. Simon, and B. Iung. 2012. “Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas.” Eng. Appl. Artif. Intell. 25 (4): 671–682. https://doi.org/10.1016/j.engappai.2010.06.002.
Wei, P. F., and J. W. Song. 2019. “Recent developments on uncertainty quantification and sensitivity analysis.” In Proc., 11th Natl. Conf. on Theory and Application of Random Vibration, 1–31. Shanghai, China: Tongji Univ.
Wu, C. S., and Z. D. Zhu. 2019. “Statistical analysis of ground loss ratio caused by different tunnel construction methods in China.” J. Zhejiang Univ. (Eng. Sci.). 53 (1): 19–30. https://doi.org/10.3785/j.issn.1008-973X.2019.01.003.
Wu, X. G., H. T. Liu, L. M. Zhang, M. J. Skibniewski, Q. L. Deng, and J. Y. Teng. 2015. “A dynamic Bayesian network based approach to safety decision support in tunnel construction.” Reliab. Eng. Syst. Saf. 134 (Feb): 157–168. https://doi.org/10.1016/j.ress.2014.10.021.
Xiang, W., and W. Zhou. 2021. “Bayesian network model for predicting probability of third-party damage to underground pipelines and learning model parameters from incomplete datasets.” Reliab. Eng. Syst. Saf. 205 (Jan): 107262. https://doi.org/10.1016/j.ress.2020.107262.
Yazdi, M., and S. Kabir. 2017. “A fuzzy Bayesian network approach for risk analysis in process industries.” Process Saf. Environ. Prot. 111 (Oct): 507–519. https://doi.org/10.1016/j.psep.2017.08.015.
Yu, J. X., S. B. Wu, Y. Yu, H. C. Chen, H. Z. Fan, J. H. Liu, and S. W. Ge. 2021. “Process system failure evaluation method based on a noisy-OR gate intuitionistic fuzzy Bayesian network in an uncertain environment.” Process Saf. Environ. Prot. 150 (Jun): 281–297. https://doi.org/10.1016/j.psep.2021.04.024.
Zhang, G. Z., V. V. Thai, K. F. Yuen, H. S. Loh, and Q. J. Zhou. 2018. “Addressing the epistemic uncertainty in maritime accidents modelling using Bayesian network with interval probabilities.” Saf. Sci. 102 (Feb): 211–225. https://doi.org/10.1016/j.ssci.2017.10.016.
Zhang, J. Z., H. W. Huang, D. M. Zhang, M. L. Zhou, C. Tang, and D. J. Liu. 2021. “Effect of ground surface surcharge on deformational performance of tunnel in spatially variable soil.” Comput. Geotech. 136 (Aug): 104229. https://doi.org/10.1016/j.compgeo.2021.104229.
Zhang, L. M., X. G. Wu, L. Y. Ding, M. J. Skibniewski, and Y. Yan. 2013. “Decision support analysis for safety control in complex project environments based on Bayesian networks.” Expert Syst. Appl. 40 (11): 4273–4282. https://doi.org/10.1016/j.eswa.2012.11.022.
Zhang, L. M., X. G. Wu, Y. W. Qin, M. J. Skibniewski, and W. L. Liu. 2016. “Towards a fuzzy Bayesian network based approach for safety risk analysis of tunnel-induced pipeline damage.” Risk Anal. 36 (2): 278–301. https://doi.org/10.1111/risa.12448.

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Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8Issue 3September 2022

History

Received: Jan 2, 2022
Accepted: Mar 18, 2022
Published online: Jul 12, 2022
Published in print: Sep 1, 2022
Discussion open until: Dec 12, 2022

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Ph.D. Candidate, Key Laboratory of Urban Security and Disaster Engineering, Beijing Univ. of Technology, Beijing 100124, China; Visiting Ph.D. Candidate, Dept. of Civil and Environmental Engineering, National Univ. of Singapore, Singapore 117576. Email: [email protected]
Professor, Dept. of Civil and Environmental Engineering, National Univ. of Singapore, Singapore 117576; Professor, Architecture and Sustainable Design, Singapore Univ. of Technology and Design, Singapore 487372. ORCID: https://orcid.org/0000-0003-2577-8639. Email: [email protected]
Chengshun Xu [email protected]
Professor, Key Laboratory of Urban Security and Disaster Engineering, Beijing Univ. of Technology, Beijing 100124, China (corresponding author). Email: [email protected]
Professor, Key Laboratory of Urban Security and Disaster Engineering, Beijing Univ. of Technology, Beijing 100124, China. Email: [email protected]
Professor, Faculty of Infrastructure Engineering, Dalian Univ. of Technology, Dalian 116024, China. Email: [email protected]

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  • Safety-Risk Transmission Assessment Based on a Factor–Event Network for Metro Construction Projects, Natural Hazards Review, 10.1061/NHREFO.NHENG-1884, 25, 1, (2024).

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