Random field-based tunneling information modeling framework for probabilistic safety assessment of shield tunnels
Abstract
Probabilistic analysis based on random field (RF) has been widely adopted in the safety assessment of shield tunnels. However, its practical applicability has been limited by the intricacy involved with integrating geotechnical data and tunneling information. This paper addresses the following research question: How can the RF-based probabilistic safety assessment be carried out efficiently? In addressing this research question, we suggested an RF-based tunneling information modeling (TIM) framework to realize the probabilistic safety assessment of shield tunnels. In the proposed framework, the modeling of tunnel structure and geological conditions is initially introduced. The numerical safety assessment model is then created via an automated procedure using the RF-based TIM. A case study is conducted to verify the suggested framework, and results demonstrate that the framework can offer an automated design-to-analysis solution to improving the safety assessment of shield tunnels by comprehensively considering the uncertainties of geological conditions.
Keyword : safety assessment, shield tunnel, tunneling information modeling, random field
How to Cite
Xie, P., Luo, H., Chen, K., & Yang, Z. (2023). Random field-based tunneling information modeling framework for probabilistic safety assessment of shield tunnels. Journal of Civil Engineering and Management, 29(8), 741–756. https://doi.org/10.3846/jcem.2023.20428
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Hu, Y., Lei, H., Zheng, G., Shi, L., Zhang, T., Shen, Z., & Jia, R. (2022). Assessing the deformation response of double-track overlapped tunnels using numerical simulation and field monitoring. Journal of Rock Mechanics and Geotechnical Engineering, 14, 436–447. https://doi.org/10.1016/j.jrmge.2021.07.003
Huang, S. P., Quek, S. T., & Phoon, K. K. (2001). Convergence study of the truncated Karhunen-Loeve expansion for simulation of stochastic processes. International Journal for Numerical Methods in Engineering, 52, 1029–1043. https://doi.org/10.1002/nme.255
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Huang, M. Q., Zhu, H. M., Ninić, J., & Zhang, Q. B. (2022). Multi-LOD BIM for underground metro station: Interoperability and design-to-design enhancement. Tunnelling and Underground Space Technology, 119, 104232. https://doi.org/10.1016/j.tust.2021.104232
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Kavvadas, M., Litsas, D., Vazaios, I., & Fortsakis, P. (2017). Development of a 3D finite element model for shield EPB tunnelling. Tunnelling and Underground Space Technology, 65, 22–34. https://doi.org/10.1016/j.tust.2017.02.001
Li, L., Wang, Y., Cao, Z., & Chu, X. (2013). Risk de-aggregation and system reliability analysis of slope stability using representative slip surfaces. Computers and Geotechnics, 53, 95–105. https://doi.org/10.1016/j.compgeo.2013.05.004
Li, D. Q., Jiang, S. H., Cao, Z. J., Zhou, W., Zhou, C. B., & Zhang, L. M. (2015). A multiple response-surface method for slope reliability analysis considering spatial variability of soil properties. Engineering Geology, 187, 60–72. https://doi.org/10.1016/j.enggeo.2014.12.003
Li, Y., Zhang, K., Guo, Z., Yang, L., Ruan, J., & Zhang, L. (2019). Parametric modeling and segment layout of wedge shield tunnel segment based on software CATIA. Tunnel Construction, 39, 391–397 (in Chinese).
Li, T., Gong, W., & Tang, H. (2021). Three-dimensional stochastic geological modeling for probabilistic stability analysis of a circular tunnel face. Tunnelling and Underground Space Technology, 118, 104190. https://doi.org/10.1016/j.tust.2021.104190
Lin, X., Chen, R., Wu, H., & Cheng, H. (2019). Deformation behaviors of existing tunnels caused by shield tunneling undercrossing with oblique angle. Tunnelling and Underground Space Technology, 89, 78–90. https://doi.org/10.1016/j.tust.2019.03.021
Liu, H., Zheng, J., Zhang, R., & Xie, P. (2021a). Probabilistic stability analysis of reinforced soil slope with non-circular RLEM. Geosynthetics International, 30(4), 432–448. https://doi.org/10.1680/jgein.21.00003
Liu, Z., Gu, X., Dong, Q., Tu, S., & Li, S. (2021b). 3D visualization of airport pavement quality based on BIM and WebGL integration. Journal of Transportation Engineering, Part B: Pavements, 147(3), 04021024. https://doi.org/10.1061/JPEODX.0000280
Luo, Z., Atamturktur, S., Juang, C. H., Huang, H., & Lin, P. S. (2011). Probability of serviceability failure in a braced excavation in a spatially random field: Fuzzy finite element approach. Computers and Geotechnics, 38(8), 1031–1040. https://doi.org/10.1016/j.compgeo.2011.07.009
Luo, Z., Li, Y., Zhou, S., & Di, H. (2018). Effects of vertical spatial variability on supported excavations in sands considering multiple geotechnical and structural failure modes. Computers and Geotechnics, 95, 16–29. https://doi.org/10.1016/j.compgeo.2017.11.017
Luo, H., Li, L., & Chen, K. (2022). Parametric modeling for detailed typesetting and deviation correction in shield tunneling construction. Automation in Construction, 134, 104052. https://doi.org/10.1016/j.autcon.2021.104052
Ninić, J., Koch, C., & Stascheit, J. (2017). An integrated platform for design and numerical analysis of shield tunnelling processes on different levels of detail. Advances in Engineering Software, 112, 165–179. https://doi.org/10.1016/j.advengsoft.2017.05.012
Ninić, J., Koch, C., Vonthron, A., Tizani, W., & König, M. (2020). Integrated parametric multi-level information and numerical modelling of mechanised tunnelling projects. Advanced Engineering Informatics, 43, 101011. https://doi.org/10.1016/j.aei.2019.101011
Ninic, J., Alsahly, A., Vonthron, A., Bui, H.G., Koch, C., König, M., Meschke, G., 2021. From digital models to numerical analysis for mechanised tunnelling: A fully automated design-through-analysis workflow. Tunnelling and Underground Space Technology, 107, 103622. https://doi.org/10.1016/j.tust.2020.103622
Pan, D., Xu, Z., Lu, X., Zhou, L., & Li, H. (2020). 3D scene and geological modeling using integrated multi-source spatial data: Methodology, challenges, and suggestions. Tunnelling and Underground Space Technology, 100, 103393. https://doi.org/10.1016/j.tust.2020.103393
Phoon, K. K., Huang, H. W., & Quek, S. T. (2005). Simulation of strongly non-Gaussian processes using Karhunen-Loeve expansion. Probabilistic Engineering Mechanics, 20(2), 188–198. https://doi.org/10.1016/j.probengmech.2005.05.007
Schanz, T., Vermeer, P. A., & Bonnier, P. G. (1999). The hardening soil model: Formulation and verification. In Beyond 2000 in computational geotechnics – Ten Years PLAXIS (pp. 281–296). Balkema. https://doi.org/10.1201/9781315138206-27
Schöberl, J. (1997). An advancing front 2D/3D-mesh generator based on abstract rules. Computing and Visualization in Science, 1, 41–52. https://doi.org/10.1007/s007910050004
Sharafat, A., Khan, M. S., Latif, K., & Seo, J. (2021). BIM-Based tunnel information modeling framework for visualization, management, and simulation of drill-and-blast tunneling projects. Journal of Computing in Civil Engineering, 35, 04020068. HTTPS://DOI.ORG/10.1061/(ASCE)CP.1943-5487.0000955
Shi, J., Wang, F., Huang, H., & Zhang, D. (2023). Horizontal convergence reconstruction in the longitudinal direction for shield tunnels based on conditional random field. Underground Space, 10, 118–136. https://doi.org/10.1016/j.undsp.2022.09.001
Song, Z., Shi, G., Wang, J., Wei, H., Wang, T., & Zhou, G. (2019). Research on management and application of tunnel engineering based on BIM technology. Journal of Civil Engineering and Management, 25(8), 785–797. https://doi.org/10.3846/jcem.2019.11056
Tang, F., Ma, T., Guan, Y., & Zhang, Z. (2020). Parametric modeling and structure verification of asphalt pavement based on BIM-ABAQUS. Automation in Construction, 111, 103066. https://doi.org/10.1016/j.autcon.2019.103066
Vanmarcke, E. (2010). Random fields: Analysis and synthesis. World Scientific. https://doi.org/10.1142/5807
Wu, G., Zhao, H., Zhao, M., & Zhu, Z. (2021a). Stochastic analysis of dual tunnels in spatially random soil. Computers and Geotechnics, 129, 103861. https://doi.org/10.1016/j.compgeo.2020.103861
Wu, Y., Bao, H., Wang, J., & Gao, Y. (2021b). Probabilistic analysis of tunnel convergence on spatially variable soil: The importance of distribution type of soil properties. Tunnelling and Underground Space Technology, 109, 103747. https://doi.org/10.1016/j.tust.2020.103747
Xie, P., Zhang, R., Zheng, J., & Li, Z. (2022). Probabilistic analysis of subway station excavation based on BIM-RF integrated technology. Automation in Construction, 135, 104114. https://doi.org/10.1016/j.autcon.2021.104114
Zakhem, A. M., & El Naggar, H. (2019). Effect of the constitutive material model employed on predictions of the behaviour of earth pressure balance (EPB) shield-driven tunnels. Transportation Geotechnics, 21, 100264. https://doi.org/10.1016/j.trgeo.2019.100264
Zhang, J. Z., Huang, H. W., Zhang, D. M., Phoon, K. K., Liu, Z. Q., & Tang, C. (2021). Quantitative evaluation of geological uncertainty and its influence on tunnel structural performance using improved coupled Markov chain. Acta Geotechnica, 16, 3709–3724. https://doi.org/10.1007/s11440-021-01287-6
Zhang, D. M., Ye, Z. W., Zhang, J. Z., Li, J. P., & Jia, J. W. (2022a). Influence of grouting on rehabilitation of an over-deformed shield tunnel lining in spatially variable soil. Computers and Geotechnics, 152, 104999. https://doi.org/10.1016/j.compgeo.2022.104999
Zhang, J.-Z., Liu, Z.-Q., Zhang, D.-M., Huang, H.-W., Phoon, K.-K., & Xue, Y.-D. (2022b). Improved coupled Markov chain method for simulating geological uncertainty. Engineering Geology, 298, 106539. https://doi.org/10.1016/j.enggeo.2022.106539
Zhang, W., Han, L., Gu, X., Wang, L., Chen, F., & Liu, H. (2022c). Tunneling and deep excavations in spatially variable soil and rock masses: A short review. Underground Space, 7, 380–407. https://doi.org/10.1016/j.undsp.2020.03.003
Zhang, J., Sun, Y., Hu, J.-z., & Huang, H.-w. (2023a). Assessing site investigation program for design of shield tunnels. Underground Space, 9, 31–42. https://doi.org/10.1016/j.undsp.2022.05.002
Zhang, Y., Zhang, J., Wang, C., & Ren, X. (2023b). An integrated framework for improving the efficiency and safety of hydraulic tunnel construction. Tunnelling and Underground Space Technology, 131. https://doi.org/10.1016/j.tust.2022.104836
Zheng, G., Fan, Q., Zhang, T., & Zhang, Q. (2022). Numerical study of the Soil-Tunnel and Tunnel-Tunnel interactions of EPBM overlapping tunnels constructed in soft ground. Tunnelling and Underground Space Technology, 124, 104490. https://doi.org/10.1016/j.tust.2022.104490
Chen, F., Wang, L., & Zhang, W. (2019). Reliability assessment on stability of tunnelling perpendicularly beneath an existing tunnel considering spatial variabilities of rock mass properties. Tunnelling and Underground Space Technology, 88, 276–289. https://doi.org/10.1016/j.tust.2019.03.013
Chen, K., Lu, W., Peng, Y., Rowlinson, S., & Huang, G. Q. (2015). Bridging BIM and building: From a literature review to an integrated conceptual framework. International Journal of Project Management, 33, 1405–1416. https://doi.org/10.1016/j.ijproman.2015.03.006
China Association of Metros. (2022). https://www.camet.org.cn/english.htm
Cho, S. E. (2010). Probabilistic assessment of slope stability that considers the spatial variability of soil properties. Journal of Geotechnical and Geoenvironmental Engineering, 136, 975–984. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000309
El-Ramly, H., Morgenstern, N. R., & Cruden, D. M. (2002). Probabilistic slope stability analysis for practice. Canadian Geotechnical Journal, 39, 665–683. https://doi.org/10.1139/t02-034
Elkateb, T., Chalaturnyk, R., & Robertson, P. K. (2003). An overview of soil heterogeneity: Quantification and implications on geotechnical field problems. Canadian Geotechnical Journal, 40(1), 1–15. https://doi.org/10.1139/t02-090
Fabozzi, S., Biancardo, S. A., Veropalumbo, R., & Bilotta, E. (2021). I-BIM based approach for geotechnical and numerical modelling of a conventional tunnel excavation. Tunnelling and Underground Space Technology, 108, 103723. https://doi.org/10.1016/j.tust.2020.103723
Gong, W., Juang, C. H., Martin, J. R., Tang, H., Wang, Q., & Huang, H. (2018). Probabilistic analysis of tunnel longitudinal performance based upon conditional random field simulation of soil properties. Tunnelling and Underground Space Technology, 73, 1–14. https://doi.org/10.1016/j.tust.2017.11.026
Hu, Y., Lei, H., Zheng, G., Shi, L., Zhang, T., Shen, Z., & Jia, R. (2022). Assessing the deformation response of double-track overlapped tunnels using numerical simulation and field monitoring. Journal of Rock Mechanics and Geotechnical Engineering, 14, 436–447. https://doi.org/10.1016/j.jrmge.2021.07.003
Huang, S. P., Quek, S. T., & Phoon, K. K. (2001). Convergence study of the truncated Karhunen-Loeve expansion for simulation of stochastic processes. International Journal for Numerical Methods in Engineering, 52, 1029–1043. https://doi.org/10.1002/nme.255
Huang, H. W., Xiao, L., Zhang, D. M., & Zhang, J. (2017). Influence of spatial variability of soil Young’s modulus on tunnel convergence in soft soils. Engineering Geology, 228, 357–370. https://doi.org/10.1016/j.enggeo.2017.09.011
Huang, M. Q., Zhu, H. M., Ninić, J., & Zhang, Q. B. (2022). Multi-LOD BIM for underground metro station: Interoperability and design-to-design enhancement. Tunnelling and Underground Space Technology, 119, 104232. https://doi.org/10.1016/j.tust.2021.104232
ISSMGE-TC304. (2021). State-of-the-art review of inherent variability and uncertainty in geotechnical properties and models. International Society of Soil Mechanics and Geotechnical Engineering (ISSMGE) – Technical Committee TC304 “Engineering Practice of Risk Assessment and Management”. https://doi.org/10.53243/R0001
Javankhoshdel, S., & Bathurst, R. J. (2016). Influence of cross correlation between soil parameters on probability of failure of simple cohesive and c- slopes. Canadian Geotechnical Journal, 53, 839–853. https://doi.org/10.1139/cgj-2015-0109
Kavvadas, M., Litsas, D., Vazaios, I., & Fortsakis, P. (2017). Development of a 3D finite element model for shield EPB tunnelling. Tunnelling and Underground Space Technology, 65, 22–34. https://doi.org/10.1016/j.tust.2017.02.001
Li, L., Wang, Y., Cao, Z., & Chu, X. (2013). Risk de-aggregation and system reliability analysis of slope stability using representative slip surfaces. Computers and Geotechnics, 53, 95–105. https://doi.org/10.1016/j.compgeo.2013.05.004
Li, D. Q., Jiang, S. H., Cao, Z. J., Zhou, W., Zhou, C. B., & Zhang, L. M. (2015). A multiple response-surface method for slope reliability analysis considering spatial variability of soil properties. Engineering Geology, 187, 60–72. https://doi.org/10.1016/j.enggeo.2014.12.003
Li, Y., Zhang, K., Guo, Z., Yang, L., Ruan, J., & Zhang, L. (2019). Parametric modeling and segment layout of wedge shield tunnel segment based on software CATIA. Tunnel Construction, 39, 391–397 (in Chinese).
Li, T., Gong, W., & Tang, H. (2021). Three-dimensional stochastic geological modeling for probabilistic stability analysis of a circular tunnel face. Tunnelling and Underground Space Technology, 118, 104190. https://doi.org/10.1016/j.tust.2021.104190
Lin, X., Chen, R., Wu, H., & Cheng, H. (2019). Deformation behaviors of existing tunnels caused by shield tunneling undercrossing with oblique angle. Tunnelling and Underground Space Technology, 89, 78–90. https://doi.org/10.1016/j.tust.2019.03.021
Liu, H., Zheng, J., Zhang, R., & Xie, P. (2021a). Probabilistic stability analysis of reinforced soil slope with non-circular RLEM. Geosynthetics International, 30(4), 432–448. https://doi.org/10.1680/jgein.21.00003
Liu, Z., Gu, X., Dong, Q., Tu, S., & Li, S. (2021b). 3D visualization of airport pavement quality based on BIM and WebGL integration. Journal of Transportation Engineering, Part B: Pavements, 147(3), 04021024. https://doi.org/10.1061/JPEODX.0000280
Luo, Z., Atamturktur, S., Juang, C. H., Huang, H., & Lin, P. S. (2011). Probability of serviceability failure in a braced excavation in a spatially random field: Fuzzy finite element approach. Computers and Geotechnics, 38(8), 1031–1040. https://doi.org/10.1016/j.compgeo.2011.07.009
Luo, Z., Li, Y., Zhou, S., & Di, H. (2018). Effects of vertical spatial variability on supported excavations in sands considering multiple geotechnical and structural failure modes. Computers and Geotechnics, 95, 16–29. https://doi.org/10.1016/j.compgeo.2017.11.017
Luo, H., Li, L., & Chen, K. (2022). Parametric modeling for detailed typesetting and deviation correction in shield tunneling construction. Automation in Construction, 134, 104052. https://doi.org/10.1016/j.autcon.2021.104052
Ninić, J., Koch, C., & Stascheit, J. (2017). An integrated platform for design and numerical analysis of shield tunnelling processes on different levels of detail. Advances in Engineering Software, 112, 165–179. https://doi.org/10.1016/j.advengsoft.2017.05.012
Ninić, J., Koch, C., Vonthron, A., Tizani, W., & König, M. (2020). Integrated parametric multi-level information and numerical modelling of mechanised tunnelling projects. Advanced Engineering Informatics, 43, 101011. https://doi.org/10.1016/j.aei.2019.101011
Ninic, J., Alsahly, A., Vonthron, A., Bui, H.G., Koch, C., König, M., Meschke, G., 2021. From digital models to numerical analysis for mechanised tunnelling: A fully automated design-through-analysis workflow. Tunnelling and Underground Space Technology, 107, 103622. https://doi.org/10.1016/j.tust.2020.103622
Pan, D., Xu, Z., Lu, X., Zhou, L., & Li, H. (2020). 3D scene and geological modeling using integrated multi-source spatial data: Methodology, challenges, and suggestions. Tunnelling and Underground Space Technology, 100, 103393. https://doi.org/10.1016/j.tust.2020.103393
Phoon, K. K., Huang, H. W., & Quek, S. T. (2005). Simulation of strongly non-Gaussian processes using Karhunen-Loeve expansion. Probabilistic Engineering Mechanics, 20(2), 188–198. https://doi.org/10.1016/j.probengmech.2005.05.007
Schanz, T., Vermeer, P. A., & Bonnier, P. G. (1999). The hardening soil model: Formulation and verification. In Beyond 2000 in computational geotechnics – Ten Years PLAXIS (pp. 281–296). Balkema. https://doi.org/10.1201/9781315138206-27
Schöberl, J. (1997). An advancing front 2D/3D-mesh generator based on abstract rules. Computing and Visualization in Science, 1, 41–52. https://doi.org/10.1007/s007910050004
Sharafat, A., Khan, M. S., Latif, K., & Seo, J. (2021). BIM-Based tunnel information modeling framework for visualization, management, and simulation of drill-and-blast tunneling projects. Journal of Computing in Civil Engineering, 35, 04020068. HTTPS://DOI.ORG/10.1061/(ASCE)CP.1943-5487.0000955
Shi, J., Wang, F., Huang, H., & Zhang, D. (2023). Horizontal convergence reconstruction in the longitudinal direction for shield tunnels based on conditional random field. Underground Space, 10, 118–136. https://doi.org/10.1016/j.undsp.2022.09.001
Song, Z., Shi, G., Wang, J., Wei, H., Wang, T., & Zhou, G. (2019). Research on management and application of tunnel engineering based on BIM technology. Journal of Civil Engineering and Management, 25(8), 785–797. https://doi.org/10.3846/jcem.2019.11056
Tang, F., Ma, T., Guan, Y., & Zhang, Z. (2020). Parametric modeling and structure verification of asphalt pavement based on BIM-ABAQUS. Automation in Construction, 111, 103066. https://doi.org/10.1016/j.autcon.2019.103066
Vanmarcke, E. (2010). Random fields: Analysis and synthesis. World Scientific. https://doi.org/10.1142/5807
Wu, G., Zhao, H., Zhao, M., & Zhu, Z. (2021a). Stochastic analysis of dual tunnels in spatially random soil. Computers and Geotechnics, 129, 103861. https://doi.org/10.1016/j.compgeo.2020.103861
Wu, Y., Bao, H., Wang, J., & Gao, Y. (2021b). Probabilistic analysis of tunnel convergence on spatially variable soil: The importance of distribution type of soil properties. Tunnelling and Underground Space Technology, 109, 103747. https://doi.org/10.1016/j.tust.2020.103747
Xie, P., Zhang, R., Zheng, J., & Li, Z. (2022). Probabilistic analysis of subway station excavation based on BIM-RF integrated technology. Automation in Construction, 135, 104114. https://doi.org/10.1016/j.autcon.2021.104114
Zakhem, A. M., & El Naggar, H. (2019). Effect of the constitutive material model employed on predictions of the behaviour of earth pressure balance (EPB) shield-driven tunnels. Transportation Geotechnics, 21, 100264. https://doi.org/10.1016/j.trgeo.2019.100264
Zhang, J. Z., Huang, H. W., Zhang, D. M., Phoon, K. K., Liu, Z. Q., & Tang, C. (2021). Quantitative evaluation of geological uncertainty and its influence on tunnel structural performance using improved coupled Markov chain. Acta Geotechnica, 16, 3709–3724. https://doi.org/10.1007/s11440-021-01287-6
Zhang, D. M., Ye, Z. W., Zhang, J. Z., Li, J. P., & Jia, J. W. (2022a). Influence of grouting on rehabilitation of an over-deformed shield tunnel lining in spatially variable soil. Computers and Geotechnics, 152, 104999. https://doi.org/10.1016/j.compgeo.2022.104999
Zhang, J.-Z., Liu, Z.-Q., Zhang, D.-M., Huang, H.-W., Phoon, K.-K., & Xue, Y.-D. (2022b). Improved coupled Markov chain method for simulating geological uncertainty. Engineering Geology, 298, 106539. https://doi.org/10.1016/j.enggeo.2022.106539
Zhang, W., Han, L., Gu, X., Wang, L., Chen, F., & Liu, H. (2022c). Tunneling and deep excavations in spatially variable soil and rock masses: A short review. Underground Space, 7, 380–407. https://doi.org/10.1016/j.undsp.2020.03.003
Zhang, J., Sun, Y., Hu, J.-z., & Huang, H.-w. (2023a). Assessing site investigation program for design of shield tunnels. Underground Space, 9, 31–42. https://doi.org/10.1016/j.undsp.2022.05.002
Zhang, Y., Zhang, J., Wang, C., & Ren, X. (2023b). An integrated framework for improving the efficiency and safety of hydraulic tunnel construction. Tunnelling and Underground Space Technology, 131. https://doi.org/10.1016/j.tust.2022.104836
Zheng, G., Fan, Q., Zhang, T., & Zhang, Q. (2022). Numerical study of the Soil-Tunnel and Tunnel-Tunnel interactions of EPBM overlapping tunnels constructed in soft ground. Tunnelling and Underground Space Technology, 124, 104490. https://doi.org/10.1016/j.tust.2022.104490