Real-Time Risk Assessment of Tunneling-Induced Building Damage Considering Polymorphic Uncertainty
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 1
Abstract
The risk assessment of tunneling-induced damage in buildings is a challenging task in geotechnical and structural engineering. It is important to consider the soil–structure interaction during the tunnel construction process. In this paper, finite-element (FE) simulation models of mechanized tunneling processes are combined with FE models of buildings to predict tunneling-induced damage. The soil–structure interaction is taken into account by considering the building stiffness in the tunneling process simulation model and by applying the computed foundation settlements as boundary conditions of the building model. The building damage risk is assessed by means of strains in the structural members and a corresponding category of damage is determined. Uncertainties of the geotechnical parameters and the structural parameters are quantified as random variables and intervals in the framework of polymorphic uncertainty modeling. For real-time predictions, the FE simulation models are approximated by artificial neural networks. This makes it possible to predict the structural damage risk according to scenarios of the operational tunneling process parameters in order to assist machine drivers during tunnel construction.
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Data Availability Statement
The data sets, which are used for the establishment of artificial neural networks in this study, are available from the corresponding author upon reasonable request.
Acknowledgments
This research was funded by the Deutsche Forschungsgemeinschaft (DFG) (German Research Foundation), Project 77309832 within Subprojects C1 and D3 of the Collaborative Research Center SFB 837 “Interaction Modeling in Mechanized Tunnelling.”
References
Adeli, H. 2001. “Neural networks in civil engineering: 1989–2000.” Comput.-Aided Civ. Infrastruct. Eng. 16 (2): 126–142. https://doi.org/10.1111/0885-9507.00219.
Alsahly, A., J. Stascheit, and G. Meschke. 2016. “Advanced finite element modeling of excavation and advancement processes in mechanized tunneling.” Adv. Eng. Software 100 (Oct): 198–214. https://doi.org/10.1016/j.advengsoft.2016.07.011.
Asher, M. J., B. F. W. Croke, A. J. Jakeman, and L. J. M. Peeters. 2015. “A review of surrogate models and their application to groundwater modeling.” Water Resour. Res. 51 (8): 5957–5973. https://doi.org/10.1002/2015WR016967.
Backes, H.-P. 1985. “Zugfestigkeit von Mauerwerk und Verformungsverhalten unter Zugbeanspruchung.” In Mauerwerk Kalender, 719–725. Berlin: Ernst und Sohn.
Bilotta, E., A. Paolillo, G. Russo, and S. Aversa. 2017. “Displacements induced by tunnelling under a historical building.” Tunnelling Underground Space Technol. 61 (Jan): 221–232. https://doi.org/10.1016/j.tust.2016.10.007.
Boscardin, M. D., and E. J. Cording. 1989. “Building response to excavation–induced settlement.” J. Geotech. Eng. 115 (1): 1–21. https://doi.org/10.1061/(ASCE)0733-9410(1989)115:1(1).
Bui, H. G., D. Schillinger, and G. Meschke. 2020. “Efficient cut-cell quadrature based on moment fitting for materially nonlinear analysis.” Comput. Method Appl. Mech. Eng. 366 (May): 113050. https://doi.org/10.1016/j.cma.2020.113050.
Burland, J. B., and C. P. Wroth. 1975. “Settlement of buildings and associated damage.” In Settlement of structures, 611–654. London: Pentech Press.
Cao, B., S. Freitag, and G. Meschke. 2016. “A hybrid RNN-GPOD surrogate model for real-time settlement predictions in mechanised tunnelling.” Adv. Model. Simul. Eng. Sci. 3 (1): 1–22. https://doi.org/10.1186/s40323-016-0057-9.
Cao, B., S. Freitag, and G. Meschke. 2018. “A fuzzy surrogate modelling approach for real-time settlement predictions in mechanised tunnelling.” Int. J. Reliab. Saf. 12 (1/2): 187–217. https://doi.org/10.1504/IJRS.2018.092521.
Cao, B. T., M. Obel, S. Freitag, P. Mark, and G. Meschke. 2020. “Artificial neural network surrogate modelling for real-time predictions and control of building damage during mechanised tunnelling.” Adv. Eng. Software 149 (Jun): 102869. https://doi.org/10.1016/j.advengsoft.2020.102869.
CEN (European Committee for Standardization). 2011. Eurocode 2—Design of concrete structures—Part 1-1: General rules and rules for buildings. DIN EN 1992-1-1. Brussels, Belgium: CEN.
Comerford, L., I. A. Kougioumtzoglou, and M. Beer. 2015. “An artificial neural network approach for stochastic process power spectrum estimation subject to missing data.” Struct. Saf. 52 (Jan): 150–160. https://doi.org/10.1016/j.strusafe.2014.10.001.
Do, D. M., K. Gao, W. Yang, and C.-Q. Lia. 2020. “Hybrid uncertainty analysis of functionally graded plates via multiple-imprecise-random-field modelling of uncertain material properties.” Comput. Methods Appl. Mech. Eng. 368 (Aug): 113116. https://doi.org/10.1016/j.cma.2020.113116.
Do, N., D. Dias, P. Oreste, and I. Djeran-Maigre. 2014. “Three-dimensional numerical simulation for mechanized tunnelling in soft ground: The influence of the joint pattern.” Acta Geotech. 9 (4): 673–694. https://doi.org/10.1007/s11440-013-0279-7.
Dong, L., D. Sun, X. Li, J. Ma, L. Zhang, and X. Tong. 2018. “Interval non-probabilistic reliability of surrounding jointed rockmass considering microseismic loads in mining tunnels.” Tunnelling Underground Space Technol. 81 (Jul): 326–335. https://doi.org/10.1016/j.tust.2018.06.034.
Elman, J. 1990. “Finding structure in time.” Cognit. Sci. 14 (2): 179–211. https://doi.org/10.1207/s15516709cog1402_1.
Faes, M. G., A. M. Valdebenito, D. Moens, and M. Beer. 2021. “Operator norm theory as an efficient tool to propagate hybrid uncertainties and calculate imprecise probabilities.” Mech. Syst. Sig. Process. 152 (May): 107482. https://doi.org/10.1016/j.ymssp.2020.107482.
Fargnoli, V., C. G. Gragnano, D. Boldini, and A. Amorosi. 2015. “3D numerical modelling of soil–structure interaction during EPB tunnelling.” Géotechnique 65 (1): 23–37. https://doi.org/10.1680/geot.14.P.091.
Ferson, S., V. Kreinovich, L. Ginzburg, D. S. Myers, and K. Sentz. 2003. Constructing probability boxes and Dempster-Shafer structures. Albuquerque, NM: Sandia National Laboratories.
fib (Fédération internationale du béton). 2010. Model code for concrete structures 2010: First complete draft: fib Bulletin No. 65. Lausanne, Switzerland: fib.
Fina, M., L. Panther, P. Weber, and W. Wagner. 2021. “Shell buckling with polymorphic uncertain surface imperfections and sensitivity analysis.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part B: Mech. Eng. 7 (2): 020909. https://doi.org/10.1115/1.4050165.
Freitag, S., M. Beer, K. Phoon, J. Stascheit, J. Ninić, B. Cao, and G. Meschke. 2013. “Concepts for reliability analyses in mechanised tunnelling—Part 1: Theory.” In Proc., 3rd Int. Conf. on Computational Methods in Tunnelling and Subsurface Engineering (EURO:TUN 2013), edited by G. Meschke, J. Eberhardsteiner, T. Schanz, K. Soga, and M. Thewes, 791–799. Bochum, Germany: Aedificatio Publishers.
Freitag, S., B. Cao, J. Ninic, and G. Meschke. 2018. “Recurrent neural networks and proper orthogonal decomposition with interval data for real-time predictions of mechanised tunnelling processes.” Comput. Struct. 207 (Sep): 258–273. https://doi.org/10.1016/j.compstruc.2017.03.020.
Freitag, S., B. T. Cao, J. Ninić, and G. Meschke. 2015. “Hybrid surrogate modelling for mechanised tunnelling simulations with uncertain data.” Int. J. Reliab. Saf. 9 (2/3): 154–173. https://doi.org/10.1504/IJRS.2015.072717.
Freitag, S., P. Edler, K. Kremer, and G. Meschke. 2020. “Multilevel surrogate modeling approach for optimization problems with polymorphic uncertain parameters.” Int. J. Approximate Reasoning 119 (Apr): 81–91. https://doi.org/10.1016/j.ijar.2019.12.015.
Freitag, S., W. Graf, and M. Kaliske. 2011. “Recurrent neural networks for fuzzy data.” Integr. Comput.-Aided Eng. 18 (3): 265–280. https://doi.org/10.3233/ICA-2011-0373.
Glock, C. 2004. “Load-bearing capacity of unreinforced concrete and masonry walls.” Ph.D. thesis, Dept. of Civil and Environmental Engineering, Technical Univ. Darmstadt.
Graf, W., M. Götz, and M. Kaliske. 2015. “Analysis of dynamical processes under consideration of polymorphic uncertainty.” Struct. Saf. 52 (Jan): 194–201. https://doi.org/10.1016/j.strusafe.2014.09.003.
JCSS (Joint Committee on Structural Safety). 2001. Probabilities model code. Tokyo: JCSS.
Jiang, S.-H., D.-Q. Li, Z.-J. Cao, C.-B. Zhou, and K.-K. Phoon. 2015. “Efficient system reliability analysis of slope stability in spatially variable soils using Monte Carlo simulation.” J. Geotech. Geoenviron. Eng. 141 (2): 04014096. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001227.
Kasper, T., and G. Meschke. 2004. “A 3D finite element model for TBM tunneling in soft ground.” Int. J. Numer. Anal. Methods Geomech. 28 (14): 1441–1460. https://doi.org/10.1002/nag.395.
Kupfer, H. B., K. H. Gerstle, and H. Rusch. 1973. “Behavior of concrete under biaxial stresses.” J. Eng. Mech. Div. 99 (4): 853–866. https://doi.org/10.1061/JMCEA3.0001789.
Liu, X., X. Wang, J. Xie, and B. Li. 2020. “Construction of probability box model based on maximum entropy principle and corresponding hybrid reliability analysis approach.” Struct. Multidiscip. Optim. 61 (2): 599–617. https://doi.org/10.1007/s00158-019-02382-9.
Lu, Q., Z. Xiao, J. Zheng, and Y. Shang. 2018. “Probabilistic assessment of tunnel convergence considering spatial variability in rock mass properties using interpolated autocorrelation and response surface method.” Geosci. Front. 9 (6): 1619–1629. https://doi.org/10.1016/j.gsf.2017.08.007.
Maidl, B., M. Herrenknecht, U. Maidl, and G. Wehrmeyer. 2011. Mechanised shield tunnelling. 2nd ed. Berlin: Wiley.
Mark, P., and B. Schnütgen. 2001. “Limits of elastic material behaviour of concrete.” Beton- Stahlbetonbau 96 (5): 373–378. https://doi.org/10.1002/best.200100400.
Möller, B., and M. Beer. 2008. “Engineering computation under uncertainty—Capabilities of non-traditional models.” Comput. Struct. 86 (10): 1024–1041. https://doi.org/10.1016/j.compstruc.2007.05.041.
Möller, B., W. Graf, and M. Beer. 2000. “Fuzzy structural analysis using -level optimization.” Comput. Mech. 26 (6): 547–565. https://doi.org/10.1007/s004660000204.
Nagel, F., J. Stascheit, and G. Meschke. 2010. “Process-oriented numerical simulation of shield tunneling in soft soils.” Geomech. Tunnelling 3 (3): 268–282. https://doi.org/10.1002/geot.201000024.
Neuhausen, M., M. Obel, A. Martin, P. Mark, and M. König. 2018. “Window detection in facade images for risk assessment in tunneling.” Visualization Eng. 6 (1): 129. https://doi.org/10.1186/s40327-018-0062-9.
Ninić, J., S. Freitag, and G. Meschke. 2017. “A hybrid finite element and surrogate modelling approach for simulation and monitoring supported TBM steering.” Tunnelling Underground Space Technol. 63 (Mar): 12–28. https://doi.org/10.1016/j.tust.2016.12.004.
Ninić, J., J. Stascheit, and G. Meschke. 2014. “Beam-solid contact formulation for finite element analysis of pile-soil interaction with arbitrary discretization.” Int. J. Numer. Anal. Methods Geomech. 38 (14): 1453–1476. https://doi.org/10.1002/nag.2262.
Obel, M., M. A. Ahrens, and P. Mark. 2020. “Metamodel-based risk analysis of structural damages due to tunneling-induced settlements.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 88 (12): 1–12. https://doi.org/10.1061/AJRUA6.0001092.
Obel, M., A. Marwan, A. Alsahly, S. Freitag, P. Mark, and G. Meschke. 2018. “Damage assessment concepts for urban structures during mechanized tunneling.” Bauingenieur 93 (12): 482–491. https://doi.org/10.37544/0005-6650-2018-12-44.
Obel, M., D. Sanio, and P. Mark. 2019. “Screening methods to reduce complex models of existing structures.” ce/papers 3 (2): 61–67. https://doi.org/10.1002/cepa.983.
Ostrowski, Z., R. Bialecki, and A. Kassab. 2008. “Solving inverse heat conduction problems using trained pod-rbf network inverse method.” Inverse Prob. Sci. Eng. 16 (1): 39–54. https://doi.org/10.1080/17415970701198290.
Park, H. I., and S. R. Lee. 2011. “Evaluation of the compression index of soils using an artificial neural network.” Comput. Geotech. 38 (4): 472–481. https://doi.org/10.1016/j.compgeo.2011.02.011.
Pasternak, P. L. 1954. “On a new method of analysis of an elastic foundation by means of two foundation constants.” Gosudarstvennoe Izdatelstvo Literaturi Po Stroitelstvu I Arkhitekture 1: 1–56.
Schindler, S. 2014. “Monitoringbasierte strukturmechanische Schadensanalyse von Bauwerken beim Tunnelbau.” Ph.D. thesis, Dept. of Civil and Environmental Engineering, Ruhr Univ. Bochum.
Schöbi, R., and B. Sudret. 2019. “Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions.” Reliability Eng. Syst. Saf. 187 (July): 129–141. https://doi.org/10.1016/j.ress.2018.11.021.
Shi, Y., and R. Eberhart. 1998. “Parameter selection in particle swarm optimization.” In Proc., 7th Int. Conf. on Evolutionary Programming VII, edited by V. W. Porto, N. Saravanan, D. Waagen, and A. E. Eiben, 591–600. Berlin: Springer.
Son, M. 2015. “Response analysis of nearby structures to tunneling-induced ground movements in sandy soils.” Tunnelling Underground Space Technol. 48 (Apr): 156–169. https://doi.org/10.1016/j.tust.2015.03.008.
Song, J., P. Wei, M. Valdebenito, S. Bi, M. Broggi, M. Beer, and Z. Lei. 2019. “Generalization of non-intrusive imprecise stochastic simulation for mixed uncertain variables.” Mech. Syst. Sig. Process. 134 (Dec): 106316. https://doi.org/10.1016/j.ymssp.2019.106316.
Sudret, B. 2012. “Meta-models for structural reliability and uncertainty quantification.” In Proc., Fifth Asian-Pacific Symp. on Structural Reliability and Its Applications (5th APSSRA), edited by K. K. Phoon, M. Beer, S. T. Quek, and S. D. Pang. Singapore: Research Publishing.
Wang, X., S. Li, Z. Xu, X. Li, P. Lin, and C. Lin. 2019. “An interval risk assessment method and management of water inflow and inrush in course of karst tunnel excavation.” Tunnelling Underground Space Technol. 92 (Oct): 103033. https://doi.org/10.1016/j.tust.2019.103033.
Yiu, W. N., H. J. Burd, and C. M. Martin. 2017. “Finite-element modelling for the assessment of tunnel-induced damage to a masonry building.” Géotechnique 67 (9): 1–15. https://doi.org/10.1680/jgeot.sip17.P.249.
Yu, H., and B. M. Wilamowski. 2011. “Levenberg-Marquardt Training.” In Chap. 12 of Industrial electronics handbook, 2nd ed., 1–15. Boca Raton, FL: CRC Press.
Zhang, J., H. W. Huang, and K. K. Phoon. 2013. “Application of the Kriging-based response surface method to the system reliability of soil slopes.” J. Geotech. Geoenviron. Eng. 139 (4): 651–655. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000801.
Zhao, C., A. Alimardani Lavasan, T. Barciaga, C. Kämper, P. Mark, and T. Schanz. 2017. “Prediction of tunnel lining forces and deformations using analytical and numerical solutions.” Tunnelling Underground Space Technol. 64 (Apr): 164–176. https://doi.org/10.1016/j.tust.2017.01.015.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8 • Issue 1 • March 2022
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© 2021 American Society of Civil Engineers.
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Received: May 17, 2021
Accepted: Aug 13, 2021
Published online: Oct 19, 2021
Published in print: Mar 1, 2022
Discussion open until: Mar 19, 2022
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