Earthquakes and Structures

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Correlated damage probabilities of bridges in seismic risk assessment of transportation networks: Case study, Tehran

  • Shahin Borzoo (Lifeline Earthquake Engineering Department, International Institute of Earthquake Engineering and Seismology) ;
  • Morteza Bastami (Lifeline Earthquake Engineering Department, International Institute of Earthquake Engineering and Seismology) ;
  • Afshin Fallah (Department of Statistics, Imam Khomeini International University) ;
  • Alireza Garakaninezhad (Department of Civil Engineering, Faculty of Engineering, University of Jiroft) ;
  • Morteza Abbasnejadfard (Lifeline Earthquake Engineering Department, International Institute of Earthquake Engineering and Seismology)
  • Received : 2023.02.12
  • Accepted : 2023.12.18
  • Published : 2024.02.25
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Abstract

This paper proposes a logistic multinomial regression approach to model the spatial cross-correlation of damage probabilities among different damage states in an expanded transportation network. Utilizing Bayesian theory and the multinomial logistic model, we analyze the damage states and probabilities of bridges while incorporating damage correlation. This correlation is considered both between bridges in a network and within each bridge's damage states. The correlation model of damage probabilities is applied to the seismic assessment of a portion of Tehran's transportation network, encompassing 26 bridges. Additionally, we introduce extra daily traffic time (EDTT) as an operational parameter of the transportation network and employ the shortest path algorithm to determine the path between two nodes. Our results demonstrate that incorporating the correlation of damage probabilities reduces the travel time of the selected network. The average decrease in travel time for the correlated case compared to the uncorrelated case, using two selected EDTT models, is 53% and 71%, respectively.

Keywords

Acknowledgement

The authors would like to acknowledge the International Institute of Earthquake Engineering and Seismology (IIEES) for providing research documents and financial support.

References

  1. Abbasnejadfard, M., Bastami, M. and Fallah, A. (2020), "Investigation of anisotropic spatial correlations of intra-event residuals of multiple earthquake intensity measures using latent dimensions method", Geophys. J. Int., 222(2), 1449-1469. https://doi.org/10.1093/gji/ggaa255.
  2. Abbasnejadfard, M., Bastami, M. and Fallah, A. (2021), "Investigating the spatial correlations in univariate random fields of peak ground velocity and peak ground displacement considering anisotropy", Geoenviron. Disasters, 8(1), 1-16. https://doi.org/10.1186/s40677-021-00196-w.
  3. Abbasnejadfard, M., Bastami, M., Fallah, A. and Garakaninezhad, A. (2021), "Analyzing the effect of anisotropic spatial correlations of earthquake intensity measures on the result of seismic risk and resilience assessment of the portfolio of buildings and infrastructure systems", Bull. Earthq. Eng., 19(14), 5791-5817. https://doi.org/10.1007/s10518-021-01203-z.
  4. Adachi, T. and Ellingwood, B.R. (2008), "Serviceability of earthquake-damaged water systems: Effects of electrical power availability and power backup systems on system vulnerability", Reliab. Eng. Syst. Saf., 93(1), 78-88. https://doi.org/10.1016/j.ress.2006.10.014.
  5. Argyroudis, S.A., Mitoulis, S.A., Winter, M.G. and Kaynia, A.M. (2019), "Fragility of transport assets exposed to multiple hazards: State-of-the-art review toward infrastructural resilience", Reliab. Eng. Syst. Saf., 191, 106567. https://doi.org/10.1016/j.ress.2019.106567.
  6. Bastami, M. and Kowsari, M. (2014), "Seismicity and seismic hazard assessment for greater Tehran region using Gumbel first asymptotic distribution", Struct. Eng. Mech., 49(3), 355-372. http://doi.org/10.12989/sem.2014.49.3.355.
  7. Bhattacharjee, G. and Baker, J.W. (2021), "Using global variancebased sensitivity analysis to prioritize bridge retrofits in a regional road network subject to seismic hazard", Struct. Infrastr. Eng., 19(2), 164-177. https://doi.org/10.1080/15732479.2021.1931892.
  8. Bocchini, P. and Frangopol, D.M. (2011), "A stochastic computational framework for the joint transportation network fragility analysis and traffic flow distribution under extreme events", Probab. Eng.Mech., 26(2), 182-193. https://doi.org/10.1016/j.probengmech.2010.11.007.
  9. Borzoo, S., Bastami, M. and Fallah, A. (2020a), "Extreme scenarios selection for seismic assessment of expanded lifeline networks", Struct. Infrastr. Eng., 17(10), 1386-1403. https://doi.org/10.1080/15732479.2020.1811989
  10. Borzoo, S., Bastami, M. and Fallah, A. (2020b), "Modeling extreme ground-motion intensities using extreme value theory", Pure Appl. Geophys., 177(10), 4691-4706. https://doi.org/10.1007/s00024-020-02519-8.
  11. Cressie, N. (2015), Statistics for Spatial Data, John Wiley & Sons, Hoboken, NJ, USA.
  12. D'Amato, M., Laguardia, R., Di Trocchio, G., Coltellacci, M. and Gigliotti, R. (2022), "Seismic risk assessment for masonry buildings typologies from L'Aquila 2009 earthquake damage data", J. Earthq. Eng., 26(9), 4545-4579. https://doi.org/10.1080/13632469.2020.1835750.
  13. Dijkstra, E. (1959), Dijkstra's algorithm; Wikipedia®, San Francisco, CA, USA. http://en.wikipedia.org/wiki/dijkstra_algorithm
  14. Dong, Y. and Frangopol, D.M. (2017), "Probabilistic assessment of an interdependent healthcare--bridge network system under seismic hazard", Struct. Infrastr. Eng., 13(1), 160-170. https://doi.org/10.1080/15732479.2016.1198399
  15. Dong, Y., Frangopol, D.M. and Saydam, D. (2014), "Sustainability of highway bridge networks under seismic hazard", J. Earthq. Eng., 18(1), 41-66. https://doi.org/10.1080/13632469.2013.841600.
  16. Erdik, M. (2017), "Earthquake risk assessment", Bull. Earthq. Eng., 15(12), 5055-5092. https://doi.org/10.1007/s10518-017-0235-2.
  17. FEMA (2018), Multi-hazard Loss Estimation Methodology: Earthquake Model, Department of Homeland Security, FEMA, Washington, D.C., USA.
  18. Garakaninezhad, A. (2018), "Development of spatial statistics methods to evaluate seismic vulnerability of lifeline networks", International Institute of Earthquake Engineering and Seismology (IIEES), Tehran, Iran.
  19. Garakaninezhad, A. and Bastami, M. (2017), "A novel spatial correlation model based on anisotropy of earthquake groundmotion intensity", Bull. Seismol. Soc. Am., 107(6), 2809-2820. https://doi.org/10.1785/0120160367.
  20. Garakaninezhad, A., Bastami, M. and Soghrat, M.R. (2017), "Spatial correlation for horizontal and vertical components of acceleration from northern Iran seismic events", J. Seismol., 21(6), 1505-1516. https://doi.org/10.1007/s10950-017-9679-8.
  21. Gelman, A., Carlin, J.B., Stern, H.S. and Rubin, D.B. (1995), Bayesian Data Analysis, Chapman and Hall/CRC, Boca Raton, FL, USA.
  22. Gomez, C. and Baker, J.W. (2019), "An optimization-based decision support framework for coupled pre-and postearthquake infrastructure risk management", Struct. Saf., 77, 1-9. https://doi.org/10.1016/j.strusafe.2018.10.002.
  23. Gordon, P., Moore, J.E., Richardson, H.W., Shinozuka, M., An, D. and Cho, S. (2004), "Earthquake disaster mitigation for urban transportation systems: An integrated methodology that builds on the Kobe and Northridge experiences", Modeling Spatial and Economic Impacts of Disasters, Springer Berlin, Heidelberg, Germany.
  24. Hastings, W.K. (1970), "Monte Carlo sampling methods using Markov chains and their applications", Biomet., 57(1), 97-109. https://doi.org/10.1093/biomet/57.1.97.
  25. Jayaram, N. and Baker, J. (2010a), Probabilistic Seismic Lifeline Risk Assessment Using Efficient Sampling and Data Reduction Techniques, Stanford University, Stanford, CA, USA.
  26. Jayaram, N. and Baker, J.W. (2009), "Correlation model for spatially distributed ground-motion intensities", Earthq. Eng. Struct. Dyn., 38(15), 1687-1708. https://doi.org/10.1002/eqe.922.
  27. Jayaram, N. and Baker, J. W. (2010b), "Efficient sampling and data reduction techniques for probabilistic seismic lifeline risk assessment", Earthq. Eng. Struct. Dyn., 39(10), 1109-1131. https://doi.org/10.1002/eqe.988.
  28. Kavousi, A., Fallah, A. and Meshkani, M.R. (2013), "Spatial analysis of air pollution in tehran city by a Bayesian autobinomial model", J. Basic Appl. Sci. Res., 3(2), 961-968.
  29. Laguardia, R., D'Amato, M., Coltellacci, M., Di Trocchio, G. and Gigliotti, R. (2023), "Fragility curves and economic loss assessment of RC buildings after L'Aquila 2009 earthquake", J. Earthq. Eng., 27(5), 1126-1150. https://doi.org/10.1080/13632469.2022.2038726.
  30. Lee, H.L. and Cohen, M.A. (1985), "A multinomial logit model for the spatial distribution of hospital utilization", J. Bus. Econ. Stat., 3(2), 159-168. https://doi.org/10.1080/07350015.1985.10509445.
  31. Lee, R. and Kiremidjian, A.S. (2007), "Uncertainty and correlation for loss assessment of spatially distributed systems", Earthq. Spectra, 23(4), 753-770. https://doi.org/10.1193/1.2791001.
  32. Lin, Y., Deng, X., Li, X. and Ma, E. (2014), "Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?", Front. Earth Sci., 8(4), 512-523. https://doi.org/10.1007/s11707-014-0426-y.
  33. Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H. and Teller, E. (1953), "Equation of state calculations by fast computing machines", J. Chem. Phys., 21(6), 1087-1092. https://doi.org/10.1063/1.1699114.
  34. Miller, M. and Baker, J. (2015), "Ground-motion intensity and damage map selection for probabilistic infrastructure network risk assessment using optimization", Earthq. Eng. Struct. Dyn., 44(7), 1139-1156. https://doi.org/10.1002/eqe.2506.
  35. Mohammadian, A. and Kanaroglou, P.S. (2003), "Applications of spatial multinomial logit model to transportation planning", Proceedings of the 10th International Conference on Travel Behaviour Research, Lucerne, Switzerland, August.
  36. Murphy, K.P. (2006), "Binomial and multinomial distributions", Tech. Rep. University of British Columbia, Vancouver, BC, Canada.
  37. Park, J., Bazzurro, P., Baker, J.W., & others. (2007), "Modeling spatial correlation of ground motion intensity measures for regional seismic hazard and portfolio loss estimation", Appl. Stat. Probab. Civil Eng., 2, 1-8.
  38. Rokneddin, K., Ghosh, J., Duenas-Osorio, L. and Padgett, J.E. (2014), "Seismic reliability assessment of aging highway bridge networks with field instrumentation data and correlated failures, II: Application", Earthq. Spectra, 30(2), 819-843. https://doi.org/10.1193/040612EQS160M.
  39. Shinozuka, M., Murachi, Y., Dong, X., Zhou, Y. and Orlikowski, M.J. (2003), "Seismic performance of highway transportation networks", Proceedings of China-US Workshop on Protection of Urban Infrastructure and Public Buildings against Earthquakes and Man-Made Disasters, Beijing, China, February.
  40. Shiraki, N., Shinozuka, M., Moore, J.E., Chang, S.E., Kameda, H. and Tanaka, S. (2007), "System risk curves: Probabilistic performance scenarios for highway networks subject to earthquake damage", J. Infrastr. Syst., 13(1), 43-54. https://doi.org/10.1061/(ASCE)1076-0342(2007)13:1(43)
  41. Silva, V. (2016), "Critical issues in earthquake scenario loss modeling", J. Earthq. Eng., 20(8), 1322-1341. https://doi.org/10.1080/13632469.2016.1138172.
  42. Tavakoli, B. and Ghafory-Ashtiany, M. (1999), "Seismic hazard assessment of Iran", Annal. Geophys., 42(6).