American Journal of Civil Engineering

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Quantitatively Measuring Transportation Network Resilience under Earthquake Uncertainty and Risks

Received: 14 June 2016    Accepted:     Published: 15 June 2016
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Abstract

Transportation network faces the possibility of sudden events that disrupts its normal operation, particularly in earthquake prone areas. As the backbone of critical infrastructure lifelines, it is therefore essential that transportation network retains its resilience after disastrous earthquakes to ensure efficient evacuation of at-risk population to safe zones and timely dispatch of emergency response resources to the impacted area. However, predicting transportation network resilience and planning for emergency situations is an extremely challenging problem, particularly under earthquake uncertainty and risks. This paper aims to propose a model to quantify seismic resilience of transportation network. The focus of this model is on generalizing quantitative resilience measures of transportation network response to earthquake risks rather than specifying characteristics of the corridor selections that lead to patterns of the response of each specific road segment. In the model, traffic capacity is selected as resilience measure and three capacity reduction indices are introduced to address the uncertainty and risks from impacted roads, buildings and bridges, respectively. Finally, the proposed models were validated by the 2008 Sichuan Earthquake data.

DOI 10.11648/j.ajce.20160404.17
Published in American Journal of Civil Engineering (Volume 4, Issue 4, July 2016)
Page(s) 174-184
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Earthquake, Transportation Network, Resilience, Uncertainty, Risks

References
[1] Keh-Chyuan Tsai, Shyh-Jiann Hwang, “Seismic retrofit program for Taiwan school buildings after 1999 Chi-Chi earthquake.” The Fourth Session of the National Earthquake Disaster Mitigation Engineering Symposium, 2009, pp. 693-703.
[2] Pan G., Tang D. L., “Damage information derived from multi-sensor data of the Wenchuan Earthquake of May 2008.” International Journal of Remote Sensing, vol. 31, 2010, pp. 3509-3519.
[3] Duramy, B. F. “Women in the aftermath of the 2010 Haitian Earthquake.” 25 Emory Int'l L., 2011, pp. 1193-1215.
[4] Murray-Tuite PMA, “Comparison of transportation network resilience under simulated system optimum and user equilibrium conditions.” The 2006 Winter Simulation Conference, Monterey, 2006, pp. 1398-1405.
[5] Freckleton, Heaslip, Louisell, and Collura. “Evaluation of transportation network resiliency with consideration for disaster magnitude”. TRB 2012 Annual Meeting. 2012.
[6] Bruneau, M, Chang, S, Eguchi, RT, et al. “A framework to quantitatively assess and enhance the seismic resilience of communities.” Earthquake Spectra., vol. 19, 2003, pp. 733-752.
[7] Rose, A. “Defining and measuring economic resilience to earthquakes.” Disaster Prevention and Management, vol. 13, 2004, pp. 307-314.
[8] Robert, D. “Assessing the resilience of transportation systems in case of large-scale disastrous events.” Environmental Engineering, 2011, pp. 1070-1076.
[9] Song, J. X., and Li, J. “Simulation on accessibility of post-seismic urban transportation system.” Journal of Nature Disasters, vol. 5, 1996, pp. 73-78 (in Chinese).
[10] Du, P. “Improvement for the calculating method of debris piling problem in the seismic disaster forecasting of the transportation system.” World Seismic Engineering, vol. 23, 2007, pp. 161-164 (in Chinese).
[11] Li Z. J., Wang, J. Y, and Dong, F. “Randomness analysis on traffic capacity of road after seismic.” Transport Engineering & Safety, 2010, pp. 131-133 (in Chinese).
[12] Liu, C. G., Du, W., and Zhai, T. “Reliability analysis of urban transportation system.” Seismic Engineering and Engineering Vibration, vol. 19, 1999, pp. 95-99 (in Chinese).
[13] Li, Y. Y., Zhou, Z. H., Jiang, Z. Z., et al. “Theoretical model of actual traffic capacity of highway post-eatrhquake”. Journal of Nanjing tech university (Natural Science Edition), vol. 36, 2014, pp. 102-106 (in Chinese).
[14] Wang D. S., Feng, Q. M. “Seismic disaster assessment methods for bridges.” Journal of Nature Disasters, vol. 10, 2001, pp. 113-118 (in Chinese).
[15] Lan, R. Q., Feng, B., and Wang, Z. F. “Study on the fast assessment of traffic capacity of highway bridges after strong earthquakes.” World Earthquake Engineering, vol. 25, 2009, pp. 82-87 (in Chinese).
[16] Elise Miller-Hooks, Xiaodong Zhang, Reza Faturechi. Measuring and maximizing resilience of freight transportation networks. Computers & Operations Research, vol. 39, 2012, pp. 1633–1643.
[17] Alberto Decò, Paolo Bocchini and Dan M. Frangopol. A probabilistic approach for the prediction of seismic resilience of Bridges. Earthquake Engineering Structural Dynamics. Dyn. 2013, 42: 1469–1487.
[18] Hitomi Nakanishi, John Black, Kojiro Matsuo. Disaster resilience in transportation: Japan earthquake and tsunami 2011. International Journal of Disaster Resilience in the Built Environment Vol. 5 No. 4, 2014, pp. 341-361.
[19] Xiaodong Zhang, Elise Miller-Hooks. Scheduling Short-Term Recovery Activities to Maximize Transportation Network Resilience. J. Comput. Civ. Eng., vol. 29 No. 6, 2015, pp: 04014087.1-10.
[20] Li, B. X., and Wang, Zh. “Lessons from the performance of masonry structure with ground RC frame during Wenchuan earthquake.” Acta Scientiarum Naturaliun Universitatis Sunyatsen I, vol. 49, 2010, pp. 22-27 (in Chinese).
[21] Jiang S. Z., and Bao F. “Vulnerability analysis of road system.” Highway, 2006, pp. 106-108 (in Chinese).
[22] Li J. Lifeline engineering seismic basic theory and application. Beijing, China. 2005.
[23] Li, Y. M., Wang, L. P., and Liu, L. P. “Predictive model of post-seismic debris obstruction of collapsed buildings in mountain cities.” Journal of PLA University of Science and Technology (Natural Science Edition), vol. 11, 2010, pp. 439-444 (in Chinese).
[24] Mao, C., Zhang, X. H., and Yang, X. M. “Embankment, Pavement damage investigation and reconstruction technical measures of constructing YINGRI Road”. Southwest Road, 2008, pp. 245-250 (in Chinese).
[25] Bai, Y. B., and Yu, P. C. “Wenchuan earthquake major disasters fault reason analysis: For example in road Demao.” Engineering Seismic Damage Investigation Analysis and Research of Wenchuan Earthquake 2009 (in Chinese).
[26] Ma H. S., Li Y. W., and Xiong J. “Wenchuan earthquake west road diseases and geological disaster investigation and analysis.” Earthquake Special Issue, 2008, pp. 265-272 (in Chinese).
[27] Zhao Chuang. Unseating damages in multi-span simply supported bridges under Canyon Topography. Suzhou: Suzhou University of Science and Technology, 2012.
[28] Zhou Guoliang, Cui Chengchen, Liu Bideng et al. Failure Modes of Near-fault Bridges in Wenchuan Earthquake. Technology for Earthquake Disaster Prevention, vol. 3, 2008, pp. 370-378.
[29] Xu Xi-wei, Wen Xue-ze, Ye Jian-qing et al. The Ms 8.0 Wenchuan Earthquake Surface Ruptures and its Seismogenic Structure. Seismology and Geology, vol. 30, 2008, pp. 597-629.
Author Information
  • Department of Civil and Architectural Engineering, North China University of Science and Technology, Tangshan, China

  • Department of Civil, Environmental and Construction Engineering, Texas Tech University, Lubbock, Texas, U.S.A

  • Department of Civil and Architectural Engineering, North China University of Science and Technology, Tangshan, China

  • Department of Civil and Architectural Engineering, North China University of Science and Technology, Tangshan, China

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  • APA Style

    Manzhen Duan, Dayong Wu, Bo Dong, Lin Zhang. (2016). Quantitatively Measuring Transportation Network Resilience under Earthquake Uncertainty and Risks. American Journal of Civil Engineering, 4(4), 174-184. https://doi.org/10.11648/j.ajce.20160404.17

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    ACS Style

    Manzhen Duan; Dayong Wu; Bo Dong; Lin Zhang. Quantitatively Measuring Transportation Network Resilience under Earthquake Uncertainty and Risks. Am. J. Civ. Eng. 2016, 4(4), 174-184. doi: 10.11648/j.ajce.20160404.17

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    AMA Style

    Manzhen Duan, Dayong Wu, Bo Dong, Lin Zhang. Quantitatively Measuring Transportation Network Resilience under Earthquake Uncertainty and Risks. Am J Civ Eng. 2016;4(4):174-184. doi: 10.11648/j.ajce.20160404.17

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  • @article{10.11648/j.ajce.20160404.17,
      author = {Manzhen Duan and Dayong Wu and Bo Dong and Lin Zhang},
      title = {Quantitatively Measuring Transportation Network Resilience under Earthquake Uncertainty and Risks},
      journal = {American Journal of Civil Engineering},
      volume = {4},
      number = {4},
      pages = {174-184},
      doi = {10.11648/j.ajce.20160404.17},
      url = {https://doi.org/10.11648/j.ajce.20160404.17},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajce.20160404.17},
      abstract = {Transportation network faces the possibility of sudden events that disrupts its normal operation, particularly in earthquake prone areas. As the backbone of critical infrastructure lifelines, it is therefore essential that transportation network retains its resilience after disastrous earthquakes to ensure efficient evacuation of at-risk population to safe zones and timely dispatch of emergency response resources to the impacted area. However, predicting transportation network resilience and planning for emergency situations is an extremely challenging problem, particularly under earthquake uncertainty and risks. This paper aims to propose a model to quantify seismic resilience of transportation network. The focus of this model is on generalizing quantitative resilience measures of transportation network response to earthquake risks rather than specifying characteristics of the corridor selections that lead to patterns of the response of each specific road segment. In the model, traffic capacity is selected as resilience measure and three capacity reduction indices are introduced to address the uncertainty and risks from impacted roads, buildings and bridges, respectively. Finally, the proposed models were validated by the 2008 Sichuan Earthquake data.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - Quantitatively Measuring Transportation Network Resilience under Earthquake Uncertainty and Risks
    AU  - Manzhen Duan
    AU  - Dayong Wu
    AU  - Bo Dong
    AU  - Lin Zhang
    Y1  - 2016/06/15
    PY  - 2016
    N1  - https://doi.org/10.11648/j.ajce.20160404.17
    DO  - 10.11648/j.ajce.20160404.17
    T2  - American Journal of Civil Engineering
    JF  - American Journal of Civil Engineering
    JO  - American Journal of Civil Engineering
    SP  - 174
    EP  - 184
    PB  - Science Publishing Group
    SN  - 2330-8737
    UR  - https://doi.org/10.11648/j.ajce.20160404.17
    AB  - Transportation network faces the possibility of sudden events that disrupts its normal operation, particularly in earthquake prone areas. As the backbone of critical infrastructure lifelines, it is therefore essential that transportation network retains its resilience after disastrous earthquakes to ensure efficient evacuation of at-risk population to safe zones and timely dispatch of emergency response resources to the impacted area. However, predicting transportation network resilience and planning for emergency situations is an extremely challenging problem, particularly under earthquake uncertainty and risks. This paper aims to propose a model to quantify seismic resilience of transportation network. The focus of this model is on generalizing quantitative resilience measures of transportation network response to earthquake risks rather than specifying characteristics of the corridor selections that lead to patterns of the response of each specific road segment. In the model, traffic capacity is selected as resilience measure and three capacity reduction indices are introduced to address the uncertainty and risks from impacted roads, buildings and bridges, respectively. Finally, the proposed models were validated by the 2008 Sichuan Earthquake data.
    VL  - 4
    IS  - 4
    ER  - 

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