IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v213y2021ics0951832021003161.html
   My bibliography  Save this article

An Integrated Quantitative Risk Assessment Method for Urban Underground Utility Tunnels

Author

Listed:
  • Wu, Jiansong
  • Bai, Yiping
  • Fang, Weipeng
  • Zhou, Rui
  • Reniers, Genserik
  • Khakzad, Nima

Abstract

With the rapid urbanization, urban underground utility tunnels have seen fast growth in China in the past few years. Urban utility tunnels can house various kinds of city ‘lifelines’ such as natural gas pipeline, heat pipeline, water supply system, sewer pipeline, electricity and telecommunication cables, which are of great significance to guarantee essential flows of energy, information and logistics for urban life. If a utility tunnel accident occurs, the consequences could be catastrophic. Risk assessment has been an important tool to examine the safety performance of industrial facilities and the effectiveness of safety measures. In this study, an integrated model based on dynamic hazard scenario identification (DHSI), Bayesian network (BN) modeling and risk analysis is proposed for risk assessment of urban utility tunnels. The worst-case scenario of urban utility tunnel accidents is identified by DHSI and modelled by BN. Meanwhile, risk analysis is conducted based on the results of BN considering casualties and economic losses. Finally, the integrated method is applied to evaluate the risk level of a real-world utility tunnel. The results indicate that the integrated quantitative risk assessment framework is an alternative and effective tool for safety assessment and land-use planning of urban utility tunnels.

Suggested Citation

  • Wu, Jiansong & Bai, Yiping & Fang, Weipeng & Zhou, Rui & Reniers, Genserik & Khakzad, Nima, 2021. "An Integrated Quantitative Risk Assessment Method for Urban Underground Utility Tunnels," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    • Handle: RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021003161
    DOI: 10.1016/j.ress.2021.107792
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832021003161
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2021.107792?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nima Khakzad & Faisal Khan & Paul Amyotte & Valerio Cozzani, 2013. "Domino Effect Analysis Using Bayesian Networks," Risk Analysis, John Wiley & Sons, vol. 33(2), pages 292-306, February.
    2. Lee, Seulbi & Choi, Minji & Lee, Hyun-Soo & Park, Moonseo, 2020. "Bayesian network-based seismic damage estimation for power and potable water supply systems," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    3. Refaul Ferdous & Faisal Khan & Rehan Sadiq & Paul Amyotte & Brian Veitch, 2011. "Fault and Event Tree Analyses for Process Systems Risk Analysis: Uncertainty Handling Formulations," Risk Analysis, John Wiley & Sons, vol. 31(1), pages 86-107, January.
    4. Khakzad, Nima, 2019. "Modeling wildfire spread in wildland-industrial interfaces using dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 165-176.
    5. Francis, Royce A. & Guikema, Seth D. & Henneman, Lucas, 2014. "Bayesian Belief Networks for predicting drinking water distribution system pipe breaks," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 1-11.
    6. Tang, Kayu & Parsons, David J. & Jude, Simon, 2019. "Comparison of automatic and guided learning for Bayesian networks to analyse pipe failures in the water distribution system," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 24-36.
    7. Ouyang, Min & Liu, Chuang & Wu, Shengyu, 2020. "Worst-case vulnerability assessment and mitigation model of urban utility tunnels," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    8. Khakzad, Nima & Landucci, Gabriele & Reniers, Genserik, 2017. "Application of dynamic Bayesian network to performance assessment of fire protection systems during domino effects," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 232-247.
    9. Kammouh, Omar & Gardoni, Paolo & Cimellaro, Gian Paolo, 2020. "Probabilistic framework to evaluate the resilience of engineering systems using Bayesian and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    10. Chen, Chao & Khakzad, Nima & Reniers, Genserik, 2020. "Dynamic vulnerability assessment of process plants with respect to vapor cloud explosions," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    11. Nima Khakzad & Gabriele Landucci & Genserik Reniers, 2017. "Application of Graph Theory to Cost‐Effective Fire Protection of Chemical Plants During Domino Effects," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1652-1667, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xue, Gang & Liu, Shifeng & Ren, Long & Gong, Daqing, 2024. "Risk assessment of utility tunnels through risk interaction-based deep learning," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Liu, Zhichen & Li, Ying & Zhang, Zhaoyi & Yu, Wenbo, 2022. "A new evacuation accessibility analysis approach based on spatial information," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    3. Yong, Weixun & Zhang, Wengang & Nguyen, Hoang & Bui, Xuan-Nam & Choi, Yosoon & Nguyen-Thoi, Trung & Zhou, Jian & Tran, Trung Tin, 2022. "Analysis and prediction of diaphragm wall deflection induced by deep braced excavations using finite element method and artificial neural network optimized by metaheuristic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    4. Hai, Nan & Gong, Daqing & Liu, Shifeng & Dai, Zixuan, 2022. "Dynamic coupling risk assessment model of utility tunnels based on multimethod fusion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Misuri, Alessio & Landucci, Gabriele & Cozzani, Valerio, 2021. "Assessment of risk modification due to safety barrier performance degradation in Natech events," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    2. Chen, Chao & Yang, Ming & Reniers, Genserik, 2021. "A dynamic stochastic methodology for quantifying HAZMAT storage resilience," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Khakzad, Nima, 2021. "Optimal firefighting to prevent domino effects: Methodologies based on dynamic influence diagram and mathematical programming," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    4. Guo, Xiaoxue & Ding, Long & Ji, Jie & Cozzani, Valerio, 2022. "A cost-effective optimization model of safety investment allocation for risk reduction of domino effects," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    5. Gholamizadeh, Kamran & Zarei, Esmaeil & Yazdi, Mohammad & Ramezanifar, Ehsan & Aliabadi, Mostafa Mirzaei, 2024. "A hybrid model for dynamic analysis of domino effects in chemical process industries," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    6. Lan, Meng & Gardoni, Paolo & Qin, Rongshui & Zhang, Xiao & Zhu, Jiping & Lo, Siuming, 2022. "Modeling NaTech-related domino effects in process clusters: A network-based approach," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    7. Khakzad, Nima, 2023. "A methodology based on Dijkstra's algorithm and mathematical programming for optimal evacuation in process plants in the event of major tank fires," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    8. Robles-Velasco, Alicia & Cortés, Pablo & Muñuzuri, Jesús & Onieva, Luis, 2020. "Prediction of pipe failures in water supply networks using logistic regression and support vector classification," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    9. Mottahedi, Adel & Sereshki, Farhang & Ataei, Mohammad & Qarahasanlou, Ali Nouri & Barabadi, Abbas, 2021. "Resilience estimation of critical infrastructure systems: Application of expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    10. Lu, Qin & Zhang, Wei, 2022. "Integrating dynamic Bayesian network and physics-based modeling for risk analysis of a time-dependent power distribution system during hurricanes," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    11. Caetano, Henrique O. & N., Luiz Desuó & Fogliatto, Matheus S.S. & Maciel, Carlos D., 2024. "Resilience assessment of critical infrastructures using dynamic Bayesian networks and evidence propagation," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    12. Ding, Long & Khan, Faisal & Ji, Jie, 2022. "A novel vulnerability model considering synergistic effect of fire and overpressure in chemical processing facilities," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    13. Rifaai, Talha M. & Abokifa, Ahmed A. & Sela, Lina, 2022. "Integrated approach for pipe failure prediction and condition scoring in water infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    14. Liu, Jin & Zhai, Changhai & Yu, Peng, 2022. "A Probabilistic Framework to Evaluate Seismic Resilience of Hospital Buildings Using Bayesian Networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    15. Khakzad, Nima & Reniers, Genserik, 2019. "Low-capacity utilization of process plants: A cost-robust approach to tackle man-made domino effects," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. Chen, Chao & Reniers, Genserik & Khakzad, Nima, 2021. "A dynamic multi-agent approach for modeling the evolution of multi-hazard accident scenarios in chemical plants," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    17. Jiansong Wu & Zhuqiang Hu & Jinyue Chen & Zheng Li, 2018. "Risk Assessment of Underground Subway Stations to Fire Disasters Using Bayesian Network," Sustainability, MDPI, vol. 10(10), pages 1-21, October.
    18. Yuan, Shuaiqi & Cai, Jitao & Reniers, Genserik & Yang, Ming & Chen, Chao & Wu, Jiansong, 2022. "Safety barrier performance assessment by integrating computational fluid dynamics and evacuation modeling for toxic gas leakage scenarios," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    19. Yunfeng Yang & Guohua Chen & Yuanfei Zhao, 2023. "A Quantitative Framework for Propagation Paths of Natech Domino Effects in Chemical Industrial Parks: Part I—Failure Analysis," Sustainability, MDPI, vol. 15(10), pages 1-17, May.
    20. Ling He & Qing Yang & Xingxing Liu & Lingmei Fu & Jinmei Wang, 2021. "Exploring Factors Influencing Scenarios Evolution of Waste NIMBY Crisis: Analysis of Typical Cases in China," IJERPH, MDPI, vol. 18(4), pages 1-16, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021003161. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.