IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v242y2024ics0951832023006464.html
   My bibliography  Save this article

Risk analysis for hazardous chemical vehicle-bridge transportation system: A dynamic Bayesian network model incorporating vehicle dynamics

Author

Listed:
  • Guo, Jian
  • Ma, Kaijiang

Abstract

This study aims to analyze the risk of transporting hazardous chemicals on sea-crossing bridges using a dynamic Bayesian network (DBN) model that incorporates vehicle dynamics. Firstly, the cause-consequence relationship analysis is constructed using the bow-tie (BT) model, which is then translated into a Bayesian network (BN) by mapping algorithms. Based on the dynamic model, the occurrence probabilities of rollover and sideslip under different wind speeds are calculated as conditional probabilities. Secondly, a DBN model that satisfies the Markov assumption and time invariance is established to realize short-term risk prediction. Finally, the proposed model is applied to a sea-crossing bridge in Zhejiang, and other node parameters are obtained by combining the monitoring data of the vehicle-bridge transportation system (VBTS) monitoring platform and expert experience. The results indicate that vehicle failure has the highest impact on VBTS, and unsafe driver behavior and road alignment are the most vulnerable root causes, which should receive more attention. Additionally, wind sensitivity to VBTS is significant and cannot be ignored. The proposed method can effectively address the risks and challenges posed by hazardous chemical transportation on sea-crossing bridges and provides valuable insights with practical application to enhance transportation safety.

Suggested Citation

  • Guo, Jian & Ma, Kaijiang, 2024. "Risk analysis for hazardous chemical vehicle-bridge transportation system: A dynamic Bayesian network model incorporating vehicle dynamics," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    • Handle: RePEc:eee:reensy:v:242:y:2024:i:c:s0951832023006464
    DOI: 10.1016/j.ress.2023.109732
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023006464
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2023.109732?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. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2011. "Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 925-932.
    2. 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.
    3. Amin, Md. Tanjin & Khan, Faisal & Imtiaz, Syed, 2018. "Dynamic availability assessment of safety critical systems using a dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 108-117.
    4. Izdebski, Mariusz & Jacyna-Gołda, Ilona & Gołda, Paweł, 2022. "Minimisation of the probability of serious road accidents in the transport of dangerous goods," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    5. Ciro Caliendo & Maria Luisa De Guglielmo, 2017. "Quantitative Risk Analysis on the Transport of Dangerous Goods Through a Bi‐Directional Road Tunnel," Risk Analysis, John Wiley & Sons, vol. 37(1), pages 116-129, January.
    6. 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).
    7. Huang, Wencheng & Zhang, Yue & Kou, Xingyi & Yin, Dezhi & Mi, Rongwei & Li, Linqing, 2020. "Railway dangerous goods transportation system risk analysis: An Interpretive Structural Modeling and Bayesian Network combining approach," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    8. Jones, B. & Jenkinson, I. & Yang, Z. & Wang, J., 2010. "The use of Bayesian network modelling for maintenance planning in a manufacturing industry," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 267-277.
    9. Xu, Chengcheng & Wang, Yong & Liu, Pan & Wang, Wei & Bao, Jie, 2018. "Quantitative risk assessment of freeway crash casualty using high-resolution traffic data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 299-311.
    10. Babaleye, Ahmed O. & Kurt, Rafet Emek & Khan, Faisal, 2019. "Safety analysis of plugging and abandonment of oil and gas wells in uncertain conditions with limited data," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 133-141.
    11. Zheng, Xiao-Wei & Li, Hong-Nan & Gardoni, Paolo, 2023. "Hybrid Bayesian-Copula-based risk assessment for tall buildings subject to wind loads considering various uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    12. DeJesus Segarra, Jonathan & Bensi, Michelle & Modarres, Mohammad, 2021. "A Bayesian Network Approach for Modeling Dependent Seismic Failures in a Nuclear Power Plant Probabilistic Risk Assessment," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    13. Guo, Jian & Luo, Cheng & Ma, Kaijiang, 2023. "Risk coupling analysis of road transportation accidents of hazardous materials in complicated maritime environment," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    14. A. V. Thomas & Satyanarayana Kalidindi & L. S. Ganesh, 2006. "Modelling and assessment of critical risks in BOT road projects," Construction Management and Economics, Taylor & Francis Journals, vol. 24(4), pages 407-424.
    15. Paul P.‐Y. Wu & M. Julian Caley & Gary A. Kendrick & Kathryn McMahon & Kerrie Mengersen, 2018. "Dynamic Bayesian network inferencing for non‐homogeneous complex systems," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(2), pages 417-434, February.
    16. 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.
    17. 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).
    18. Liu, Cuiwei & Wang, Yazhen & Li, Xinhong & Li, Yuxing & Khan, Faisal & Cai, Baoping, 2021. "Quantitative assessment of leakage orifices within gas pipelines using a Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    19. Renee M. Clark & Mary E. Besterfield‐Sacre, 2009. "A New Approach to Hazardous Materials Transportation Risk Analysis: Decision Modeling to Identify Critical Variables," Risk Analysis, John Wiley & Sons, vol. 29(3), pages 344-354, March.
    20. Liu, Zengkai & Ma, Qiang & Cai, Baoping & Shi, Xuewei & Zheng, Chao & Liu, Yonghong, 2022. "Risk coupling analysis of subsea blowout accidents based on dynamic Bayesian network and NK model," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    21. Bahar Y. Kara & Vedat Verter, 2004. "Designing a Road Network for Hazardous Materials Transportation," Transportation Science, INFORMS, vol. 38(2), pages 188-196, May.
    22. Delvosalle, C. & Fiévez, C. & Pipart, A. & Fabrega, J. Casal & Planas, E. & Christou, M. & Mushtaq, F., 2005. "Identification of reference accident scenarios in SEVESO establishments," Reliability Engineering and System Safety, Elsevier, vol. 90(2), pages 238-246.
    23. Zhou, Ying & Li, Chenshuang & Zhou, Cheng & Luo, Hanbin, 2018. "Using Bayesian network for safety risk analysis of diaphragm wall deflection based on field data," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 152-167.
    24. Noguchi, H. & Hienuki, S. & Fuse, M., 2020. "Network theory-based accident scenario analysis for hazardous material transport: A case study of liquefied petroleum gas transport in japan," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    25. Yang, Yongsheng & Khan, Faisal & Thodi, Premkumar & Abbassi, Rouzbeh, 2017. "Corrosion induced failure analysis of subsea pipelines," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 214-222.
    Full references (including those not matched with items on IDEAS)

    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. Hassan, Shamsu & Wang, Jin & Kontovas, Christos & Bashir, Musa, 2022. "An assessment of causes and failure likelihood of cross-country pipelines under uncertainty using bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    2. Adumene, Sidum & Khan, Faisal & Adedigba, Sunday & Zendehboudi, Sohrab & Shiri, Hodjat, 2021. "Dynamic risk analysis of marine and offshore systems suffering microbial induced stochastic degradation," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    3. Guo, Jian & Luo, Cheng & Ma, Kaijiang, 2023. "Risk coupling analysis of road transportation accidents of hazardous materials in complicated maritime environment," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    4. Izdebski, Mariusz & Jacyna-Gołda, Ilona & Gołda, Paweł, 2022. "Minimisation of the probability of serious road accidents in the transport of dangerous goods," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    5. Chen, Yinuo & Tian, Zhigang & He, Rui & Wang, Yifei & Xie, Shuyi, 2023. "Discovery of potential risks for the gas transmission station using monitoring data and the OOBN method," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    6. Dao, Uyen & Sajid, Zaman & Khan, Faisal & Zhang, Yahui, 2023. "Dynamic Bayesian network model to study under-deposit corrosion," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. 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).
    8. Aalirezaei, Armin & Kabir, Dr. Golam & Khan, Md Saiful Arif, 2023. "Dynamic predictive analysis of the consequences of gas pipeline failures using a Bayesian network," International Journal of Critical Infrastructure Protection, Elsevier, vol. 43(C).
    9. Tao, Longlong & Wu, Jie & Ge, Daochuan & Chen, Liwei & Sun, Ming, 2022. "Risk-informed based comprehensive path-planning method for radioactive materials road transportation," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    10. Zhang, Hengqi & Geng, Hua & Zeng, Huarong & Jiang, Li, 2023. "Dynamic risk evaluation and control of electrical personal accidents," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    11. Ding, Rui & Liu, Zehua & Xu, Jintao & Meng, Fanpeng & Sui, Yang & Men, Xinhong, 2021. "A novel approach for reliability assessment of residual heat removal system for HPR1000 based on failure mode and effect analysis, fault tree analysis, and fuzzy Bayesian network methods," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    12. Chen, Xi & Bose, Neil & Brito, Mario & Khan, Faisal & Thanyamanta, Bo & Zou, Ting, 2021. "A Review of Risk Analysis Research for the Operations of Autonomous Underwater Vehicles," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    13. Laihao Ma & Xiaoxue Ma & Jingwen Zhang & Qing Yang & Kai Wei, 2021. "Identifying the Weaker Function Links in the Hazardous Chemicals Road Transportation System in China," IJERPH, MDPI, vol. 18(13), pages 1-17, July.
    14. Li, Mei & Liu, Zixian & Li, Xiaopeng & Liu, Yiliu, 2019. "Dynamic risk assessment in healthcare based on Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 327-334.
    15. He, Rui & Zhu, Jingyu & Chen, Guoming & Tian, Zhigang, 2022. "A real-time probabilistic risk assessment method for the petrochemical industry based on data monitoring," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    16. Wang, Jian & Gao, Shibin & Yu, Long & Ma, Chaoqun & Zhang, Dongkai & Kou, Lei, 2023. "A data-driven integrated framework for predictive probabilistic risk analytics of overhead contact lines based on dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    17. Babaleye, Ahmed O. & Kurt, Rafet Emek & Khan, Faisal, 2019. "Safety analysis of plugging and abandonment of oil and gas wells in uncertain conditions with limited data," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 133-141.
    18. Cai, Baoping & Zhang, Yanping & Wang, Haifeng & Liu, Yonghong & Ji, Renjie & Gao, Chuntan & Kong, Xiangdi & Liu, Jing, 2021. "Resilience evaluation methodology of engineering systems with dynamic-Bayesian-network-based degradation and maintenance," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    19. Bhuyan, Kasturi & Sharma, Hrishikesh, 2022. "Reliability analysis & performance-based code calibration for slabs/walls of protective structures subject to air blast loading," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    20. Xiang, W. & Zhou, W., 2021. "Bayesian network model for predicting probability of third-party damage to underground pipelines and learning model parameters from incomplete datasets," Reliability Engineering and System Safety, Elsevier, vol. 205(C).

    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:242:y:2024:i:c:s0951832023006464. 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.