IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v252y2024ics0951832024005271.html
   My bibliography  Save this article

A conceptual risk modelling for cargo tank fire/explosion in chemical tanker by using Evidential Reasoning -SLIM and Bayesian belief network approach

Author

Listed:
  • Sezer, Sukru Ilke
  • Akyuz, Emre

Abstract

The transportation of hazardous cargoes, particularly in chemical tankers, represents significant risks such as fire and explosion, which can have catastrophic consequences for both human life, commodity and maritime environment. This article presents a conceptual risk modelling for cargo tank fire/explosion incidents in chemical tanker ships under the Evidential Reasoning (ER) - Success likelihood index method (SLIM) approach with the Bayesian belief network (BBN) to provide a practical tool for assessing and managing the associated risks. Whilst the ER-SLIM approach offers a systematic human error probability (HEP) prediction and handling uncertainty in risk, allowing for the incorporation of expert judgments and data-driven information, the BBN provides a probabilistic graphical model to represent the causal relationships among various risk factors. The result shows that the risk of cargo tank fire/explosion during the cargo tank cleaning operation is calculated as 2.83E-02. The findings of the research including consequences analysis provide valuable insights for decision-makers, safety managers, superintendents, ship masters and officers in the maritime industry to prioritize risk management strategies and enhance the safety of chemical tanker operations.

Suggested Citation

  • Sezer, Sukru Ilke & Akyuz, Emre, 2024. "A conceptual risk modelling for cargo tank fire/explosion in chemical tanker by using Evidential Reasoning -SLIM and Bayesian belief network approach," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    • Handle: RePEc:eee:reensy:v:252:y:2024:i:c:s0951832024005271
    DOI: 10.1016/j.ress.2024.110455
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832024005271
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2024.110455?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. Zhang, Xiaoge & Mahadevan, Sankaran, 2021. "Bayesian network modeling of accident investigation reports for aviation safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Zhang, Weibin & Feng, Xinyu & Goerlandt, Floris & Liu, Qing, 2020. "Towards a Convolutional Neural Network model for classifying regional ship collision risk levels for waterway risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    3. Aziz, Abdul & Ahmed, Salim & Khan, Faisal & Stack, Chris & Lind, Annes, 2019. "Operational risk assessment model for marine vessels," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 348-361.
    4. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2012. "Dynamic risk analysis using bow-tie approach," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 36-44.
    5. Sezer, Sukru Ilke & Akyuz, Emre & Arslan, Ozcan, 2022. "An extended HEART Dempster–Shafer evidence theory approach to assess human reliability for the gas freeing process on chemical tankers," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    6. Uflaz, Esma & Sezer, Sukru Ilke & Tunçel, Ahmet Lutfi & Aydin, Muhammet & Akyuz, Emre & Arslan, Ozcan, 2024. "Quantifying potential cyber-attack risks in maritime transportation under Dempster–Shafer theory FMECA and rule-based Bayesian network modelling," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    7. 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.
    8. Kandel, Rajesh & Baroud, Hiba, 2024. "A data-driven risk assessment of Arctic maritime incidents: Using machine learning to predict incident types and identify risk factors," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    9. Elidolu, Gizem & Sezer, Sukru Ilke & Akyuz, Emre & Arslan, Ozcan & Arslanoglu, Yasin, 2023. "Operational risk assessment of ballasting and de-ballasting on-board tanker ship under FMECA extended Evidential Reasoning (ER) and Rule-based Bayesian Network (RBN) approach," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    10. Zhang, Mingyang & Kujala, Pentti & Hirdaris, Spyros, 2022. "A machine learning method for the evaluation of ship grounding risk in real operational conditions," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    11. Sezer, Sukru Ilke & Camliyurt, Gokhan & Aydin, Muhmmet & Akyuz, Emre & Gardoni, Paolo, 2023. "A bow-tie extended D-S evidence-HEART modelling for risk analysis of cargo tank cracks on oil/chemical tanker," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    12. Park, Kyung S. & Lee, Jae in, 2008. "A new method for estimating human error probabilities: AHP–SLIM," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 578-587.
    13. Li, Huanhuan & Ren, Xujie & Yang, Zaili, 2023. "Data-driven Bayesian network for risk analysis of global maritime accidents," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    14. Deng, Wanyi & Ma, Xiaoxue & Qiao, Weiliang, 2024. "A novel methodology to quantify the impact of safety barriers on maritime operational risk based on a probabilistic network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    15. Obeng, Francis & Domeh, Daniel & Khan, Faisal & Bose, Neil & Sanli, Elizabeth, 2024. "An operational risk management approach for small fishing vessel," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    16. Yamin Huang & P. H. A. J. M. van Gelder, 2020. "Time‐Varying Risk Measurement for Ship Collision Prevention," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 24-42, January.
    17. Sezer, Sukru Ilke & Akyuz, Emre & Gardoni, Paolo, 2023. "Prediction of human error probability under Evidential Reasoning extended SLIM approach: The case of tank cleaning in chemical tanker," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
    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. Fan, Hanwen & Jia, Haiying & He, Xuzhuo & Lyu, Jing, 2024. "Navigating uncertainty: A dynamic Bayesian network-based risk assessment framework for maritime trade routes," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    2. Deng, Wanyi & Ma, Xiaoxue & Qiao, Weiliang, 2024. "A novel methodology to quantify the impact of safety barriers on maritime operational risk based on a probabilistic network," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Meng, Huixing & Hu, Mengqian & Kong, Ziyan & Niu, Yiming & Liang, Jiali & Nie, Zhenyu & Xing, Jinduo, 2024. "Risk analysis of lithium-ion battery accidents based on physics-informed data-driven Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    4. Liu, Qi & Sun, Ke & Liu, Wenqi & Li, Yufeng & Zheng, Xiangyu & Cao, Chenhong & Li, Jiangtao & Qin, Wutao, 2025. "Quantitative risk assessment for connected automated Vehicles: Integrating improved STPA-SafeSec and Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    5. 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.
    6. Bhardwaj, U. & Teixeira, A.P. & Guedes Soares, C., 2022. "Casualty analysis methodology and taxonomy for FPSO accident analysis," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    7. Uflaz, Esma & Sezer, Sukru Ilke & Tunçel, Ahmet Lutfi & Aydin, Muhammet & Akyuz, Emre & Arslan, Ozcan, 2024. "Quantifying potential cyber-attack risks in maritime transportation under Dempster–Shafer theory FMECA and rule-based Bayesian network modelling," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    8. Li, Huanhuan & Çelik, Cihad & Bashir, Musa & Zou, Lu & Yang, Zaili, 2024. "Incorporation of a global perspective into data-driven analysis of maritime collision accident risk," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    9. Li, Weijun & Sun, Qiqi & Zhang, Jiwang & Zhang, Laibin, 2024. "Quantitative risk assessment of industrial hot work using Adaptive Bow Tie and Petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    10. Chen, Tianyi & Wang, Hua & Cai, Yutong & Liang, Maohan & Meng, Qiang, 2025. "Exploring key factors for long-term vessel incident risk prediction," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    11. Sezer, Sukru Ilke & Camliyurt, Gokhan & Aydin, Muhmmet & Akyuz, Emre & Gardoni, Paolo, 2023. "A bow-tie extended D-S evidence-HEART modelling for risk analysis of cargo tank cracks on oil/chemical tanker," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    12. Fu, Shanshan & Yu, Yuerong & Chen, Jihong & Xi, Yongtao & Zhang, Mingyang, 2022. "A framework for quantitative analysis of the causation of grounding accidents in arctic shipping," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    13. Lu, Xin & Zeng, Shengkui & Guo, Jianbin & Deng, Wei & He, Mingjun & Che, Haiyang, 2025. "An integrated method of extended STPA and BN for safety assessment of man-machine phased-mission system," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    14. Zhang, Mingyang & Taimuri, Ghalib & Zhang, Jinfen & Zhang, Di & Yan, Xinping & Kujala, Pentti & Hirdaris, Spyros, 2025. "Systems driven intelligent decision support methods for ship collision and grounding prevention: Present status, possible solutions, and challenges," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    15. Xin, Xuri & Liu, Kezhong & Loughney, Sean & Wang, Jin & Li, Huanhuan & Ekere, Nduka & Yang, Zaili, 2023. "Multi-scale collision risk estimation for maritime traffic in complex port waters," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    16. Zhou, Kaiwen & Xing, Wenbin & Wang, Jingbo & Li, Huanhuan & Yang, Zaili, 2024. "A data-driven risk model for maritime casualty analysis: A global perspective," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    17. Liang, Xinrui & Fan, Shiqi & Lucy, John & Yang, Zaili, 2022. "Risk analysis of cargo theft from freight supply chains using a data-driven Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    18. Kandel, Rajesh & Baroud, Hiba, 2024. "A data-driven risk assessment of Arctic maritime incidents: Using machine learning to predict incident types and identify risk factors," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    19. Bauranov, Aleksandar & Rakas, Jasenka, 2024. "Bayesian network model of aviation safety: Impact of new communication technologies on mid-air collisions," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    20. Domeh, Vindex & Obeng, Francis & Khan, Faisal & Bose, Neil & Sanli, Elizabeth, 2023. "An operational risk awareness tool for small fishing vessels operating in harsh environment," Reliability Engineering and System Safety, Elsevier, vol. 234(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:252:y:2024:i:c:s0951832024005271. 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.