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Critical risk factors in ship fire accidents

Author

Listed:
  • Likun Wang
  • Jinhui Wang
  • Mingyang Shi
  • Shanshan Fu
  • Mo Zhu

Abstract

Risk management of ship fire accidents (SFA) is a vital issue in maritime transportation systems since ship fires are instantaneous and developing events-small errors can cause serious accidents. The traditional approach for SFA analysis is on a coarse-grained level, using accident data from one or several case studies or expert knowledge; such data acquisition method substantially relies on subjective expert experience and brings about epistemic uncertainties. This study proposes a new framework for identifying critical risk factors in SFA. First, grounded theory (GT) is applied to obtain risk factors on a fine-grained level by converting unstructured text information to structured accident data. Then, Fault tree analysis (FTA) is used to develop a risk model and make a quantitative analysis of the SFA. Bayesian network (BN) is also integrated to verify and identify the critical risk factors in SFA with sensitivity analysis. Results indicate that sealing off the ship cabin timely, effective ventilation system, as well as prompt emergency response by crews and passengers on board are the dominant factors. Our findings provide useful insights for maritime safety administration and shipping companies to take actions for fire prevention.

Suggested Citation

  • Likun Wang & Jinhui Wang & Mingyang Shi & Shanshan Fu & Mo Zhu, 2021. "Critical risk factors in ship fire accidents," Maritime Policy & Management, Taylor & Francis Journals, vol. 48(6), pages 895-913, August.
    • Handle: RePEc:taf:marpmg:v:48:y:2021:i:6:p:895-913
    DOI: 10.1080/03088839.2020.1821110
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    Cited by:

    1. Junzhong Bao & Zhijie Bian & Bitong Li & Yan Li & Yuguang Gong, 2023. "A Hybrid Approach for Quantitative Analysis of Fire Hazards in Enclosed Vehicle Spaces on Ro-ro Passenger Ships," Sustainability, MDPI, vol. 15(17), pages 1-16, August.
    2. Yuechao Zhao & Haobo Zhao & Zeya Miao & Dihao Ai & Qifei Wang, 2023. "A Numerical Study on the Smoke Dispersion and Temperature Distribution of a Ship Engine Room Fire Based on OpenFOAM," Sustainability, MDPI, vol. 15(20), pages 1-23, October.
    3. Jiale Zhao & Fuqiang Yang & Yong Guo & Xin Ren, 2022. "A CAST-Based Analysis of the Metro Accident That Was Triggered by the Zhengzhou Heavy Rainstorm Disaster," IJERPH, MDPI, vol. 19(17), pages 1-20, August.
    4. Xu, Sheng & Kim, Ekaterina & Haugen, Stein & Zhang, Mingyang, 2022. "A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

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