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Citation:
　Utkarsh Bhardwaj,Angelo Palos Teixeira,C. Guedes Soares.Probabilistic Risk model of Ship Allision Accidents with Offshore Platforms[J].Journal of Marine Science and Application,2026,(3):713-727.[doi:10.1007/s11804-026-00812-1]
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Probabilistic Risk model of Ship Allision Accidents with Offshore Platforms

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Title:
Probabilistic Risk model of Ship Allision Accidents with Offshore Platforms
Author(s):
Utkarsh Bhardwaj;  Angelo Palos Teixeira;  C. Guedes Soares
Affilations:
Author(s):
Utkarsh Bhardwaj;  Angelo Palos Teixeira;  C. Guedes Soares
Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Lisbon, 1600-214, Portugal
Keywords:
Vessel-platform allision accidents; Bayesian networks; Causal factors; Basic causes; Sensitivity analysis
分类号:
-
DOI:
10.1007/s11804-026-00812-1
Abstract:
This paper proposes a Bayesian Network-based framework for risk assessment and probability estimation of vessel-platform allision accidents, using a novel technique that derives probabilities from incidental data. A dataset of 557 allision incidents collected from multiple open source agencies is analysed to identify causation patterns. Basic causes could only be determined for 375 incidents, with supply vessels involved in 61% of cases. Statistical analysis revealed that vessel type and the month of occurrences are significantly associated, and most incidents arose during cargo transfer operations. Fixed installation accounted for the majority of allisions with moving vessels, and human error emerged as the leading contributor (30%). Building on these insights, a Bayesian Network model is developed incorporating 42 identified causes, three causal factors and four consequence levels. Using a recent probabilistic approach, probabilities of basic causes are derived from annual allision occurrence rates. The BN model is then applied to predict annual allision probabilities and to conduct sensitivity analyses. Results show that weather-related causes and misalignment errors exert the strongest influences on accident probabilities. The methodology is transparent and holistic in providing better discernment of the causation probability of allision accidents.

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Memo

Memo:
Received date:2025-8-6。<br>Foundation item:Supported by the Portuguese Foundation for Science and Technology (Funda&#231;&#227;o para a Ci&#234;ncia e Tecnologia—FCT), under contract UIDB/UIDP/00134/2020. Open access funding provided by FCT∣FCCN (b-on).<br>Corresponding author:Utkarsh Bhardwaj,E-mail:utkarsh.bhardwaj@centec.tecnico.ulisboa.pt
Last Update: 2026-06-25