A framework for risk assessment for maritime transportation systems—A case study for open sea collisions involving RoPax vessels
Система оценки риска для морских транспортных систем: тематическое исследование столкновений в открытом море с участием судов RoPax
2013-12-16
SCID: 54.1/bhqg7exe
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Bayesian Belief NetworksGulf of FinlandRoPax vesselsmaritime risk assessmentopen sea ship collisions
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Abstract (AI)
Maritime accidents involving ships carrying passengers may pose a high risk with respect to human casualties. For effective risk mitigation, an insight into the process of risk escalation is needed. This requires a proactive approach when it comes to risk modelling for maritime transportation systems. Most of the existing models are based on historical data on maritime accidents, and thus they can be considered reactive instead of proactive. This paper introduces a systematic, transferable and proactive framework estimating the risk for maritime transportation systems, meeting the requirements stemming from the adopted formal definition of risk. The framework focuses on ship–ship collisions in the open sea, with a RoRo/Passenger ship (RoPax) being considered as the struck ship. First, it covers an identification of the events that follow a collision between two ships in the open sea, and, second, it evaluates the probabilities of these events, concluding by determining the severity of a collision. The risk framework is developed with the use of Bayesian Belief Networks and utilizes a set of analytical methods for the estimation of the risk model parameters. Finally, a case study is presented, in which the risk framework developed here is applied to a maritime transportation system operating in the Gulf of Finland (GoF). The results obtained are compared to the historical data and available models, in which a RoPax was involved in a collision, and good agreement with the available records is found.
Key Findings
1
A Gulf of Finland case study demonstrates good agreement between the framework’s results, historical collision records, and available models.
2
Bayesian Belief Networks and analytical methods are used to estimate risk-model parameters and determine collision severity.
3
The approach addresses limitations of predominantly reactive, historical-data-based maritime accident risk models by supporting proactive risk mitigation.
4
The framework models open-sea ship–ship collisions involving a RoPax vessel as the struck ship, including post-collision event sequences and their probabilities.
5
The paper introduces a systematic, transferable, and proactive framework for estimating maritime transportation-system collision risk.
Research Object
open-sea ship–ship collisions involving a RoRo/Passenger (RoPax) vessel as the struck ship within maritime transportation systems
Research Subject
the escalation process and resulting risk severity of these collisions, including the probabilities and consequences of post-collision events
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2013-12-16
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