Towards an evidence-based probabilistic risk model for ship-grounding accidents

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Abstract

Most of the risk models for ship-grounding accidents do not fully utilize available evidence, since it is based on accident statistics and expert opinions. The major issue with such kinds of models is their limitation in supporting the process of risk-management with respect to grounding accidents, since they do not reflect the reality to the extent required. This paper presents an evidence-based and expert-supported approach to structure a model assessing the probability of ship-grounding accidents, to make it more suitable for risk-management purposes. The approach focuses on using evidential data of ship-grounding accidents extracted from the actual accident and incident reports as well as the judgement elicited from the experts regarding the links and probabilities not supported by the reports. The developed probabilistic model gathers, in a causal fashion, the evidential contributing factors in ship-grounding accidents. The outcome of the model is the probability of a ship-grounding accident given the prior and posterior probabilities of the contributing factors. Moreover, the uncertainties associated with the elements of the model are clearly communicated to the end-user adopting a concept of strength-of-knowledge. The model can be used to suggest proper risk-control-measures to mitigate the risk. By running uncertainty and sensitivity analyses of the model, the areas that need more research for making educated decisions are defined. The model suggests the high-level critical parameters that need proper control measures are complexity of waterways, traffic situations encountered, and off-coursed ships. The critical area that calls for more investigation is the onboard presence of a sea-pilot.

Details

Original languageEnglish
Pages (from-to)195-210
Number of pages16
JournalSafety Science
Volume86
Publication statusPublished - 1 Jul 2016
MoE publication typeA1 Journal article-refereed

    Research areas

  • Bayesian Belief Network, Evidenced-based modeling, Ship-grounding, Strength of knowledge

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