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

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Mazaheri, Arsham
dc.contributor.author Montewka, Jakub
dc.contributor.author Kujala, Pentti
dc.date.accessioned 2017-05-11T09:16:10Z
dc.date.available 2017-05-11T09:16:10Z
dc.date.issued 2016-07-01
dc.identifier.citation Mazaheri , A , Montewka , J & Kujala , P 2016 , ' Towards an evidence-based probabilistic risk model for ship-grounding accidents ' SAFETY SCIENCE , vol 86 , pp. 195-210 . DOI: 10.1016/j.ssci.2016.03.002 en
dc.identifier.issn 0925-7535
dc.identifier.other PURE UUID: fac34927-0266-47dd-895f-5d2b8d1662c0
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/towards-an-evidencebased-probabilistic-risk-model-for-shipgrounding-accidents(fac34927-0266-47dd-895f-5d2b8d1662c0).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=84960384007&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/11427281/mazaheri_safety_science.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/25987
dc.description.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. en
dc.format.extent 16
dc.format.extent 195-210
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries SAFETY SCIENCE en
dc.relation.ispartofseries Volume 86 en
dc.rights openAccess en
dc.subject.other Safety Research en
dc.subject.other Public Health, Environmental and Occupational Health en
dc.subject.other Safety, Risk, Reliability and Quality en
dc.subject.other 222 Other engineering and technologies en
dc.title Towards an evidence-based probabilistic risk model for ship-grounding accidents en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department School services, ENG
dc.contributor.department Department of Mechanical Engineering
dc.subject.keyword Bayesian Belief Network
dc.subject.keyword Evidenced-based modeling
dc.subject.keyword Ship-grounding
dc.subject.keyword Strength of knowledge
dc.subject.keyword Safety Research
dc.subject.keyword Public Health, Environmental and Occupational Health
dc.subject.keyword Safety, Risk, Reliability and Quality
dc.subject.keyword 222 Other engineering and technologies
dc.identifier.urn URN:NBN:fi:aalto-201705114362
dc.identifier.doi 10.1016/j.ssci.2016.03.002
dc.type.version publishedVersion


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