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A framework for evidence-based risk modeling of ship grounding

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Montewka, Jakub, Dr., Aalto University, Department of Mechanical Engineering, Finland
dc.contributor.author Mazaheri, Arsham
dc.date.accessioned 2017-06-10T09:02:48Z
dc.date.available 2017-06-10T09:02:48Z
dc.date.issued 2017
dc.identifier.isbn 978-952-60-7478-8 (electronic)
dc.identifier.isbn 978-952-60-7479-5 (printed)
dc.identifier.issn 1799-4942 (electronic)
dc.identifier.issn 1799-4934 (printed)
dc.identifier.issn 1799-4934 (ISSN-L)
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/26625
dc.description.abstract Most of the risk models for ship-grounding accidents do not fully utilize available evidence, since in general they are merely based on accident statistics and expert opinions. The major issue with models of such kind is their limitation in supporting the process of risk management with respect to grounding accidents; because they do not necessarily reflect the reality to the extent required.  This thesis proposes an evidence-based framework for building evidence-based risk models for probabilistic assessment of ship grounding. In order to build the evidence required for creating the evidence-based risk model, traffic characteristics as primary source of data are extracted from AIS data and accident statistics of the Gulf of Finland. Additionally, using expert knowledge of the local pilots in the Gulf of Finland, a location dependent and semi-quantitative index as Waterway Complexity Index is defined to assess the dependency of ship grounding and navigational difficulty of a waterway to handle a ship. Moreover, ship grounding incident and accident reports from Finnish, Swedish, and British maritime authorities are utilized as primary and secondary sources of data respectively to build the required evidence for constructing the risk model. In this regard, two frameworks are introduced in this thesis to review and extract the embedded information from the reports. A new version of Human Factors Analysis and Classification System (HFACS) is introduced as a framework to review the grounding accident reports; and a new positive taxonomy as Safety Factors, which are based on high level positive functions that are prerequisite for safe transport operations, is introduced to review the grounding incident reports.  Utilizing the proposed framework for evidence-based risk modeling as well as the built evidence from primary and secondary sources of data and expert knowledge, a Bayesian Network risk model is developed in this thesis for assessing the probability of ship grounding accidents. The uncertainties associated with the elements of the model are clearly communicated to the end user adopting a concept of strength of knowledge, and by introducing knowledge strength map for the built model. Therefore, it is argued in this thesis that the developed model is more suitable for risk management purposes, and the model can be used to suggest proper risk-control-measures to mitigate the risk of ship grounding accident. The developed model in this thesis 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 62 + app. 90
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Aalto University en
dc.publisher Aalto-yliopisto fi
dc.relation.ispartofseries Aalto University publication series DOCTORAL DISSERTATIONS en
dc.relation.ispartofseries 112/2017
dc.relation.haspart [Publication 1]: Mazaheri, Arsham; Montewka, Jakub; Kujala, Pentti. Modeling the risk of ship grounding – A literature review from a risk management perspective. WMU-Journal of Maritime Affairs, Vol.13, No.2, pp.269-297, October 2014. DOI: 10.1007/s13437-013-0056-3
dc.relation.haspart [Publication 2]: Mazaheri, Arsham; Montewka, Jakub; Kotilainen, Pentti; Sormunen, Otto-Ville Edvard; Kujala, Pentti. Assessing grounding frequency using ship traffic and waterway complexity. The Journal of Navigation, Vol.68, No.01, pp.89-106, January 2015. DOI: 10.1017/S0373463314000502
dc.relation.haspart [Publication 3]: Mazaheri, Arsham; Montewka, Jakub; Nisula, Jari; Kujala, Pentti. Usability of Accident and Incident Reports for Evidence-Based Risk Modeling - A case study on ship grounding reports. Safety Science, Vol.76, July, pp.202-214, July 2015, DOI: 10.1016/j.ssci.2015.02.019
dc.relation.haspart [Publication 4]: Mazaheri, Arsham; Montewka, Jakub; Kujala, Pentti. Towards an evidence-based probabilistic risk model for ship-grounding accidents. Safety Science, Vol. 86, July, pp.195-210, July 2016. DOI: 10.1016/j.ssci.2016.03.002
dc.subject.other Safety technology en
dc.subject.other Marine engineering en
dc.title A framework for evidence-based risk modeling of ship grounding en
dc.type G5 Artikkeliväitöskirja fi
dc.contributor.school Insinööritieteiden korkeakoulu fi
dc.contributor.school School of Engineering en
dc.contributor.department Konetekniikan laitos fi
dc.contributor.department Department of Mechanical Engineering en
dc.subject.keyword evidence-based risk modeling en
dc.subject.keyword ship grounding en
dc.subject.keyword knowledge strength en
dc.subject.keyword background knowledge en
dc.subject.keyword Bayesian Network en
dc.identifier.urn URN:ISBN:978-952-60-7478-8
dc.type.dcmitype text en
dc.type.ontasot Doctoral dissertation (article-based) en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.contributor.supervisor Kujala, Pentti, Prof., Aalto University, Department of Mechanical Engineering, Finland
dc.opn Martins, Marcelo Ramos, Associate Prof., University of São Paulo, Brazil
dc.contributor.lab Research Group on Maritime Risk and Safety en
dc.rev Lützhöft, Margareta, Prof., Australian Maritime College, Australia
dc.rev Bouwer Utne, Ingrid, Prof., Norwegian University of Science and Technology, Norway
dc.date.defence 2017-08-11
local.aalto.formfolder 2017_06_10_klo_11_02
local.aalto.archive yes

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