A fuzzy event tree model for accident scenario analysis of ship stuck in ice in arctic waters

Arctic waters have historically been regarded as harsh environments because of the extreme weather conditions and remoteness from land. The advantages of shorter sea routes and hydrocarbon energy exploitation have recently led to increased marine activities in such harsh environments. Nevertheless,...

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Bibliographic Details
Published in:Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology
Main Authors: Fu, Shanshan, Zhang, Di, Montewka, Jakub, Yan, Xinping, ZIO, ENRICO
Other Authors: Zio, Enrico
Format: Conference Object
Language:English
Published: American Society of Mechanical Engineers (ASME) 2016
Subjects:
Online Access:http://hdl.handle.net/11311/1020931
https://doi.org/10.1115/OMAE2016-54882
http://www.asmedl.org/journals/doc/ASMEDL-home/proc/
Description
Summary:Arctic waters have historically been regarded as harsh environments because of the extreme weather conditions and remoteness from land. The advantages of shorter sea routes and hydrocarbon energy exploitation have recently led to increased marine activities in such harsh environments. Nevertheless, the risks therein need to be systematically identified and assessed. Specifically, the potential consequences of major incidents in Arctic waters should be studied. However, research in this domain is scarce, mainly due to the lack of knowledge and information related to the Arctic marine transportation system (AMTS). In this paper, we present an event tree analysis (ETA) model to illustrate the possible accident scenarios and calculate the probabilities for the associated consequences of ship stuck in ice in Arctic waters. The probability of occurrence of the initiating event and intermediate events in the scenarios are extracted by experts' elicitation and, then, the probabilities of the potential outcome events are computed from the ETA model. Fuzzy set theory is incorporated into the ETA model to handle the epistemic uncertainties in the probability values.