Problem description:
Probability distribution function (PDF) of ocean-wave crests/heights is a key design property for the offshore and maritime industries. The present approach to deriving and improving accuracy of such PDF is based on a bulk approach: i.e. researchers and ocean engineers aim at obtaining as much as possible field in situ measurements and use such data to investigate and parameterise some average PDF by means of such large ensembles. Babanin (2013, OMAE) argued that in this way data from different statistical families are brought together which impedes and ultimately makes it impossible to advance the knowledge of PDF beyond some limits. This is because physical environments are different among physical regimes which roughly can be subdivided into three major categories. First category covers stable wave fields, for which second-to-third approximation for Stokes waves should be sufficient. Second-category wave fields are subject to modulational instability which makes occasional waves grow very high and causes even rare rogue-wave events. Probability distributions of waves crests in such surface fields have to be treated and described separately and differently. The third category is waves in extreme metocean conditions, such as tropical cyclones. Wave dynamics, wind-wave and nonlinear interactions, wave breaking, instability mechanisms are different in such conditions, and therefore such waves belong to a different PDF.
Therefore, it is proposed to use the available data to separate the wave fields into 1) stable; 2) unstable; 3) extreme – and to build separate PDFs for these wave fields. This will be a principally novel way to approach the old problem and to describe probability distributions of the open ocean wave crests and heights.
Data description:
Extended data sets of in situ measurements in the Indian Ocean and the North Sea, including extreme tropical and extra-tropical cyclones, and of numerical simulations of stable and unstable wave fields with fully nonlinear wave model.
Supervisors:
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Erik Vanem, UiO and DNV
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Alexander Babanin, University of Melbourne
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Riccardo de Bin, UiO
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Odin Gramstad, DNV
Scope: 60 study points
Additional information (why choose this project):
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This master project will address an actual problem with high interest from the industry and academia
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Collaboration with industry, DNV
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International project with collaboration with University of Melbourne, Australia
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Cross-disciplinary project between statistics and ocean engineering
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A good thesis will hopefully get its results published as a scientific paper (supervisors can help preparing the paper if the student doesn’t have time)
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Results will potentially have an impact on the ocean engineering industry
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A successful student will have the opportunity to continue studies as a PhD student at University of Melbourne
References:
Alexander V. Babanin. Physics-based approach to wave statistics and probability. In Proc. OMAE 2013
George Z. Foristall. Wave Crest Distributions: Observations and Second-Order Theory. Journal of Physical Oceanography, Vol. 30, pp. 1931-1943, 2000
Marios Christou and Kevin Ewans. Field Measurements of Rogue Water Waves. Journal of Physical Oceanography, Vol. 44, pp. 2317-2335, 2014
Richard Gibson, Marios Christou and Graham Feld. The statistics of wave height and crest elevation during the December 2012 storm in the North Sea. Ocean Dynamics, Vol. 64, pp. 1305-1317, 2014