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Application of Confidence Regions to Ice Ridge Keel Data Statistical Assessment

[+] Author Affiliations
Petr Zvyagin

Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia

Jaakko Heinonen

VTT Technical Research Centre of Finland Ltd, Espoo, Finland

Paper No. OMAE2017-62253, pp. V008T07A010; 6 pages
doi:10.1115/OMAE2017-62253
From:
  • ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology
  • Trondheim, Norway, June 25–30, 2017
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-5776-2
  • Copyright © 2017 by ASME

abstract

Sets of measurements of underwater ridge parts usually contain a limited amount of data. Outcomes need to be made while relying on small sample sizes. In this event, the chance of making inaccurate estimations increases.

This paper proposes to use stochastic confidence regions in the estimation of the unknown parameters of keel depths. A model for a random variable with a lognormal distribution for keel depths is assumed. Regions for the mean and standard deviation of keel depths are obtained from Mood’s and minimum-area confidence regions for parameters of the normally distributed random variable. Conservative safety probability of non-exceeding the critical keel depth in one random interaction of the ridge with structure is estimated.

An algorithm for statistically assessment of ice ridge keel data by means of confidence region building is here offered. The assessment of a set of ridge keel depths for the Gulf of Bothnia (Baltic Sea) is performed.

Copyright © 2017 by ASME
Topics: Ice ridges , Keel

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