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A stochastic method for the prediction of icebreaker bow extreme stresses

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Abstract It is well established that the ship-ice interaction process is quite complex and associated ice loads on the icebreaker hull is a stochastic process. Obviously, novel accurate statistical methods… Click to show full abstract

Abstract It is well established that the ship-ice interaction process is quite complex and associated ice loads on the icebreaker hull is a stochastic process. Obviously, novel accurate statistical methods and models should be developed and applied to estimate extreme bow stresses. This paper studies icebreaker bow stresses based on measured distribution of ice thickness in the Arctic Ocean on the way to and from the North Pole. Since the vessel route was carefully selected searching for easier ice conditions, the Arctic Ocean crossing was not a straight linear but a meandering path. Thus, the specific ship route data was biased with respect to general ice statistics in the region, but true with respect to the route specific ice data encountered by a ship navigating in that region. Therefore the route specific ice thickness data is directly needed for ship design and navigation analysis. It is assumed that captains are competent and knowledgeable, and therefore will select a route that provides the most favourable ice conditions. This paper contributes to study of the newest Chinese self-designed polar icebreaker, serving the purpose of enhancing icebreaker operational reliability. Finite Element Method software package ANSYS/LS-DYNA has been employed to simulate bow stress pattern for a particular icebreaker operating in the Arctic Ocean. Extreme bow stresses were estimated using Naess-Gaidai method. The latter is a first application of Naess-Gaidai method to a distribution with lower bound. Thus this paper aims at introducing an efficient method of estimating route-specific icebreaker extreme bow stresses.

Keywords: bow; method; route; extreme; ice; icebreaker

Journal Title: Applied Ocean Research
Year Published: 2019

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