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Mean-Square Non-Local Stability of Ship in Storm Conditions of Operation Cover

Mean-Square Non-Local Stability of Ship in Storm Conditions of Operation

Open Access
|Dec 2019

Abstract

The purpose of the paper is to create a method for studying nonlocal stability in the mean and in the mean square of the ship, positioned on the beam of an intensive wind–waves mode, which is based on the use of the correlation theory of random functions close to continuous Markov processes. With the help of this method and the integral formula of event probability, a method for determining the reliability indicator of the ship in respect of the existing wind–waves excitations of the operating area is formed. An example of investigating the nonlinear motion of the ship, determining its local and nonlocal stability in the first approximation of the theory of considered random functions, is given. Such approximation uses correlation theory with models of acting excitations represented by the generalised derivatives of the Wiener process. Moreover, special attention is paid to reflecting the connection of the proposed methods for investigating the ship stability under constantly acting random excitations with the traditional methods of studying ship stability at small and large inclinations. The established connection defines the proposed methods as a development of the traditional methods of ship stability deterministic theory during the transition to its formation in the class of random functions, with the addition to these methods of the missing link of determining the level of reliability of ships towards the acting wind–waves excitations of the operation area.

DOI: https://doi.org/10.2478/pomr-2019-0061 | Journal eISSN: 2083-7429 | Journal ISSN: 1233-2585
Language: English
Page range: 6 - 15
Published on: Dec 31, 2019
Published by: Gdansk University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 Valeriy Nekrasov, published by Gdansk University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.