The article presents the Seakeeping research software, developed for the computation of a ship’s motions in regular and irregular waves on the basis of the following ship parameters: length between perpendiculars, beam, draught, block coefficient and transverse initial metacentric height. The software implements approximating functions of amplitude-phase characteristics of rolling, heaving, and pitching, developed by the author by means of artificial neural networks. The software determines transfer functions for the phenomena accompanying the rolling motion, such as slamming, green water, propeller surfacing, vertical acceleration forward and on the bridge. The article discusses possible uses of the software in scientific research, ship design and operation, and for educational purposes.
Problems concerning preliminary design of FPSO vessels are presented in view of their seakeeping ability. The article analyzes the presently applied approach in which seakeeping quality of FPSO vessels is taken into consideration and discusses possibilities of using this approach at the preliminary stage of design. Besides, the current approach used for predicting such phenomena as heaving, slamming and green water loading is discussed.
PL
W artykule przedstawiono problematykę projektowania wstępnego statków FPSO, biorąc pod uwagę właściwości morskie tych statków. W artykule przeanalizowano aktualnie stosowane podejście, dotyczące uwzględniania właściwości morskich statków FPSO i możliwości wykorzystania tego podejścia na wstępnym etapie projektowania. W artykule przedstawiono aktualnie stosowane podejście do prognozowania m.in. nurzań, slemingu i zalewania pokładu statków FPSO.
This paper presents an analysis of a presently applied approach to accounting for seakeeping qualities of FPSO sea-going ships and possible using it in preliminary design stage. Approximations of heaving, pitching, green water ingress on the deck and slamming of FPSO ships, based on main ship design and wave parameters, are presented. The approximations were elaborated with the use of the linear regression method and theory of artificial neural networks for a very wide range of FPSO ship dimensions and hull forms. In the investigations ship operational conditions were limited to those occurring in real service of FPSO ships, described by means of the so called operational scenario. Such approach made it possible to reach simultaneously high approximation accuracy and simple structure of mathematical model.
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