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This paper presents the modeling of car passenger ferryship design parameters with respect to such design criteria as selected sea-keeping qualities and additional resistance in waves. In the first part of the investigations approximations of selected statistical parameters of design criteria of ferryship were elaborated with respect to ship design parameters. The approximation functions were obtained with the use of artificial neural networks. In the second part of the investigations design solutions were searched for by applying the single- and multi-criterial optimization methods. The multi-criterial optimization was performed by using Pareto method. Such approach made it possible to present solutions in such form as to allow decision makers (shipowner, designer) to select solutions the most favourable in each individual case
In the paper, were presented approximations of numerical calculations of ships roll on thebasis of main service parameters of the ship. This way were obtained several relationshipswhich make it possible to approximate ship roll in regular and irregular waves by usingthe parameters available in the phase of voyage routing. The relationships were elabora-ted by means of artificial neural networks as well as linear and non-linear regressionmethods. A comparative analysis of the methods regarding approximation accuracyagainst standard data was also performed
This paper presents a method which makes it possible to determine optimum hull form of passenger car ferry with regard to selected sea-keeping qualities and additional resistance in waves. In the first phase of investigations a hull form characterized by the highestqualities was selected from the list of similar ships. Next, its optimum dimension ratios were determined. Design criteria were formulated by using a method based on deterministic scenarios, but objective functions of partial targets were determined in the form of artificialneural networks. To select the best design variants elements of fuzzy logic were used, that made it possible a.o. to show merits of the design by means of linguistic variables. Such approach made it possible to find the best hull form and its dimensions from the point of view of all considered criteriasimultaneously
The main scientific aim of this research was to elaborate design guidelines which could make it possible to improve sea-keeping qualities of passenger-car ferries. The searched- for design guidelines were prepared in the form of regression functions as well as artificial neural networks on the basis of the results obtained from calculations with the use of numerical methods based on the theory of planar flow around a body. The guidelines make it possible to predict ship roll, sea-sickness index, lateral and vertical accelerations on the basis of quantities available in the preliminary stage of ship design
This article presents regression formulas for the preliminary design of tankers, bulk carriers and container vessels, based on the data of ships built from 2000 to 2018. The formulas could have practical application for the estimation of total engine power by using ship’s deadweight or TEU capacity and speed.The regressions presented in this article are based on the most recent data and were developed for individual sub-types of tankers, bulk carriers and container ships. The presented regressions comply with trends found in the literature and offer greater accuracy for characteristics of new-built ships
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
This paper presents approximations of pitching motion of S-175 containership in irregular waves within the full range of ship’s serviceparameters. It continues the research described in [1] dealing with application of artificial neural network stop redict ship’s motions.Referencepitch values were calculated by means of SEAWAY software based on accurate numerical methods. Approximating function was elaborated by using the artificial neural networks
In this paper a method is presented of modelling the green water ingress into holds of open-top containership, which can be useful in the preliminary ship design phase. As a result of the research a mathematical formula which makes it possible to determine a minimum freeboard height with a view of as- low- as- possible occurrence rate of green water ingress into holds at given ship design parameters, was obtained. The research was carried out under assumption of constant ship hull dimensions. The design formula was elaborated by using a method based on a goal-oriented conceptual approach to formulation of design criteria, proposed by IMO. On the basis of the concept a deterministic scenario describing operational conditions of the ship in question, was assumed, and for the conditions the research was performed
In this paper are presented problems of modelling seakeeping qualities of open-top container carriers in the preliminary design phase. Approximations of accelerations and occurrence rate of green water ingress to holds are presented in function of main ship design and wave parameters. The approximations have been elaborated by applying theory of artificial neural networks in the wide range of ship hull dimensions and forms, while ship motion and wave parameters have been limited to real operational conditions described by means of the so called operational scenario. Such approach has made it possible to reach high accuracy of approximation and simple structure of mathematical model simulatneously
The article presents the mathematical function to calculate the added wave resistance transfer function for bulk carriers. Based on this function, the statistical mean added wave resistance generated by an irregular head wave with arbitrary statistical parameters can be forecasted. The input parameters are: waterplane area, waterplane coefficient, ship speed, and frequency of the regular wave. The model has been developed based on the theory of artificial neural networks. The presented function can be used in design analyses, and for planning shipping routes in situations when basic geometrical parameters of the hull are only available and not the full technical documentation. The article presents sample cases of use of this function to calculate the added wave resistance transfer function and the statistical mean added wave resistance. Another presented application refers to waterplane coefficient optimisation taking into account the added wave resistance at the stage of preliminary bulk carrier design
This paper presents a new approach which makes it possible to take into account seakeeping qualities of ship in the preliminary stage of its design. The presented concept is based on representing ship’s behaviour in waves by means of the so called operational effectiveness index. Presented values of the index were calculated for a broad range of design parameters. On this basis were elaborated analytical functions which approximate the index depending on ship design parameters. Also, example approximations of the index calculated by using artificial neural networks, are attached. The presented approach may find application to ship preliminary design problems as well as in ship service stage to assess sea-keeping performance of a ship before its departure to sea
This paper presents an application of artificial neural networks to approximation andidentification of additional wave-generated resistance, slamming and internal forcesdepending on ship motion and wave parameters. The analysis was performed for a typical bulk carrier in ballast loading conditions. The investigations were carried out on the basis of ship response data calculated by means of exact numerical methods. Analytical functions presented in the form of artificial neural networks were analyzed with a viewof their accuracy against standard values. Possible ways of application of the artificialneural networks were examined from the point of view of accuracy of approximation and identification ofthe assumed ship response parameters
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