Memorial University DAI: Ship manoeuvrability prediction using neural networks

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Title	Ship manoeuvrability prediction using neural networks
Author	Wang, Yie, 1966-
Description	Thesis (M.Eng.)--Memorial University of Newfoundland, 1996. Engineering and Applied Science
Date	1996
Pagination	144 leaves : graphs
Subject	Ships--Maneuverability--Computer simulation; Neural networks (Computer science)
Degree	M.Eng.
Degree Grantor	Memorial University of Newfoundland. Faculty of Engineering and Applied Science
Discipline	Engineering and Applied Science
Language	Eng
Notes	Bibliography: leaves 119-122.
Abstract	This thesis is divided into three parts. The first two parts deal with two different methods for predicting the manoeuvring characteristics of ships using a neural network technique. The third part deals with the application of the random decrement concept to the coupled sway-yaw motions. -- In the first part of this thesis, a new predictive method is presented for the estimation of the hydrodynamic characteristics of a ship performing certain standard manoeuvres. This method uses the static neural network technique to predict the nonlinear hydrodynamic forces of the ship during its motion in the horizontal plane. The neural network model uses a steepest descent search to find the neural network weights. In this thesis, a back propagation algorithm is used to calculate the slope of the sum-of-squared-error curve as a function of the different weights. Data for training the neural network consists of the data from a 35-35 degree zigzag manoeuvre. Surge, sway, yaw velocities and rudder angles are used as input to the predictive model. The target output data are the lumped nonlinear hydrodynamic functions. -- The generalization of the trained neural network model is checked by simulating the manoeuvres of the ship in a situation different from the one used in the training of neural network. A moderate 20-20 degree zigzag manoeuvre, a 25 degree turning (starboard) and a 20 degree Dieudonne spiral manoeuvre are selected to check the validity of the neural network model. -- In the second part of this thesis, another approach to predict ship turning manoeuvres is proposed. This model maps the relationship between sway velocities and yaw rates during the circular manoeuvre using a neural network technique. This method reduces the number of equations to be used in the prediction to a single yaw equation. This new yaw equation can then be used for predicting turning manoeuvres. -- In the last part of the thesis work, the extension of the random decrement approach to the nonlinear sway-yaw motions is presented. The random waves are simulated based on the ITTC spectrum formula. The linear system and the nonlinear system of sway and yaw motion equations are discussed. The autocorrelation functions of the response of sway and yaw velocities in random waves are obtained. A method for using these functions to identify the hydrodynamic characteristics of the coupled sway-yaw motions is suggested.
Type	Text
Resource Type	Electronic thesis or dissertation
Format	Image/jpeg; Application/pdf
Source	Paper copy kept in the Centre for Newfoundland Studies, Memorial University Libraries
Local Identifier	a1177851
Rights	The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.
Collection	Electronic Theses and Dissertations
Scanning Status	Completed
PDF File	(8.32 MB) -- http://collections.mun.ca/PDFs/theses/YieWang.pdf
CONTENTdm file name	31820.cpd