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Statistical Estimation of Two-Body Hydrodynamic Properties Using System Identification

A basic understanding of the hydrodynamic response behavior of the two-body system is
important for a wide variety of offshore operations. This is a complex problem and
model tests can provide data that in turn can be used to retrieve key information
concerning the response characteristics of such systems. The current study demonstrates
that the analysis of these data using a combination of statistical tools and system
identification techniques can efficiently recover the main hydrodynamic parameters
useful in design.
The computation of the statistical parameters, spectral densities and coherence functions
provides an overview of the general response behavior of the system. The statistical
analysis also guides the selection of the nonlinear terms that will be used in the reverse
multi-input / single-output (R-MI/SO) system identification method in this study. With
appropriate linear and nonlinear terms included in the equation of motion, the R-MISO
technique is able to estimate the main hydrodynamic parameters that characterize the
offshore system. In the past, the R-MISO method was primarily applied to single body
systems, while in the current study a ship moored to a fixed barge was investigated. The formulation included frequency-dependant hydrodynamic parameters which were
evaluated from the experimental measurements. Several issues specific to this extension
were addressed including the computation load, the interpretation of the results and the
validation of the model. Only the most important cross-coupling terms were chosen to
be kept based on the estimation of their energy. It is shown that both the heading and the
loading condition can influence system motion behavior and that the impact of the wave
in the gap between the two vessels is important. The coherence was computed to verify
goodness-of-fit of the model, the results were overall satisfying.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2009-08-7062
Date14 January 2010
CreatorsXie, Chen
ContributorsNiedzwecki, John M.
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeBook, Thesis, Electronic Dissertation
Formatapplication/pdf

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