Spectral Analysis of Ship-Generated Waves in Finite-Depth Water

2002 ◽  
Author(s):  
Carl A. Scragg
Keyword(s):  
Deep Water ◽  
Wave Spectrum ◽  
Finite Depth ◽  
Far Field ◽  
Wave Spectra ◽  
Data Set ◽  
Free Wave ◽  
Common Reference ◽  
Depth Water ◽  
Wave Elevations

Recent efforts to compare the waves generated by different vessels traveling in finite-depth water have struggled with difficulties presented by various data sets of wave elevations (either measurements or predictions) corresponding to different lateral distances from the ship. Some of the attempts to shift the data to a common reference location have relied upon crude and potentially misleading approximations. The use of free-wave spectral-methods not only overcomes such difficulties, but it also provides us the means to accurately extend CFD results into the far field. As in the deep-water case, one can define a free-wave spectrum that is valid for all lateral positions and distances astern of the vessel. The free-wave spectrum contains a complete description of the Kelvin wake, and wave elevations at any far-field position can be readily calculated once the spectrum is known. For the case of infinitely deep water, Eggers, Sharma, and Ward [1967] presented a method by which free-wave spectra can be determined from appropriate measurements of the far-field wave elevations. The current paper discusses the use of free-wave spectra for finite-depth problems and presents a method for the determination of free-wave spectra based upon fitting predicted wave elevations to a corresponding data set. The predicted wave elevations can be calculated from an unknown distribution of finite-depth Havelock singularities. The unknown singularities are determined by minimizing the mean-square-difference between predicted and measured wave fields. The method appears to be quite general and can be used to calculate either finite or infinite-depth free-wave spectra from experimental data or from local CFD predictions.

Spectral Representation of Ship-Generated Waves in Finite-Depth Water

2003 ◽  
Vol 125 (1) ◽  
pp. 65-71 ◽  
Author(s):  
Carl A. Scragg
Keyword(s):  
Deep Water ◽  
Wave Spectrum ◽  
Finite Depth ◽  
Far Field ◽  
Wave Spectra ◽  
Data Set ◽  
Free Wave ◽  
Common Reference ◽  
Depth Water ◽  
Wave Elevations

Recent efforts to compare the waves generated by different vessels traveling in finite-depth water have struggled with difficulties presented by various data sets of wave elevations (either measurements or predictions) corresponding to different lateral distances from the ship. Some of the attempts to shift the data to a common reference location have relied upon crude and potentially misleading approximations. The use of free-wave spectral-methods not only overcomes such difficulties, but is also provides us the means to accurately extend CFD results into the far field. As in the deep-water case, one can define a free-wave spectrum that is valid for all lateral positions and distances astern of the vessel. The free-wave spectrum contains a complete description of the Kelvin wake, and wave elevations at any far-field position can be readily calculated once the spectrum is known. For the case of infinitely deep water, Eggers, Sharma, and Ward [1] presented a method by which free-wave spectra can be determined from appropriate measurements of the far-field wave elevations. The current paper discusses the use of free-wave spectra for finite-depth problems and presents a method for the determination of free-wave spectra based upon fitting predicted wave elevations to a corresponding data set. The predicted wave elevations can be calculated from an unknown distribution of finite-depth Havelock singularities. The unknown singularities are determined by minimizing the mean-square-difference between predicted and measured wave fields. The method appears to be quite general and can be used to calculate either finite or infinite-depth free-wave spectra from experimental data or from local CFD predictions.

Ocean Wave Measurements From ENVISAT ASAR Data Using a Parametric Inversion Scheme

2004 ◽  
Author(s):  
J. Schulz-Stellenfleth ◽  
S. Lehner ◽  
D. Hoja ◽  
J. C. Nieto-Borge
Keyword(s):  
A Priori ◽  
Wave Spectrum ◽  
Global Scale ◽  
Wave Mode ◽  
Ocean Wave ◽  
Wave System ◽  
Wave Spectra ◽  
Data Set ◽  
Envisat Asar ◽  
Sar Imaging

A parametric algorithm is presented to estimate two-dimensional ocean wave spectra from ENVISAT ASAR wave mode data on a global scale. The retrieval scheme makes use of prior information taken from numerical wave models. The Partition Rescale and Shift algorithm (PARSA) is based on a partitioning technique, which splits an a priori wave spectrum into its wave system components. Integral parameters of these systems, such as mean direction, mean wavelength, waveheight, and directional spreading are then adjusted iteratively to improve the consistency with the SAR observation. The method takes into account the full nonlinear SAR imaging process and uses a maximum a posteriori approach, which is based on statistical model quantifying the errors of the SAR imaging model, the SAR measurement, and the prior wave spectra. The method is applied to a global data set of ENVISAT ASAR data acquired during the CAL/VAL phase. The benefit of cross spectra compared to conventional symmetric image spectra is demonstrated.

Similarity of the wind wave spectrum in finite depth water part 2: Statistical relations between shape and growth stage parameters

1987 ◽  
Vol 40 (1) ◽  
pp. 1-24 ◽  
Author(s):  
Evert Bouws ◽  
Heinz Günther ◽  
Wolfgang Rosenthal ◽  
Charles L. Vincent
Keyword(s):  
Growth Stage ◽  
Wind Wave ◽  
Wave Spectrum ◽  
Finite Depth ◽  
Depth Water

scholarly journals WAVE GROUP ANATOMY OF OCEAN WAVE SPECTRA

1984 ◽  
Vol 1 (19) ◽  
pp. 45 ◽  
Author(s):  
Warren C. Thompson ◽  
Arthur R. Nelson ◽  
Dean G. Sedivy
Keyword(s):  
Statistical Analysis ◽  
Deep Water ◽  
Wave Spectrum ◽  
Ocean Wave ◽  
Group Model ◽  
Wave Spectra ◽  
Wave Group ◽  
Wave Groups

This paper inquires into the questions of how wave groups are related to the wave spectrum, and how they differ in sea versus swell. Some results are presented in the form of a wave group model for sea spectra and for swell spectra. The models were developed from statistical analysis of a large number of wave records and apply to deep water only.

scholarly journals ON A DESIGN WAVE SPECTRUM

1984 ◽  
Vol 1 (19) ◽  
pp. 25
Author(s):  
Paul C. Liu
Keyword(s):  
Great Lakes ◽  
Wave Height ◽  
Deep Water ◽  
Water Wave ◽  
Significant Wave Height ◽  
Wave Spectrum ◽  
Wave Spectra ◽  
Practical Applications ◽  
Average Wave ◽  
Deep Water Wave

We propose the use of a generalized representation for acquiring a design wave spectrum. The generalized form, free from any predetermined coefficients and exponents, requires only significant wave height and average wave period as input for practical applications. The usefulness of this representation has been demonstrated with over 2000 measured deep-water wave spectra recorded from NOMAD buoys in the Great Lakes during 1981.

Similarity of the wind wave spectrum in finite depth water: 1. Spectral form

1985 ◽  
Vol 90 (C1) ◽  
pp. 975 ◽  
Author(s):  
E. Bouws ◽  
H. Günther ◽  
W. Rosenthal ◽  
C. L. Vincent
Keyword(s):  
Wind Wave ◽  
Wave Spectrum ◽  
Finite Depth ◽  
Spectral Form ◽  
Depth Water

Evaluation of Directional Analysis Methods for Low-Frequency Waves to Predict LNGC Motion Response in Nearshore Areas

2013 ◽  
Author(s):  
Sanne van Essen ◽  
Arne van der Hout ◽  
René Huijsmans ◽  
Olaf Waals
Keyword(s):  
Shallow Water ◽  
Wave Field ◽  
Wave Spectrum ◽  
Low Frequency ◽  
Wave Frequency ◽  
Stochastic Methods ◽  
Wave Spectra ◽  
Wave Fields ◽  
Free Wave

Because LNG terminals are located increasingly close to shore, the importance of shallow-water effects associated with low-frequency (LF) waves increases as well. The LF wave spectrum in these areas is generally complex, with multiple frequency peaks and/or directional peaks due to LF wave interaction with the shore. Both free and bound LF waves at the same frequency can be present. Since LF waves are potentially very significant for moored vessel motions, it is important to include their effect in an early stage of the terminal design. This requires an efficient and relatively simple tool able to estimate the LF wave spectrum in nearshore areas. The benefit of such a procedure with respect to state-of-the-art response methods is the ability to include the LF free wave distribution in a local wave field in the vessel response calculation. The objectives of the present study are to identify such a tool, and to evaluate the use of its output as input for a vessel motion calculation. Three methods, designed for the determination of wave spectra of free wave-frequency (WF) waves, were applied to artificial LF wave fields for comparison of their performance. Two stochastic methods, EMEP (Hashimoto et al., 1994) and BDM (Hashimoto et al., 1987) and one deterministic method, r-DPRA (De Jong and Borsboom, 2012) were selected for this comparison. The foreseen application is beyond the formal capabilities for which these three methods were intended. However, in this study we have investigated how far we can take these existing methods for the determination of directional LF wave spectra. Sensitivity analyses showed that the EMEP method is the most suitable method of the three for a range of LF wave fields. The reconstructed LF wave spectra using EMEP resembled the input spectra most closely over the whole range of water depths and frequencies, although its performance deteriorated with increasing water depth and wave frequency. Subsequently, a first effort was made to use the information in the reconstructed EMEP LF wave spectrum of a representative shallow-water wave field for a first estimate of the motions of a moored LNG carrier. The results were acceptable. This is a first indication that EMEP output might be used to calculate the motions of an LNG carrier moored in shallow water.

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