Deriving the absolute wave spectrum from an encountered distribution of wave energy spectral densities

Abstract The objective of ship motion-based wave spectrum estimation is to provide the distribution of wave energy densities in absolute domain. However, as a ship generally advances relative to the progressing waves, any spectrum estimate inherently dates back to the encounter domain and, consequently, the spectrum estimate must be transformed to absolute domain. In following sea conditions, spectrum transformation from encounter to absolute domain has no unique (mathematical) solution. This article presents an optimisation-based technique to carry out the particular transformation in following sea conditions. The optimisation relies on an object function established using (wave) spectral moments; calculated directly using the estimated encounter-wave spectrum on the one side and by using a parameterised wave spectrum valid in absolute domain on the other side. The simplicity of the transformation technique is a strength in itself as it leads to an insignificant computational effort in the transformation to absolute domain. Equally important, the specific technique proves capable to provide accurate results in the majority of cases, when comprehensive testings with numerically simulated data of following sea conditions are performed. Furthermore, the technique is tested successfully using experimental full-scale sea trials data.

[2]  Judith Wolf,et al.  Methods for intercomparison of wave measurements , 1999 .

[3]  Asgeir J. Sørensen,et al.  A brute-force spectral approach for wave estimation using measured vessel motions , 2018 .

[4]  Ulrik Dam Nielsen,et al.  Estimation of wind sea and swell using shipboard measurements – A refined parametric modelling approach , 2016 .

[5]  Ulrik Dam Nielsen Transformation of a wave energy spectrum from encounter to absolute domain when observing from an advancing ship , 2017 .

[6]  Igor Rychlik,et al.  WAFO - A Matlab Toolbox For Analysis of Random Waves And Loads , 2000 .

[7]  Asgeir J. Sørensen,et al.  Sea state estimation using vessel response in dynamic positioning , 2018 .

[8]  M. J. Tucker Recommended standard for wave data sampling and near-real-time processing , 1993 .

[9]  Edward M. Lewandowski,et al.  The Dynamics of Marine Craft: Maneuvering and Seakeeping , 2003 .

[10]  Sverre Haver,et al.  Simplified Double Peak Spectral Model For Ocean Waves , 2004 .

[11]  Alexandre N. Simos,et al.  Estimating directional wave spectrum based on stationary ship motion measurements , 2003 .

[12]  Astrid H. Brodtkorb,et al.  Ship Motion-Based Wave Estimation Using a Spectral Residual-Calculation , 2018, 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO).

[13]  Ulrik Dam Nielsen,et al.  Estimations of on-site directional wave spectra from measured ship responses , 2006 .

[14]  Ulrik Dam Nielsen Introducing two hyperparameters in Bayesian estimation of wave spectra , 2008 .

[15]  R. Bhattacharyya Dynamics of Marine Vehicles , 1978 .

[16]  Toshio Iseki,et al.  Bayesian estimation of directional wave spectra based on ship motions , 1998 .

[17]  Asgeir J. Sørensen,et al.  Ocean Wave Spectral Estimation Using Vessel Wave Frequency Motions , 2007 .

[18]  Lokukaluge P. Perera,et al.  Estimation of directional sea spectra from ship motions in sea trials , 2017 .