Jean-Baptiste Saulnier

Extreme Sea Conditions in Shallow Water: Estimations Based on In-Situ Measurements

This paper focuses on the assessment of the environmental extreme conditions in term of wind and waves at the SEMREV wave energy test site for application in the design of Marine Renewable Energy (MRE) devices and components. The paper will first present the existing in situ wind and wave measurements. A prediction chain from global to regional scales, and based on a regional wave model calibrated at the SEMREV location, is then described. It enables to build a specific 22 year hindcast dataset for the test site. Long term extrapolation is finally achieved at the SEMREV location using existing methodologies for deep water conditions. Long term extrapolations methods are usually very sensitive to the parameterization and configuration of the prediction chain and we demonstrate in this study that the best overall performances are reached by a POT method at this stage of development in the prediction chain.Copyright

Peakedness of Wave Systems Observed on the French Wave Energy Test Site (SEM-REV) Using a Spectral Partitioning Algorithm

Located off the Guerande peninsula, SEM-REV is the French maritime facility dedicated to the testing of wave energy converters and related components. Lead by Ecole Centrale de Nantes through the LHEEA laboratory, its aim is to promote research alongside the development of new offshore technologies. To this end, the 1km2, grid-connected zone is equipped with a comprehensive instruments network sensing met-ocean processes and especially waves, with two identical directional Waverider buoys deployed on the site since 2009.For the design of moored floating structures and, a fortiori, floating marine energy converters, the knowledge of the main wave resource — for regular operation — but also extreme conditions — for moorings and device survivability — has to be as precise as possible. Also, the consideration of the multiple wave systems (swell, wind sea) making up the sea state is a key asset for the support of developers before and during the testing phase.To this end, a spectral partitioning algorithm has been implemented which enables the individual characterisation of wave systems, in particular that of their spectral peakedness which is especially addressed in this work. Peakedness has been shown to be strongly related to the groupiness of large waves and is defined here as the standard JONSWAP’s peak enhancement factor γ. Statistics related to this quantity are derived from the measurement network, with a particular focus on the extreme conditions reported on SEM-REV (Joachim storm).Copyright

Uncertainty in Peakedness Factor Estimation by JONSWAP Spectral Fitting From Measurements

In offshore engineering, JONSWAP shapes are commonly used to fit wave spectra and characterise the peakedness of the sea state. The latter is defined as γ, the so-called peak enhancement factor, which is as large as the peak is acute, with values generally ranging from ∼1 to 7 (1 and 3.3 being usually adopted for fully-developed and average wind seas respectively). The determination of γ values permit to simulate realistic sea conditions later on, in particular for determining extreme loads on floating structures in severe sea states.The consistency of the fitting with respect to the actual sea state is subject to — at least — two key, connected aspects, which are: the frequency resolution (i.e., the spacing between two consecutive spectrum estimates) and the sampling error (i.e., the statistical variability of estimates due to both the finiteness of the wave record and the spectral averaging).Based on realistic sea state spectral simulations, this work addresses the sensitivity of the JONSWAP fitting to these aspects and shows that it systematically results in a bias in the peakedness estimate — the bias being aggravated when the sampling error is large for a given signal length (from 10min to 1h). It is shown, in particular, that the error committed with respect to the true γ value is generally higher than 5% for most types of peaks and may often exceed 30%.The aim of this work is to emphasize this issue for practical offshore and oceanographic applications for it may, in turn, potentially introduce a bias in the dynamic response of floating structures in numerical simulations and tank tests.© 2013 ASME