The DeRisk database: Extreme Design Waves for Offshore Wind Turbines

The estimation of extreme loads from waves is an essential part of the design of an offshore wind turbine. Standard design codes suggest to either use simplified methods based on regular waves, or to perform fully nonlinear computations. The former might not provide an accurate representation of the extreme waves, while the latter is computationally too intensive for design iterations. We address these limitations by using the fully nonlinear solver OceanWave3D to establish the DeRisk database, a large dataset of extreme waves kinematics in a two-dimensional domain. From the database, which is open and freely available, a designer can extract fully-nonlinear wave kinematics for a wave condition and water depth of interest by identifying a suitable computation in the database and, if needed, by Froude-scaling the kinematics. The nonlinear solver is validated against the DeRisk model experiments at two different water depths, $33.0 [m]$ and $20.0 [m]$, and an excellent agreement is found for the analyzed cases. The experiments are used to calibrate OceanWave3D's numerical breaking filter constant, and the best agreement is found for $\beta=0.5$. We compare the experimental static force with predictions by the DeRisk database and the Rainey force model, and with state-of-the-art industrial practices. For milder storms, we find a good agreement in the predicted extreme force between the present methodology and the standard methodologies. At the deep location and for stronger storms, the largest loads are given by slamming loads due to breaking waves. In this condition, the database methodology is less accurate than the embedded stream function method and more accurate than the WiFi JIP methodology, providing generally nonconservative estimates. For strong storms at the shallower location, where wave breaking is less dominating, the database methodology is the most accurate overall.
Comment: Submitted to Marine Structures (Elsevier), 46 pages, 16 figures, 6 tables. The database associated with the publication is available at https://data.dtu.dk/articles/dataset/The_DeRisk_Database/10322033