Prokopis Vlachogiannis
Offshore wind is essential in the global transition to Net Zero carbon emission goals. As the industry pushes into deeper waters, bottom-fixed offshore wind solutions are no longer viable, increasing the reliance on floating alternatives. During their operational lifespan exceeding 25 years, floating wind turbines are exposed to stochastic winds, waves, currents, and the nonlinear coupled effects of these loads, making fatigue assessment critical in their design and maintenance planning. The state-of-the-art industry approach is grouping similar met-ocean conditions together into bins, each with an associated probability of occurrence based on historical data. However, by assuming all members inside the same bin are equivalent, this approach loses information, leading to inaccuracies. In this work, a higher-resolution approach is proposed, the Numerical Prototype, where each individual sea state is considered. This approach, presented in two parts, better replicates the real world environmental loading, due to lower levels of averaging and higher detail in the representation of the met-ocean conditions. In Part 1, the Numerical Prototype is compared with a reference binning method using equally sized bins and an optimised binning method adapted to data density. The tower base and mooring fairleads are studied, being well known hotspots of fatigue. The case study uses the UMaine VolturnUS-S/IEA 15 MW structure for a site in South Brittany, France. The Numerical Prototype yields lower cumulative fatigue estimations by 24% for the turbine tower and 14% for the mooring line fairleads compared to the classical binning method. The main contributing factors are 2D wave spectra for the tower base and reduced averaging for the mooring lines, with offshore- and site-specific turbulence intensity (TI) also contributing. These results demonstrate the conservatism of existing methods that lead to over-engineering. Part 2 addresses the conservatism of using 90th-percentile Turbulence Intensity levels for fatigue calculations. To derive a representative Turbulence Intensity for the studied site, a Monte Carlo approach is applied using approximately 79000 sea states. The analysis yields additional reduction of 43% and 55% of cumulative fatigue for the tower base and mooring fairlead, respectively. A sensitivity analysis suggests a fatigue representative Turbulence Intensity quartile of 70%. In this work, for the first time, a detailed methodology for fatigue estimation is presented that works as an upper bound of modelling accuracy. It quantifies the conservatism of the current industry fatigue calculation methodology and proposes improvements that allow optimised designs and reduce structural weight with consequent savings in both installation and material costs.