Abstract. Fatigue load assessment of floating offshore wind turbines poses new challenges on the feasibility of numerical procedures. Due to the increased sensitivity of the considered system with respect to the environmental conditions from wind and ocean, the application of common procedures used for fixed-bottom structures results in either inaccurate simulation results or hard-to-quantify conservatism in the system design. Monte Carlo-based sampling procedures provide a more realistic approach to deal with the large variation in the environmental conditions, although basic randomization has shown slow convergence. Specialized sampling methods allow efficient coverage of the complete design space, resulting in faster convergence and hence a reduced number of required simulations. In this study, a quasi-random sampling approach based on Sobol sequences is applied to select representative events for the determination of the lifetime damage. This is calculated applying Monte Carlo integration, using subsets of a resulting total of 16 200 coupled time-domain simulations performed with the simulation code FAST. The considered system is the Danmarks Tekniske Universitet (DTU) 10 MW reference turbine installed on the LIFES50+ OO-Star Wind Floater Semi 10 MW floating platform. Statistical properties of the considered environmental parameters (i.e., wind speed, wave height and wave period) are determined based on the measurement data from the Gulf of Maine, USA. Convergence analyses show that it is sufficient to perform around 200 simulations in order to reach less than 10 % uncertainty of lifetime fatigue damageequivalent loading. Complementary in-depth investigation is performed, focusing on the load sensitivity and the impact of outliers (i.e., values far away from the mean). Recommendations for the implementation of the proposed methodology in the design process are also provided.
The dynamic response of floating offshore wind turbines is complex and requires numerous design iterations in order to converge at a cost-efficient hull shape with reduced responses to wind and waves. In this article, a framework is presented, which allows the optimization of design parameters with respect to user-defined criteria such as load reduction and material costs. The optimization uses a simplified nonlinear model of the floating wind turbine and a self-tuning model-based controller. The results are shown for a concrete three-column semi-submersible and a 10 MW wind turbine, for which a reduction of the fluctuating wind and wave loads is possible through the optimization. However, this happens at increased material costs for the platform due to voluminous heave plates or increased column spacing.
A comparison of fatigue and extreme loads from simulations with full-scale measurements collected over a period of ten months in the offshore test field, Alpha Ventus, is presented in this paper. There are two goals of this study: (1) to check if the measured range of fatigue and extreme loads can be captured correctly by simulations when the variations of relevant environmental parameters are taken into account; and (2) to investigate if measured extreme loads can be reproduced by simulations when ten-minute averages of the environmental parameters are used. The results show a good overall match of loads when the variation of environmental parameters is considered but an insufficient match when the events of maximum load occurrence are compared.
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