An important yet difficult task in the design of wind turbines is to assess the extreme load behaviour, most notably finding the 50-year load. Where existing methods often focus on ways to extrapolate from small sample sizes, this paper proposes a different approach. It combines
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An important yet difficult task in the design of wind turbines is to assess the extreme load behaviour, most notably finding the 50-year load. Where existing methods often focus on ways to extrapolate from small sample sizes, this paper proposes a different approach. It combines generating constrained gusts in turbulence fields, Delaunay tessellation to assign probabilities and a genetic algorithm to find the desired load in an efficient way. The individual parts of the method are verified and the results are compared to both crude Monte Carlo and importance sampling. We found that using a genetic algorithm is a promising approach to find the 50-year load, with only a small number of load cases (~103) to be evaluated and requiring no user input but an appropriate fitness function.@en
