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. The large amount of computational effort required for a full fatigueassessment of offshore wind turbine support structures under operationalconditions can make these analyses prohibitive, especially for applicationslike design optimization, for which the analysis would have to be repeated foreach iteration of the process. To combat this issue, we present a simpleprocedure for reducing the number of load cases required for an accuratefatigue assessment. After training on one full fatigue analysis of a basedesign, the method can be applied to establish a deterministic, reducedsampling set to be used for a family of related designs. The method is basedon sorting the load cases by their severity, measured as the product offatigue damage and probability of occurrence, and then calculating therelative error resulting from using only the most severe load cases toestimate the total fatigue damage. By assuming this error to be approximatelyconstant, one can then estimate the fatigue damage of other designs usingjust these load cases. The method yields a maximum error of about 6 %when using around 30 load cases (out of 3647) and, for most cases, errors ofless than 1 %–2 % can be expected for sample sizes in the range15–60. One of the main points in favor of the method is its simplicity whencompared to more advanced sampling-based approaches. Though there arepossibilities for further improvements, the presented version of the methodcan be used without further modifications and is especially useful for designoptimization and preliminary design. We end the paper by noting somepossibilities for future work that extend or improve upon the method.

wind energy science

Reducing the number of load cases for fatigue damage assessment of offshore wind turbine support structures using a simple severity-based sampling method