Abstract. The large amount of computational effort required for a full fatigue
assessment of offshore wind turbine support structures under operational
conditions can make these analyses prohibitive, especially for applications
like design optimization, for which the analysis would have to be repeated for
each iteration of the process. To combat this issue, we present a simple
procedure for reducing the number of load cases required for an accurate
fatigue assessment. After training on one full fatigue analysis of a base
design, the method can be applied to establish a deterministic, reduced
sampling set to be used for a family of related designs. The method is based
on sorting the load cases by their severity, measured as the product of
fatigue damage and probability of occurrence, and then calculating the
relative error resulting from using only the most severe load cases to
estimate the total fatigue damage. By assuming this error to be approximately
constant, one can then estimate the fatigue damage of other designs using
just 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 of
less than 1 %–2 % can be expected for sample sizes in the range
15–60. One of the main points in favor of the method is its simplicity when
compared to more advanced sampling-based approaches. Though there are
possibilities for further improvements, the presented version of the method
can be used without further modifications and is especially useful for design
optimization and preliminary design. We end the paper by noting some
possibilities for future work that extend or improve upon the method.
Reliability-based design optimization of a spar-type floating offshore wind turbine support structure
