The extended Davenport peak factor as an extreme-value estimation method for linear combinations of correlated non-Gaussian random variables

The method was applied to the analysis of the extreme wind actions on a parabolic trough. The model parameters were expressed in terms of 3 magnitudes which characterize the spatial (correlation), temporal (frequency of peaks) and intrinsic (variance) variability of the actions. The results are consistent with methods that consider the variability of the components and the variability that is introduced by their combination. Nonetheless, the methods that do not incorporate this information result in peak factors that are an average of 13% lower. Also, the methods for Gaussian variables do not capture the variability between the case studies.