In this paper, we compare the load displacement behavior of an offshore monopile foundation obtained with different beam-spring approaches (p-y-curves) with numerical results obtained with the Finite Element method. Good agreement between the Finite Element calculation and the beam-spring model can be achieved if the p-y-curves according to the API guidelines are modified at small displacements. Furthermore, the eigenfrequency of an offshore wind turbine predicted with the initial stiffness of API p-y-curves and the modified p-y-curves are compared with in-situ measurements. Employing the higher initial stiffness of the modified p-y-curves significantly improves the match with the measured eigenfrequency.


Realistic prediction of the load displacement behaviour of laterally loaded piles obviously depends on capturing the pile-soil interaction for lateral stresses correctly. In offshore geotechnics, beam-spring models with non-linear, distributed bedding springs are commonly used for this task, both for calculating deformations and bearing capacity. The bedding springs for coarse grained soils are usually related to standard soil parameters (bulk weight, effective friction angle) according to the recommendations of the American Petroleum Institute (API).

The p-y-curves published in the API-guidelines (API 2000) are based on model tests with pile diameters of 0.3 m - 0.64 m (Reese et al. 1974, Matlock 1970, O'Neill & Murchison 1983). Pile diameters up to 8 m, however, are common in offshore monopile foundations, and the transfer of the API-recommendations to these large diameter piles is not yet fully clarified. Achmus et al. (2005) found a softer behaviour of large diameter monopiles in Finite Element calculations than obtained with the API-p-y-curves. Based on the work of Achmus et al., Kirsch et al. (2014) proposed a reduction of the effective friction angle depending on the pile diameter. However, other studies (Stevens & Audibert 1979) found the opposing effect of stiffer bedding for large diameter piles than predicted with API p-y-curves.

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