Cyclic overlay model of p–y curves for laterally loaded monopiles in cohesionless soil

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Song, J.; Achmus, M.: Cyclic overlay model of p–y curves for laterally loaded monopiles in cohesionless soil. In: Wind energy science : WES 8 (2023), Nr. 3, S. 327-339. DOI: https://doi.org/10.5194/wes-8-327-2023

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Abstract: 
The bearing behaviour of large-diameter monopile foundations for offshore wind turbines under lateral cyclic loads in cohesionless soil is an issue of ongoing research. In practice, mostly the p–y approach is applied in the design of monopiles. Recently, modifications of the original p–y approach for monotonic loading stated in the API regulations have been proposed to account for the special bearing behaviour of large-diameter piles with small length-to-diameter ratios. However, cyclic loading for horizontally loaded piles predominates the serviceability of the offshore wind converters, and the actual number of load cycles cannot be considered by the cyclic p–y approach of the API regulations. This research therefore focuses on the effects of cyclic loading on the p–y curves along the pile shaft and aims to develop a cyclic overlay model to determine the cyclic p–y curves valid for a lateral load with a given number of load cycles. A stiffness degradation method (SDM) is applied in a three-dimensional finite element model to determine the effect of the cyclic loading by degrading the secant soil stiffness according to the magnitude of cyclic loading and number of load cycles based on the results of cyclic triaxial tests. Thereby, the numerical simulation results are used to develop a cyclic overlay model, i.e. an analytical approach to adapt the monotonic (or static) p–y curve to the number of load cycles. The new model is applied to a reference system and compared to the API approach for cyclic loads.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2023
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 25 50.00%
2 image of flag of United States United States 8 16.00%
3 image of flag of United Kingdom United Kingdom 3 6.00%
4 image of flag of Denmark Denmark 3 6.00%
5 image of flag of Belgium Belgium 3 6.00%
6 image of flag of Vietnam Vietnam 1 2.00%
7 image of flag of Tanzania, United Republic of Tanzania, United Republic of 1 2.00%
8 image of flag of Netherlands Netherlands 1 2.00%
9 image of flag of China China 1 2.00%
10 image of flag of Australia Australia 1 2.00%
    other countries 3 6.00%

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