Explore applicability of predicted cone penetration test profiles from geostatistical co-simulation on deterministic and probabilistic monopile foundation design for offshore wind turbines
Applicability of predicted cone penetration test profiles from geostatistical co-simulation on deterministic and probabilistic
Lennart Siemann ª, Sigrid Wilhelm, Pedram Masoudi, Ramiro Relanezª
Patrick Arnold , Benjamin Schwarzª, Frank Rackwitz, , Tobias M¨orz
Fraunhofer Institute for Wind Energy Systems IWES, Am Fallturm 1, D-28359, Bremen, Germany
GuD Geotechnik und Dynamik Consult GmbH, Darwinstr. 13, D-10589, Berlin, Germany
Geovariances a Datamine Company, 44 avenue de Valvins, F-77210, Avon, France
Chair of Soil Mechanics and Geotechnical Engineering, Technical University of Berlin, Gustav-Meyer-Allee 25, D-13355, Berlin, Germany
UBC Uni Bremen Campus GmbH, Universit¨ atsallee 11–13, D-28359, Bremen, German
Abstract
To reduce site investigation costs for site characterization as well as timelines in offshore windfarm development, methods to predict the soil profile and essential geotechnical parameters at unexplored locations gain increasing interest from the industry. Hereby, the more abundant geophysical data can be used as guiding information in addition to the scarcely spaced direct investigations to improve the prediction of ground conditions and reduce its uncertainty at unexplored locations. However, since it is a rather new tool in offshore wind site character
ization, little is known about the applicability of those predicted soil profiles and the associated geotechnical parameters for the design process of offshore wind infrastructures. This study aims to highlight the generation of predicted geotechnical profiles and parameters in the form of predicted cone penetration tests (pCPTs) and its use for the design of monopile foundations. Using real data from a German North Sea site the pCPTs are generated by applying geostatistical co-simulation, resulting in a best estimate with a location and depth specific uncertainty. These probabilistic results are utilized for the derivation of a design pile length. This pile length is either computed based on a deterministic estimate of the pCPT, taken as a quantile values, or with a reliability-based approach with respect to a target reliability level. It could be shown that a safe design length in comparison to the measured values is achieved by using a quantile value of 5% or less
within a deterministic design or the reliability-based design approach.
Keywords:
Predicted CPT; Reliability-based pile design; Offshore wind;Site characterization;Multivariate modelling;Probabilistic;Monopile