Optimization-based calibration of hydrodynamic drag coefficients for a semisubmersible platform using experimental data of an irregular sea state

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Böhm, M.; Robertson, A.; Hübler, C.; Rolfes, R.; Schaumann, P.: Optimization-based calibration of hydrodynamic drag coefficients for a semisubmersible platform using experimental data of an irregular sea state. In: Journal of Physics: Conference Series 1669 (2020), Nr. 1, 012023. DOI: https://doi.org/10.1088/1742-6596/1669/1/012023

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For the simulation of the coupled dynamic response of floating offshore wind turbines, it is crucial to calibrate the hydrodynamic damping with experimental data. The aim of this work is to find a set of hydrodynamic drag coefficients for the semisubmersible platform of the Offshore Code Comparison Collaboration, Continuation, with Correlation and unCertainity (OC6) project which provides suitable results for an irregular sea state. Due to the complex interaction of several degrees of freedom (DOF), it is common to calibrate drag coefficients with the time series of decay tests. However, applying these drag coefficients for the simulation of an irregular sea state results in misprediction of the motions. By using numerical optimization, it is possible to calibrate multiple drag coefficients simultaneously and effectively, while also considering several DOF. This work considers time series of structural displacements from wave tank tests of the OC6 project and from simulations of the same load cases in OpenFAST. Results are transferred into the frequency domain and the deviation between power spectral densities of surge, pitch and heave from experiment and numerical simulation is used as an objective function to obtain the best fitting drag coefficients. This novel numerical optimization approach enables finding one set of drag coefficients for different load cases, which is a major improvement compared to decay-test-tuned drag coefficients. © Published under licence by IOP Publishing Ltd.
License of this version: CC BY 3.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2020
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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1 image of flag of United States United States 10 26.32%
2 image of flag of Germany Germany 9 23.68%
3 image of flag of China China 7 18.42%
4 image of flag of Sweden Sweden 2 5.26%
5 image of flag of United Kingdom United Kingdom 2 5.26%
6 image of flag of Japan Japan 1 2.63%
7 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 1 2.63%
8 image of flag of Europe Europe 1 2.63%
9 image of flag of Czech Republic Czech Republic 1 2.63%
10 image of flag of Canada Canada 1 2.63%
    other countries 3 7.89%

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