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  4. Optimization-based calibration of hydrodynamic drag coefficients for a semisubmersible platform using experimental data of an irregular sea state
 
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2020
Conference Paper
Title

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

Abstract
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.
Author(s)
Böhm, M.
Robertson, A.
Hübler, C.
Rolfes, R.
Schaumann, P.
Mainwork
EERA DeepWind 2020, 17th Deep Sea Offshore Wind R&D Conference  
Conference
Deep Sea Offshore Wind R&D Conference (DeepWind) 2020  
Open Access
DOI
10.1088/1742-6596/1669/1/012023
Additional full text version
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Fraunhofer-Institut für Windenergiesysteme IWES  
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