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- W4321790901 abstract "The paper presents a parametric optimization of Tuned Liquid Column Damper (TLCD) to control the structural vibration of 5MW NREL offshore wind turbine (OWT) subject to the wind and waves random forces. In this work, the fluid–structure interaction of monopile with seawater are modeled as an added mass and the soil-structure interaction of monopile foundation is considered through simplified model of discrete coupled springs model. Using a proprietary genetic algorithm, the TLCD on nacelle has its parameters optimized to reduce the standard deviation or roots mean square (RMS) dynamic response on tower top. The displacement results are compared to the ones obtained by exhaustive search methods via a response map. From the stochastic analysis of the structure response, the ideal tuning ratio and damping ratio are determined for the liquid column damper to present its highest efficiency, i.e. the lowest RMS displacement at the tower top. The damper parameters achieved by both optimization methods show a significant agreement between them. In addition, the use of the genetic algorithm, a parametric optimization of the TLCD installed in OWT is carried out considering the random excitation of the wind, wave, and rotor forces (Kaimal, JONSWAP, and rotational spectra, respectively). In possession of the TLCD optimal parameters determined by the parametric study, the mitigation of displacements at the standard wind turbine top is analyzed. The fore-aft vibration at tower top with a TLCD attached shows a significant reduction for actions dynamic components. Finally, TLDC optimal parameters have a direct relation with the considered force spectrum and the turbine transfer function, and both must be considered for the damper optimization process." @default.
- W4321790901 created "2023-02-25" @default.
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- W4321790901 date "2023-04-08" @default.
- W4321790901 modified "2023-09-26" @default.
- W4321790901 title "Optimum TLCD for Mitigation of Offshore Wind Turbine Dynamic Response Considering Soil–Structure Interaction" @default.
- W4321790901 doi "https://doi.org/10.1142/s0219455423501870" @default.
- W4321790901 hasPublicationYear "2023" @default.
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