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Research Papers: Ocean Renewable Energy

Irregular Nonlinear Wave Simulation and Associated Loads on Offshore Wind Turbines

[+] Author and Article Information
E. Marino

CRIACIV,
Department of Civil and
Environmental Engineering,
University of Florence,
Firenze 50139, Italy
CNR-INSEAN,
Maritime Research Institute,
Roma 00128, Italy
e-mail: enzo.marino@dicea.unifi.it

H. Nguyen

Department of Civil, Architectural,
and Environmental Engineering,
University of Texas,
Austin, TX 78712
e-mail: nhh@utexas.edu

C. Lugni

CNR-INSEAN,
Maritime Research Institute,
Roma 00128, Italy
AMOS,
Trondheim NO-7491, Norway
e-mail: claudio.lugni@cnr.it

L. Manuel

Department of Civil, Architectural, and
Environmental Engineering,
University of Texas,
Austin, TX 78712
e-mail: lmanuel@mail.utexas.edu

C. Borri

CRIACIV,
Department of Civil and
Environmental Engineering,
University of Florence,
Firenze 50139, Italy
e-mail: dir-dicea@dicea.unifi.it

1Corresponding author.

Contributed by the Ocean, Offshore, and Arctic Engineering Division of ASME for publication in the JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING. Manuscript received October 8, 2013; final manuscript received November 15, 2014; published online December 18, 2014. Assoc. Editor: António Falcão.

J. Offshore Mech. Arct. Eng 137(2), 021901 (Apr 01, 2015) (9 pages) Paper No: OMAE-13-1096; doi: 10.1115/1.4029212 History: Received October 08, 2013; Revised November 15, 2014; Online December 18, 2014

The accuracy of predicted loads on offshore wind turbines depends on the mathematical models employed to describe the combined action of the wind and waves. Using a global simulation framework that employs a domain-decomposition strategy for computational efficiency, this study investigates the effects of nonlinear waves on computed loads on the support structure (monopile) and the rotor–nacelle assembly of a bottom-supported offshore wind turbine. The fully nonlinear (FNL) numerical wave solver is invoked only on subdomains where nonlinearities are detected; thus, only locally in space and time, a linear solution (and associated Morison hydrodynamics) is replaced by the FNL one. An efficient carefully tuned linear–nonlinear transition scheme makes it possible to run long simulations such that effects from weakly nonlinear up to FNL events, such as imminent breaking waves, can be accounted for. The unsteady nonlinear free-surface problem governing the propagation of gravity waves is formulated using potential theory and a higher-order boundary element method (HOBEM) is used to discretize Laplace’s equation. The FNL solver is employed and associated hydrodynamic loads are simulated in conjunction with aerodynamic loads on the rotor of a 5-MW wind turbine using the NREL open-source software, fast. We assess load statistics associated with a single severe sea state. Such load statistics are needed in evaluating relevant load cases specified in offshore wind turbine design guidelines; in this context, the influence of nonlinear wave modeling and its selection over alternative linear or linearized wave modeling is compared. Ultimately, a study such as this one will seek to evaluate long-term loads using the FNL solver in computations directed toward reliability-based design of offshore wind turbines where a range of sea states will need to be evaluated.

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References

Figures

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Fig. 1

Sketch of the zero-crossing analysis of the free surface elevation for the estimation of the time instant at which the nonlinear event occurs (example with ib = 4)

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Fig. 2

Schematic representation of the domain decomposition method for the ib-th subdomain. The figures on the right-hand side depict the spatial subdomain Ωib.

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Fig. 3

The 5-MW offshore wind turbine model (courtesy: Jason Jonkman)

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Fig. 4

Pitch control, rotor speed, and power curve

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Fig. 5

One-hour time series of the hub-height longitudinal wind velocity (m/s), wave elevation (m), tower base fore-aft shear force (MN), tower base fore-aft bending moment (MN · m), and tower-top fore-aft deflection (m)

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Fig. 6

Time series of the hub-height longitudinal wind velocity (m/s), wave elevation (m), tower base fore-aft shear force (MN), tower base fore-aft bending moment (MN·m), and tower-top fore-aft deflection (m) around events 1 and 4. (a) Event 1 and (b) event 4.

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Fig. 7

Estimates of PSD functions for the WaveElev, TwrBsFxt, TwrBsMyt, and TTDspFA processes

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Fig. 8

Time histories of PSDs components at 0.092 Hz of (from top to bottom) WaveElev, TwrBsFxt, TwrBsMyt, and TTDspFA processes

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Fig. 9

Time histories of PSDs components at 0.28 Hz of (from top to bottom) WaveElev, TwrBsFxt, TwrBsMyt, and TTDspFA processes

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