Unsteady Aerodynamics Experiment Phases II-IV Test Configurations and Available Data Campaigns

Simms, D.; Hand, M.; Fingersh, Lee; Jäger, D.

doi:10.2172/12144

Cited by 62 publications

(36 citation statements)

References 7 publications

(7 reference statements)

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“…It operates in free yaw down wind of the tower with a cut-in wind speed of 6m/s and a nominal rotor speed of 72 RPM. The nominal rated power is 20kW [19]. The turbine is shown in Figure 1.3, and a close-up of the turbine hub is shown in Figure 1.4.…”

Section: Doe/nrel/nwtc Unsteady Aerodynamics Experiments Phase III Turmentioning

confidence: 99%

Estimation of fatigue and extreme load distributions from limited data with application to wind energy systems.

Fitzwater

2004

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An estimate of the distribution of fatigue ranges or extreme loads for wind turbines may be obtained by separating the problem into two uncoupled parts, (1) a turbine specific portion, independent of the site and (2) a site-specific description of environmental variables. We consider contextually appropriate probability models to describe the turbine specific response for extreme loads or fatigue. The site-specific portion is described by a joint probability distribution of a vector of environmental variables, which characterize the wind process at the hub-height of the wind turbine. Several approaches are considered for combining the two portions to obtain an estimate of the extreme load, e.g., 50-year loads or fatigue damage. We assess the efficacy of these models to obtain accurate estimates, including various levels of epistemic uncertainty, of the turbine response.

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Section: Doe/nrel/nwtc Unsteady Aerodynamics Experiments Phase III Turmentioning

confidence: 99%

Estimation of fatigue and extreme load distributions from limited data with application to wind energy systems.

Fitzwater

2004

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“…Blade-mounted five-hole pitot tubes have been used in several research projects (Madsen, 1991;Brand et al, 1996;Petersen and Madsen, 1997;Simms et al, 1999;Hand et al, 2001;Schepers et al, 2002;Madsen et al, 2003Madsen et al, , 2010bMedina et al, 2011), but other types of sensors could be used as well. In the current context, a blade-mounted flow sensor (BMFS) is assumed to measure the 3-D inflow velocity at its position, i.e.…”

Section: Introductionmentioning

confidence: 99%

Free-flow wind speed from a blade-mounted flow sensor

et al. 2018

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Abstract. This paper presents a method for obtaining the free-inflow velocities from a 3-D flow sensor mounted on the blade of a wind turbine.From its position on the rotating blade, e.g. one-third from the tip, a blade-mounted flow sensor (BMFS) is able to provide valuable information about the turbulent sheared inflow in different regions of the rotor. At the rotor, however, the inflow is affected by the wind turbine, and in most cases the wind of interest is the inflow that the wind turbine is exposed to, i.e. the free-inflow velocities.The current method applies a combination of aerodynamic models and procedures to estimate the induced velocities, i.e. the disturbance of the flow field caused by the wind turbine. These velocities are subtracted from the flow velocities measured by the BMFS to obtain the free-inflow velocities. Aeroelastic codes, like HAWC2, typically use a similar approach to calculate the induction, but they use it for the reversed process, i.e. they add the induction to the free inflow to get the flow velocities at the blades, which are required to calculate the resulting aerodynamic forces.The aerodynamic models included in the current method comprise models based on blade element momentum (BEM) for axial and tangential induction, a radial induction model and tip loss correction, and models for skew and dynamic inflow.It is shown that the method is able to calculate the free-inflow velocities with high accuracy when applied to aeroelastic HAWC2 simulations with a stiff structural model while some deviations are seen in simulations with a flexible structure.Furthermore, the method is tested on simulations performed by a flexible structural model coupled with a large-eddy simulation (LES) flow solver. The results of this higher-fidelity verification confirm the HAWC2-based conclusion.

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“…The fourth phase, initiated in late 1995, also used the twisted blades; the flow angle measurements, however, were improved. The instrumentation differences between the Phase II, Phase III, and Phase IV configurations were described by Simms et al (1999). This report contains information regarding Phase V, which was conducted during 1998.…”

Section: Introductionmentioning

confidence: 99%

“…For information regarding Phases II-IV, the reader is referred to Butterfield, Musial, and Simms (1992) and Simms et al (1999). The tables in the body of this report that describe the channels collected by the data system are based upon the header files that accompany each data campaign.…”

Section: Introductionmentioning

confidence: 99%

Unsteady Aerodynamics Experiment Phase V: Test Configuration and Available Data Campaigns

Hand¹,

Simms²,

Fingersh³

et al. 2001

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Unsteady Aerodynamics Experiment Phases II-IV Test Configurations and Available Data Campaigns

Cited by 62 publications

References 7 publications

Estimation of fatigue and extreme load distributions from limited data with application to wind energy systems.

Estimation of fatigue and extreme load distributions from limited data with application to wind energy systems.

Free-flow wind speed from a blade-mounted flow sensor

Unsteady Aerodynamics Experiment Phase V: Test Configuration and Available Data Campaigns

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