CFD Simulation of the NREL Phase VI Rotor

Song, Yang Ho; Perot, Blair

doi:10.1260/0309-524x.39.3.299

Cited by 30 publications

(26 citation statements)

References 17 publications

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“…For this turbine the flow starts to separate at the inflow speed of 7m/s and goes to massively stalled conditions from the inflow speed of 10 m/s. [4][5][6][7][8] The reported results indicated that for attached flows URANS is able to reproduce the mechanical power and thrust, but for higher wind speeds with flow separation, it over-predicts both quantities. Correspondingly, they showed deviations from the experiment for the force coefficients for different sections along the rotor span.…”

Section: Introductionmentioning

confidence: 95%

“…2,3 Although previous inventigations have demonstrated that RANS based models are accurate enough in the pre-stall regime, they are known to be not accurate for predicting the aerodynamic loads for wind turbines in separated flow. [4][5][6][7][8] Flow separation typically occurs when the blade sections are subjeted to high angles of attack, what might take place under a varieties of operating conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Correspondingly, they showed deviations from the experiment for the force coefficients for different sections along the rotor span. [4][5][6][7] This could be due to two main reasons:…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

DDES and URANS comparison of the NREL phase-VI wind turbine at deep stall

Rahimi

Dose

Herráez

et al. 2016

34th AIAA Applied Aerodynamics Conference

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This paper presents a comparison between two well known techniques in Computational Fluid Dynamics (CFD) for simulating the turbulent and separated flow around a rotating wind turbine blade, namely: Delayed Detached-Eddy Simulation (DDES) and Unsteady Reynolds-Averaged NavierStokes (URANS). The simulations are performed using the open source CFD toolbox OpenFOAM. For the purpose of validation, aerodynamic key parameters such as normal and tangential force coefficients and pressure distributions at different spanwise sections along the blade are compared with measurements. The influence of the computational grid and time step on the results is also investigated. Results indicate that a slight improvement in the predication of the transient behavior of the rotor blade for the pressure distribution and prediction of vortex shedding is achieved using the DDES approach.Nomenclature U = Velocity m/s r = the ratio of the model length-scale to the wall distance

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Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

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DDES and URANS comparison of the NREL phase-VI wind turbine at deep stall

Rahimi

Dose

Herráez

et al. 2016

34th AIAA Applied Aerodynamics Conference

View full text Add to dashboard Cite

show abstract

“…Therefore, the time-dependent aerodynamic loads on the surface of wind rotor were computed by solving the unsteady To obtain better convergence and precise aerodynamic results, full-hexahedral mesh grids of reasonable quality subdivided the entire computational domain by applying the block topology, which can be seen in Figure 2. By adopting the O-grid generation technique [28], mesh refinement was generated near the blade surface to describe with sufficient precision the boundary layer flow, and the size of the first element in the wall-normal direction was fine enough to ensure y + < 5. This y + value made it suitable for the use of the enhanced wall function [29].…”

Section: Numerical Simulation Methods Based On Cfdmentioning

confidence: 99%

Numerical Study of the Aerodynamic Loads on Offshore Wind Turbines under Typhoon with Full Wind Direction

2016

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Abstract:Super typhoon activity is likely to make the electric power network fail, or blow the wind-measuring device off, which all lead to the yaw control system of wind turbine being inactive. Under this condition, blades can be blown by the violent side wind from unfavorable directions, and the aerodynamic loads on the wind turbine will be increased by a large amount, which can lead to low-cycle fatigue damage and other catastrophic collapses. So far, not enough consideration has been given to the above problems in wind turbine design. Using the transient computational fluid dynamics (CFD), this study investigates the wind load characteristics of offshore wind turbines under typhoon condition with 360-degree full wind directions. Two primary influence factors of the aerodynamic characteristics of wind turbines are clarified: variation of the wind direction and different parking positions of the wind rotor. Using 3D-numerical simulation results, this study provides detailed references for the ultimate strength and fatigue life in wind turbine design, and presents the best parking position of the wind turbine with a free yawing strategy.

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“…The effects being studied in this work are largely due to external geometry, so an actuator disk model was deemed sufficient. Detailed RANS simulations of the rotating blades and their trailing vortices have been performed elsewhere but are not required here . The governing equations are

\frac{\partial {\overset{true¯}{u}}_{i}}{\partial t} + {\overset{true¯}{u}}_{j} \frac{\partial {\overset{true¯}{u}}_{i}}{\partial x_{j}} = - \frac{1}{ρ} \frac{\partial \overset{p}{true}}{\partial x_{i}} + \frac{\partial}{\partial x_{j}} ν \frac{\partial {\overset{true¯}{u}}_{i}}{\partial x_{j}} + \frac{\partial ((), \overset{true¯}{{\overset{'}{u}}_{i} {\overset{'}{u}}_{j}})}{\partial x_{j}} + \frac{1}{ρ} f_{i} \frac{\partial {\overset{true¯}{u}}_{i}}{\partial x_{i}} = 0,

where x i represents the position,

{\overset{true¯}{u}}_{i}

the mean flow velocity in i ‐direction,

\overset{p}{true}

the averaged pressure, and f i the body force per unit volume acting on the fluid (in particular, this is the axial force in the regions of the actuator disks that mimics drag from the wind turbine).…”

Section: Numerical Setup and Formulationmentioning

confidence: 99%

Improving the efficiency of wind farms via wake manipulation

2018

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Wind turbine farms suffer from wake losses, where the downstream turbines generate less power, and/or the leading turbines are throttled to reduce the downstream power losses. In this paper, we focus on possible external modifications that can enhance the wind turbines' performance when they are operating in a farm environment. In particular, this study is interested in enhancing the performance of the downstream turbines in wind farms. The idea is to move each turbine's wake down and away from subsequent turbines. This goal is achieved by using stationary external airfoils that are placed in proximity to the rotating blades. A number of different designs are tested and the design concepts are tested using Reynolds‐Averaged Navier‐Stokes simulations of an aligned array of 2 wind turbines. The turbines are modeled as actuator disks with axial induction and are placed in a velocity field that is modeled as a turbulent atmospheric boundary layer. It is found that fixed external airfoils can enable partial or full power recovery at turbine separations of as small as 3 rotor diameters downstream. We will also demonstrate that some devices can also improve the performance of the upstream turbine. The physical reasons for these power recovery phenomena are discussed.

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CFD Simulation of the NREL Phase VI Rotor

Cited by 30 publications

References 17 publications

DDES and URANS comparison of the NREL phase-VI wind turbine at deep stall

DDES and URANS comparison of the NREL phase-VI wind turbine at deep stall

Numerical Study of the Aerodynamic Loads on Offshore Wind Turbines under Typhoon with Full Wind Direction

Improving the efficiency of wind farms via wake manipulation

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