Dr. Sven Schmitz University of California, Davis Computational Modeling of Wind Turbine Aerodynamics and Helicopter Hover Flow Using Hybrid CFD Pennsylvania

Dr. Sven SchmitzDr. Sven Schmitz

University of California, DavisUniversity of California, Davis

Computational Modeling of Wind Turbine AerodynamicsComputational Modeling of Wind Turbine Aerodynamics and Helicopter Hover Flow Using Hybrid CFD and Helicopter Hover Flow Using Hybrid CFD

Pennsylvania State University

April 21st, 2010

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OutlineOutline

Wind EnergyWind Energy

The NREL Phase VI ExperimentThe NREL Phase VI Experiment

Hybrid CFD for Wind TurbinesHybrid CFD for Wind Turbines

Hybrid CFD for Helicopter Hover FlowHybrid CFD for Helicopter Hover Flow

Future Research DirectionsFuture Research Directions

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Wind EnergyWind Energy

“Alternative Sunrise”

Windkraftanlage Holzweiler mit Braunkohlekraftwerk Grevenbroich, Germany, April 2010.

Free energy source

Emission free

No water use

Scalability, i.e. ‘local’ & ‘wind power plant’

Less dependence on fossil fuels

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Wind Energy - U.S. Wind Energy - U.S. MarketMarket

Over 10,000 MW installed in 2009 - U.S. world Over 10,000 MW installed in 2009 - U.S. world leaderleader

Top U.S. Wind Turbine Supplier : Top U.S. Wind Turbine Supplier : GE EnergyGE Energy

Wind industry supports 85,000 jobs in 50 statesWind industry supports 85,000 jobs in 50 states

Now 9 wind turbine manufacturers in U.S.Now 9 wind turbine manufacturers in U.S.

www.awea.org/reports (April (April 2010)2010)

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Wind Energy - Wind Energy - IncentivesIncentives

US DOE – Energy Efficiency and Renewable US DOE – Energy Efficiency and Renewable EnergyEnergy 20% Wind Energy by 203020% Wind Energy by 2030

Pennsylvania - Alternative Energy Investment Pennsylvania - Alternative Energy Investment Act (2009)Act (2009) Wind Energy Supply Chain Initiative (WESCI)Wind Energy Supply Chain Initiative (WESCI)

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Wind Energy - Power Wind Energy - Power CurveCurve

P

23 C 4

2

1

DWP

and W site specific

CP ≈ 0.52 at Wrated (CP,Betz = 0.59)

Rotor Diameter D driving factor

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Wind Energy - Cost of Energy Wind Energy - Cost of Energy (COE)(COE)

O & M estimated at 10%-20% of total COE.

Availability & Loss are site & design specific.

Aerodynamics &

Aeroelasticity

[Walford, C., SAND2006-1100][Walford, C., SAND2006-1100]

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Wind Energy - Cost Wind Energy - Cost ReductionReduction

Maximize Availability, Minimize LossMaximize Availability, Minimize Loss Improved designs for Region IIImproved designs for Region II Reduce fatigue loadsReduce fatigue loads

Minimize Operation and Maintenance (O & Minimize Operation and Maintenance (O & M)M) Reduce # turbines to maintain by increasing Reduce # turbines to maintain by increasing

turbine powerturbine power Reduce fatigue loadsReduce fatigue loads

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Wind EnergyWind EnergyChallenges in Computational ModelingChallenges in Computational Modeling

Unsteady AerodynamicsUnsteady Aerodynamics Blade load response to wind gustBlade load response to wind gust

AeroelasticityAeroelasticity Blade tip deflections of several metersBlade tip deflections of several meters Twist changes > 10degTwist changes > 10deg

Airfoil SoilingAirfoil Soiling Performance loss caused by dirt, insects, etc.Performance loss caused by dirt, insects, etc.

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The NREL Phase VI The NREL Phase VI ExperimentExperiment

NREL = NREL = NNational ational RRenewable enewable EEnergy nergy LLaboratoryaboratory

NREL Phase VI Rotor, April 2000NREL Phase VI Rotor, April 2000

R = 5.03mR = 5.03m2 Blades, Twist, Taper2 Blades, Twist, TaperStall-controlled, S809 Stall-controlled, S809

Airfoil Airfoil [Somers, NREL/SR-[Somers, NREL/SR-440-6918]440-6918]

5m/s < V5m/s < VWindWind < 25m/s < 25m/s = 72rpm= 72rpmP ≈ 10KWP ≈ 10KW

NREL Phase VI Rotor in NASA Ames 120’ x 80’ wind

tunnel

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Blind Comparison Run, December 2000Blind Comparison Run, December 2000

Comparison of computational Comparison of computational modelsmodels

Performance Codes (BEMs)Performance Codes (BEMs)Aeroelastic CodesAeroelastic CodesWake CodesWake CodesCFD CodesCFD Codes

NREL Phase VI Rotor in NASA Ames 120’ x 80’ wind

tunnel

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No-Yaw, Steady-State, No-Stall conditions …No-Yaw, Steady-State, No-Stall conditions … Turbine Power Prediction : 25% - 175% of measuredTurbine Power Prediction : 25% - 175% of measured

Blade Bending Prediction : 85% - 150% of measuredBlade Bending Prediction : 85% - 150% of measured

CFD Codes -> Overall best predictions of turbine power and blade CFD Codes -> Overall best predictions of turbine power and blade loads.loads.Wake Codes -> Good performance for attached flow.Wake Codes -> Good performance for attached flow.

Main Results from Blind Comparison Run Main Results from Blind Comparison Run [NREL/TP-500-29494][NREL/TP-500-29494]

Conclusions from Blind Comparison Run Conclusions from Blind Comparison Run [NREL/TP-500-29494][NREL/TP-500-29494]

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Difficulties of computational modelsDifficulties of computational models

CFD CodesCFD Codes : High Computational Cost & Artificial : High Computational Cost & Artificial Dissipation Dissipation

Wake Codes Wake Codes : Prediction of strong 3D effects close to : Prediction of strong 3D effects close to the rotor bladethe rotor blade

Reduce cost and dissipation.

Near-Field RANS + Far-Field Wake Code

=

Hybrid CFD for Wind Turbines

Hybrid CFD for Wind Hybrid CFD for Wind TurbinesTurbines

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Parallelized Coupled Solver (PCS)Parallelized Coupled Solver (PCS)

Navier-Stokes

Vortex Method

)()( 1 jjj yy Vortex Filament

Biot-Savart Law (discrete)

j

Bound

Vortex

j

j

Vortex

Filament

j

r

rl

r

rlv

3

_

3

4

4

Boundary of Navier-Stokes Zone

Converged for …

51 10)()( njnj yy

j jL Aj dAdsvy ..)( Bound Vortex


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Average uB from power estimate using actuator disc theory

Biot-Savart Law

3

__

4

)(

r

rldrv

R

uUadv T

T

R

uUadv B

B

05.0 TB uu

0)(2 22 BB uuURP

Hybrid CFD for Wind Hybrid CFD for Wind TurbinesTurbinesVortex MethodVortex Method

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C

Accuracy of straight-line Vortex Segmentation :

=> [Gupta & Leishman, AIAA-2004-0828]

ΔΘ = 10˚ => Error < 10%

ΔΘ < 2.5˚ => Error < 1%

Parameters for accurate

calculation of induced velocities :

Minimum Number of Vortex Filaments : 39

Trefftz Plane Location : 20 blade radii behind the rotor disc

Vortex Segmentation ΔΘ : 0.02˚ at the blade, 12˚ after 1 revolution

Accuracy achieved in Induced Velocities at representative points : < 1%

Hybrid CFD for Wind Hybrid CFD for Wind TurbinesTurbinesVortex MethodVortex Method

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Optimum Wind TurbineOptimum Wind Turbine

Inviscid Flow :PCS = Parallelized Coupled Solver

VLM = Vortex Line Method [J.J. Chattot]

8.8048.8048.8798.879Power [kW]Power [kW]

-583.80-583.80-588.82-588.82Torque [Nm]Torque [Nm]

1814.81814.81803.11803.1Bending Moment [Nm]Bending Moment [Nm]

-179.89-179.89-183.63-183.63Tangential Force [N]Tangential Force [N]

508.31508.31509.62509.62Thrust [N]Thrust [N]

PCSPCSVLMVLM

Difference in Power : 0.84 %


[S. Schmitz, J. J. Chattot, Computers & Fluids (2006)]

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Optimum Wind TurbineOptimum Wind Turbine

Viscous Flow :

7.3217.3217.8357.835Power [kW]Power [kW]

-485.50-485.50-519.58-519.58Torque [Nm]Torque [Nm]

1636.41636.41670.21670.2Bending Moment [Nm]Bending Moment [Nm]

-150.80-150.80-163.26-163.26Tangential Force [N]Tangential Force [N]

458.60458.60472.41472.41Thrust [N]Thrust [N]

PCSPCSVLMVLM

Difference in Power : 6.6 %

PCS = Parallelized Coupled Solver

VLM = Vortex Line Method [J.J. Chattot]


[S. Schmitz, J. J. Chattot, Computers & Fluids (2006)]

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Rotating, S-Sequence

Fully Attached Flow : U=7m/s

NREL Phase VI RotorNREL Phase VI Rotor


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Very good agreement w/ measured surface pressure coefficient.

[S. Schmitz, J. J. Chattot, ASME JSEE (2005)]



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Influence of Vortex Sheet Revolutions on Rotor Torque : VWind = 7m/s

Collaboration with GE Wind

Wind Aero Design Tool Development

(2007-2009)

UCD Award #08003057, #700163655

Routine Design Use

Hybrid CFD for Wind Hybrid CFD for Wind TurbinesTurbinesNREL Phase VI RotorNREL Phase VI Rotor

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Other CFD Results

[Duque et al, AIAA-1999-0037]

[Sezer-Uzol, Long, AIAA-2006-0394]

[Potsdam, Mavriplis, AIAA-2009-1221]

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Application of PCS to the NREL Phase VI Rotor :

Steady (no yaw), Fully Turbulent, k-ε and k-ω turbulence models

VLM = Vortex Line Model

[J. J. Chattot , CFD Journal (2002)]

PCS = Parallelized Coupled Solver



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Distribution of Bound Circulation(Parked, L – Sequence, U = 20.1 m/s)

Trailing Vortex @ r/R=0.40

Attached FlowSeparated Flow

Stalled Flow

Good agreement between VLM and PCS for attached flow.

Apparent Differences for separated flow (3D effects)

A ‘Trailing Vortex’ is attached to a region of stalled flow.

[Schreck, AIAA-2005-0776]

[Tangler, AIAA-2005-0591]



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(a) 47 = 3.53deg (b) 47 = 13.46deg (c) 47 = 23.49deg (d) 47 = 33.50deg

Iso-Vorticity Surface behind Parked NREL PhaseVI Blade (=19s-1) (L – Sequence, U = 20.1 m/s)

Visualization of ‘Trailing Vortex’ by an Iso-Vorticity Surface



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complex physicsneed for high accuracya recurring engineering needmany methods developed, few validatedlittle data that supports complete physical models

Hybrid CFD for Helicopter Hybrid CFD for Helicopter Hover FlowHover Flow

Collaboration with US Army AFDD

A New CFD Approach for the Computation of General Rotorcraft Flows (2006-2010)

UCD Award #NNX08AU38A, #NNA0CB79A

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Coupling UMTURNS w/ HELIX-IA

i. HELIX-IA provides wake structure and

induced inflow.

ii. Interpolate HELIX-IA velocity to UMTURNS

boundary.

iii. Impose Blade Circulation from

UMTURNS to HELIX-IA Wake.

Typical HELIX-IA-hybrid grid topology

91x125x107

193x65x96


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HELIX-IA : An Iterative Eulerian- / Lagrangian Solution Process

Vorticity Embedding


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t = Vorticity Embedding

Roll Up – Vortex Sheet w/ Elliptical Loading (Qv Field)

[S. Schmitz et al, AIAA-2009-3856]

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t = 0.0

t = /4

t = 2

[S. Schmitz et al, AIAA-2009-3856]

Vorticity Embedding

Roll Up – Pair of Vortex Ring Sheets

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Validation : Model UH-60A Validation : Model UH-60A BladeBlade


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Axial/Radial Tip Vortex Trajectory Axial/Radial Tip Vortex Trajectory

ComparisonsComparisons

Model UH-60A Rotor – CModel UH-60A Rotor – CTT// = 0.085, = 0.085,

MMtiptip=0.63=0.63Radial Axial


[S. Schmitz et al, AHS Journal (2009)]

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r/R = 0.865 r/R = 0.92

r/R = 0.945 r/R = 0.965

Hybrid CFD for Helicopter Hybrid CFD for Helicopter Hover FlowHover FlowPressure Coefficient vs. x/c Pressure Coefficient vs. x/c


MMtiptip=0.63=0.63


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Hybrid CFD for Helicopter Hybrid CFD for Helicopter Hover FlowHover FlowPressure Coefficient vs. z/c Pressure Coefficient vs. z/c


MMtiptip=0.63=0.63


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Hybrid CFD for Helicopter Hybrid CFD for Helicopter Hover FlowHover FlowFigure-of-Merit vs. CFigure-of-Merit vs. CTT


MMtiptip=0.63=0.63


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Fast and robust

Accurate wake computation

Suggests that hover data are insufficient


Typical HELIX-IA-hybrid grid topology

Coupling UMTURNS w/ HELIX-IA

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Combining experiences & resources in Wind Energy and Rotorcraft

HYBRID U-RANS/POTENTIAL SOLVER

Outer Wake Solver

Vorticity-Embedding Potential Solver, HELIX-IA

For steady flow comparable to Biot-Savart

Possibility for efficient free wake computation

Inner U-RANS Solver OverFlow, CFX, UMTURNS, etc.


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=0deg

Solve N blades

Vortex Model

NBj

,

BC – u,v,w

Converged or # subiterations

=+

# Revolutions until solution is periodic.

U-RANS

0,,

xU

t

NB

j

Wind

NB

j

Converged

Understanding the Unsteady Aerodynamics is vital

for future competitiveness of Wind Energy.

HYBRID

U-RANS/POTENTIAL

SOLVER


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HYBRID

U-RANS/POTENTIAL

SOLVER

Aeroelasticity

(PSU VLRCOE)

Acoustics

(Brentner, McLaughlin, Morris)

Mesoscale Modeling

(Brasseur, Haupt)

Airfoil Soiling

(Brasseur, Maughmer)


Current Funding : GE Wind, US Army AFDD

Future Funding : DOE, NSF, NREL, State of Pennsylvania, GE Wind, US Army AFDD

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Wake Interactions at ‘Horns Rev’, Denmark

Hybrid CFD for Wind TurbinesHybrid CFD for Wind TurbinesFuture fast & accurate wind Future fast & accurate wind

turbine/plant designsturbine/plant designs

Documents

Dr. Sven Schmitz University of California, Davis Computational Modeling of Wind Turbine Aerodynamics and Helicopter Hover Flow Using Hybrid CFD Pennsylvania