Dr. Sven Schmitz Dr. Sven Schmitz University of California, Davis University of California, Davis Computational Modeling of Wind Turbine Computational Modeling of Wind Turbine Aerodynamics Aerodynamics and Helicopter Hover Flow Using Hybrid CF and Helicopter Hover Flow Using Hybrid CF Pennsylvania State University April 21 st , 2010
40
Embed
Dr. Sven Schmitz University of California, Davis Computational Modeling of Wind Turbine Aerodynamics and Helicopter Hover Flow Using Hybrid CFD Pennsylvania.
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
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
2
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
3
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
4
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)
5
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)
6
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
7
Wind Energy - Cost of Energy Wind Energy - Cost of Energy (COE)(COE)
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
9
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.
10
The NREL Phase VI The NREL Phase VI ExperimentExperiment
The NREL Phase VI The NREL Phase VI ExperimentExperiment
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]
13
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
Visualization of ‘Trailing Vortex’ by an Iso-Vorticity Surface
Hybrid CFD for Wind Hybrid CFD for Wind TurbinesTurbinesNREL Phase VI RotorNREL Phase VI Rotor
[S. Schmitz, J. J. Chattot, ASME JSEE (2006)]
26
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
27
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
Hybrid CFD for Helicopter Hybrid CFD for Helicopter Hover FlowHover Flow
28
HELIX-IA : An Iterative Eulerian- / Lagrangian Solution Process
Vorticity Embedding
Hybrid CFD for Helicopter Hybrid CFD for Helicopter Hover FlowHover Flow
29
Hybrid CFD for Helicopter Hybrid CFD for Helicopter Hover FlowHover Flow
t = Vorticity Embedding
Roll Up – Vortex Sheet w/ Elliptical Loading (Qv Field)
[S. Schmitz et al, AIAA-2009-3856]
30
Hybrid CFD for Helicopter Hybrid CFD for Helicopter Hover FlowHover Flow
t = 0.0
t = /4
t = 2
[S. Schmitz et al, AIAA-2009-3856]
Vorticity Embedding
Roll Up – Pair of Vortex Ring Sheets
31
Validation : Model UH-60A Validation : Model UH-60A BladeBlade
Hybrid CFD for Helicopter Hybrid CFD for Helicopter Hover FlowHover Flow
32
Axial/Radial Tip Vortex Trajectory Axial/Radial Tip Vortex Trajectory