Jonathan Naughton - V&V of Models for Wind Turbine and Wind Plant Aerodynamics: the Relationship to Blade Design

Naughton8/31/2016 Sandia Blade Workshop 1

V&V of Models for Wind Turbine and Wind Plant Aerodynamics:

The Relationship to Blade Design

Jonathan NaughtonProfessor of Mechanical Engineering

Director, Wind Energy Research CenterUniversity of Wyoming


Overview

• Introduction• V&V Process• Application to Wind Turbine and Wind

Plant• Impact of V&V of WT and WP on Blade

Design• Summary and next steps


IntroductionWhat is V&V?

• Validationú The process of determining

the degree to which a model is an accurate representation of the real world, from the perspective of the intended uses of the model

• Note that validation is not an acceptance/rejection/ endorsement of a model

• Verificationú Code verification

• Software errors or algorithm deficiencies that corrupt simulation results.

ú Solution verification• Human procedural

errors or numerical solution errors that corrupt the simulation


IntroductionWhat is a Validation Focused Program

• Goalú Formalized highly collaborative approach to planning and executing joint

experimental/modeling programs for the purpose of characterizing model accuracy for an intended application

• Why?ú Provides a transparent, structured, documented approach for integrate

program planning across scalesú Applicable to models of all fidelity, including reduced order modelsú High quality data sets well suited for collaborative model validation effortsú Quantifies prediction uncertainty for use by designers

• Foundation of framework usedú Framework developed for nuclear energy, SNL NW, and other programs ú Framework consistent with various ASME and AIAA V&V Guides, Codes and

Standards


IntroductionV&V - Not a New Idea


IntroductionWhy is V&V needed

• Without a level of trust of our tools, there results are of limited value

• Recently, our ability to simulate wind turbine and wind farm simulations has outstripped our ability to know whether the results are meaningful

Computational simulations complements of Jay Sitaraman and Dimitri Mavriplis


IntroductionMotivation - A2E

• A2E Objectiveú Transform today’s wind plant

operating environment through advanced physics-based modeling, analysis, and simulation capabilities

ú Approach• Development of high fidelity

models• Collection of existing data and

generation of new data through an experimental measurement campaign

• Strategic linking of these efforts through a Validation Focused Program

High Fidelity Modeling Experimental MeasurementCampaign

V&V


V&V ProcessOverview

• V&V Frameworkú Phenomena Identification

and Ranking Tableú Validation Hierarchyú Prioritizationú Experiment Design,

Execution & Analysisú Verification of Codeú Validation Metric

Determinationú Assessmentú Determination of level of

credibility


V&V ProcessFramework

P

Application: Specify system scenario and response quantities (SRQ) to be predicted at plant scale

Validation Hierarchy: Identify and prioritize those phenomena for which the models should be tested, the scales and hierarchy required for the tests, and conceptually how the validation tests should occur

Phenomena Identification: Identify and prioritize the plant scale phenomena required for models to successfully predict the SRQ for system scenario

Prioritize experiments within hierarchy based on program needs and resources

Document

Integrated Program Planning

Code Verification: Software and algorithm quality assessment

Experiment Design, Execution & Analysis through tightly coupled experimental/modeling effort

Validation Metrics

Assessment

Credibility of processes used

Document

Solution Verification: Mesh convergence error

Integrated Experiment and

Model Planning and Execution

Document


V&V ProcessPIRT

PIRT: Phenomenon Importance Ranking Table

• Consensus based• Provides gap analysis of

ability to model phenomena─ Physics gaps─ Numerical gaps─ Data gaps─ Validation gaps

• Gap analysis used to prioritize planning, including experimental planning


V&V ProcessPIRT Development

• Assemble groups of expertsú Several meetings over the past 24 monthsú Wide range of expertise

• Have the experts identify the physics important to a specific systemú Wind turbineú Wind farm

• Have the experts prioritizeú How important are the physics to the problemú How well do the codes model those physics

• Take results of several executions and distill into a final PIRT• Use the final PIRT to develop a Validation Hierarchy


V&V ProcessValidation Hierarchy

Increasin

gCo

mplexity

Increasin

gAccuracy

ValidationHierarchy

IntegratedEffectsTests

SeparateEffectsTests

SubsystemTests

SystemTests

CharacterizationTests

Increasin

gScale


V&V ProcessPrioritization

• Prioritize Experimentsú Program needsú Program funding

• Considerationsú What data is available that can address part/all of a needú What tests are capable of being carried out now or in future

• Facility availability• Experiment development time• Instrumentation maturity• Experiment cost• Funding cycle• Insufficient model capability• Insufficient computational resources


Application to Wind Turbine/Wind Plant

• Planning steps have been carried outú Wind turbine scaleú Wind plant scale

• Important to consider these are not independent effortsú Wind turbine scale is a

subsystem of wind plant scale

WindTurbineHierarchy

WindPlantHierarchy

Increasin

gCo

nfigurationCo

mplexity

Increasin

gMeasuremen

tAccuracy

Increasin

gScale


Application to Wind Turbine/Wind PlantPIRT – Wind Turbine

Physics Code Val

Blade Aero / Wake GenerationBlade load distribution effects and rotor thrust H M L L

Integrates to Rotor Thrust-Torque; Rotor Load Model important for LES-ALM.

Some experiments done for validation. Important to measure for experiments where rotor loading is correlated to wake meas.

Blade-WakeTip and root vortex development, evolution and merging H M L L

Wake PIV Experiments performed, but error bars and QA/QC may be missing or unknown. Does not cover effect of inflow conditions.

Full-scale and sub-scale field sites, and wind tunnel testing. Blade-Wake

Vortex sheet and rollup (in addition to tip/root vortex) M M M L

Some experimental data available that indicates phenomenon are present and may be important to wake stability. Effect of separation uncertain.

Further discovery experiments -> validation experiments.

Blade-WakeBlade generated turbulence characteristics (energetic scales at trailing edge) H L L L Coherent vortices shed from blade, including how they interact

with the atmosphere and near-wake.Full-scale and sub-scale field sites. High bandwidth probes, flow imaging. Blade-Wake

Root flow acceleration effect ('hub jet') Unknown M L L Effects root dynamic pressure and loading.Sensitivity Study to assess importance, qualitative data available.

Blade-Chord

Boundary layer development (transition, separation)

H M L L

Affects airfoil tables -> AL methods. Affects fully resolved modeling requirements (grid, transition model). Depends on incoming turbulence intensity relevant to blade surface boundary layer, depends on surface quality (roughness, soiling, bugs, erosion).

Wind tunnel and field tests.

Chord

Surface roughness effects (roughness, soiling, bugs, erosion) H L L L

Directly influences boundary layer development and blade loads.

Wind tunnel and field tests. Full scale surface quantification.

Chord

Boundary layer details near leading and trailing edge H M L L

Relates to boundary layer development, and important for aeroacoustics. Full-scale and sub-scale field sites

Chord

Rotational augmentationH L L L

Inability of HFM models to capture stall consistently. Tests done on multiple rotor scales, need to assess gaps remaining from tests.

Chord

Dynamic stallH L L L

2D data based on non-specific wind turbine airfoils and/or are limited to lower Reynolds numbers than relevant to full-scale.

Tests done on multiple rotor scales, need to assess gaps remaining from tests.

Chord

Unsteady inflow effect (veer, shear, yaw, gusts, atmospheric stability, turbulence intensity, spectra, coherence)

H L L LLarger time scale than what affects blade surface BL, but faster than that allowed by steady-state on chord scale. Full-scale and sub-scale field sites,

and wind tunnel testing.Blade-Wake-ABL

Blade flow controlM L L L Can be used to enhance blade performance and alleviate loads.

Full-scale and sub-scale field sites, and wind tunnel testing.

Blade-Chord

IcingH L L L Importance depends on regional climate (Northeast vs Midwest).Full-scale and wind tunnel testing.

Blade-Chord

Wake Development (growth/recovery) Skew and meander of aggregate wake H L L L Gross movement and deflection of far-wake.

Full-scale and sub-scale field sites, and wind tunnel testing. Wake

Swirl instability L L L L Interaction of axial and tangential momentum Wind tunnel tests. WakeVortex merging L L L L Important for the far-wake and turbine-turbine interaction. Sub-scale field sites and wind tunnel

testing. WakeWake vorticity diffusion and dissipation H L L L Important to wake recovery and far-wake properties.

Sub-scale field sites and wind tunnel testing. Wake

Asymmetry effects (ground plane, yaw, tilt, cone-angle) M M L L Influence the wake stability, recovery, meander, and vertical and horizontal deflection.


Inflow effect (shear, veer, yaw, turb. intensity, turb. spectrum, coherence, gusts, atmos. stab.)

H L L LFull scale data often does not measure to top of turbine, limited to single vertical profile. Full-scale and sub-scale field sites,

and wind tunnel testing. Wake-ABLTower/rotor/nacelle wake interactions H M L L Primarily included for noise, also influence blade and wake. Full-scale and sub-scale field sites Turbine-WakeAeroelasticity H M L L Rated for very large blades. Full-scale and sub-scale field sites,

and wind tunnel testing. BladeAeroacoustics H M L L Noise sources, mainly trailing edge, root, and tip.

Full-scale and sub-scale field sites and wind tunnel. Blade-Chord

Planning Priority

Phenomenon Importance

at Application

Level

Model Adequacy InterfaceIssue/Comments Response Including Scale

Physics Code Val













Blade-Chord


H M L L



Chord




Chord



Chord



Chord




Chord






Blade-Chord


Blade-Chord













Planning Priority


at Application

Level


Physics Code Val













Blade-Chord


H M L L



Chord




Chord



Chord



Chord




Chord






Blade-Chord


Blade-Chord













Planning Priority


at Application

Level



Application to Wind Turbine/Wind PlantPIRT – Wind Plant

Physics Code Val

Inflow Turbulence/Wake Interaction

Wind direction (shear/veer/assymetry) H L M M Wake sensitivity to gusts, low-level jets, etc. that promote three-dimensional boundary layers Wind tunnel and field tests. ABL/Turbine

Turbulence characteristics (intensity, spectra, coherence, stability) H L M M Wake sensitivity to turbulence Wind tunnel and field tests using real

and psuedo ABL spectra ABL

Coherent turblence structure H L M L Wake sensitivity to organized structures Difficult to test, but could include both wind tunnel and field tests. ABL

Surface conditions (roughness, canopy, waves, surface heat flux, topography) H L M M Wake sensitivity to changes in ABL due to surface features Wind tunnel and field testing looking at

changes in ABL ABL

Momentum transport (horizontal and vertical fluxes) H L L L Wake sensitivity to momentum supplied by ABL. Side-flow is

a special case, as well as the deep array. Wind tunnel and field tests. ABL

Multi-Turbine Wake EffectsWake interaction, merging, meander

H L L L Physics behind unsteady wake behavior Wind tunnel and field tests.

Plant flow control for optimum performance H M M L Strategies for optimizing the wind farm rather than individual

turbinesSubscale and full scale field tests. Large controlled facility tests.

Wake steering (yaw & tilt effects)H L L L Effect of non-normal inflow on wake behavior. Useful for

control. Wind tunnel and field tests.

Wake dissipationH L L L Evolution toward a neglibly small wake Wind tunnel and field test

Wake Impingement (full, half, etc.)H L L L Effect of upstream wake position on downstream turbine Wind tunnel and field test

Deep array effects (change in turbulence, etc.) H L L L Emphasis on the behavior of the flow within the wind plant Wind tunnel and full scale field test

Other EffectsWind plant blockage effects and plant wake

M M M L Emphasis on the effect of the wind farm on cross-stream downstream regions Wind tunnel and full scale field test ABL

Acoustic PropagationH L L L Noise generation and propogation through a wind plant Full-scale and sub-scale field sites Turbine

Planning Priority

Response Including Scale InterfacePhenomenon

Importance at

Application Level

Model Adequacy Issue/Comments


Application to Wind Turbine/Wind PlantValidation Hierarchy – Wind Turbine

SingleIndustrialScaleTurbineInField

SingleTurbineValidationHierarchy

IntegratedEffects(Benchmark)

SeparateEffects(UnitProblems)

Subsystem

System

ScaledTurbineInField

SingleTurbineinLWT

PitchingBlade

FixedAirfoils

PitchingAirfoil

BoundaryLayer

AxisymmetricWake

RootVortexTipVortex

FixedAeroelasticBlade

AirfoilFlowControl

BladeFlowControl

SingleTurbineinWTwithTI

AirfoilwithIcingAirfoilwithTI SingleTurbineinSWTwithTI

FixedBlade

AxisymmetricWakewithSwirl


Application to Wind Turbine/Wind PlantValidation Hierarchy – Wind Plant

IndustrialScaleWindPlant

WindPlantValidationHierarchy

ScaledWindFarmInField

ScaledWindFarminWindTunnel

InfiniteWindFarmWindTunnel

Wake/TurbineInteractioninWindTunnel

MultipleWakeswithInflowTurbulence

WakeSteer/Veer

SingleWindTurbineHierarchy

IntegratedEffects(Benchmark)

SeparateEffects(UnitProblems)

Subsystem

System


Application to Wind Turbine/Wind PlantPrioritized Phenomena Experimental Mapping

Blad

eAe

ro/W

akeGeneration

BladeLoadDistributionEffects

Tip&Roo

tVortexEvolution

VortexSheetEvolutio

n

BladeGe

neratedTurbulence

RootFlowAcceleration

BoundaryLayerDevelopment

SurfaceRo

ughnessE

ffects

BoundaryLayerNearLEandTE

Rotatio

nalA

ugmen

tatio

n

DynamicStall

UnsteadyInflo

wEffects*

BladeFlow

Control

Icing

PhysicsPresent/PhysicsMeasured

EntirelyMostlySomewhatLimitedMissing

BoundaryLayer

PhysicsPresent

PhysicsCapturedbyMeasurements

AxisymmetricWake(withSwirl)

PhysicsPresent


Root/TipVortex

PhysicsPresent


FixedAirfoils(withflowcontrol)

PhysicsPresent


TestingIssues

BoundaryCon

ditio

ns

ScaleEffects

FixedBlade(withTurbulentInflow)

PhysicsPresent


Increasin

gCo

mplexity

Increasin

gAccuracy

ValidationHierarchy



SubsystemTests

SystemTests


Increasin

gScale



PitchingAirfoil

PhysicsPresent


AirfoilwithIcing

PhysicsPresent


FixedAeroelasticblade

PhysicsPresent


SingleWindTurbine(Small)inWindTunnel

PhysicsPresent


Blad

eAe

ro/W

akeGeneration


Tip&Roo

tVortexEvolution

VortexSheetEvolutio

n

BladeGe

neratedTurbulence



SurfaceRo

ughnessE

ffects


Rotatio

nalA

ugmen

tatio

n

DynamicStall

UnsteadyInflo

wEffects*

BladeFlow

Control

Icing



TestingIssues

BoundaryCon

ditio

ns

ScaleEffects

Increasin

gCo

mplexity

Increasin

gAccuracy

ValidationHierarchy



SubsystemTests

SystemTests


Increasin

gScale



Increasin

gCo

mplexity

Increasin

gAccuracy

ValidationHierarchy



SubsystemTests

SystemTests


Increasin

gScale

Blad

eAe

ro/W

akeGe

neratio

n


Tip&Roo

tVortexEvolution

VortexSheetEvolutio

n

BladeGe

neratedTurbulence



SurfaceRo

ughnessE

ffects


Rotatio

nalA

ugmen

tatio

n

DynamicStall

UnsteadyInflo

wEffects*

BladeFlow

Control

Icing



PitchingBlade(withFlowControl)

PhysicsPresent


TurbineinVLWT(~5mrotor)

PhysicsPresent


TurbineinWT(~1mrotor),TurbulentInflow

PhysicsPresent


ScaledTurbineinField(~30mrotor)

PhysicsPresent

PhysicsCapturedbyMeasurementsTestingIssues

BoundaryCon

ditio

ns

ScaleEffects

IndustrialScaleTurbineinField(~120mrotor)

PhysicsPresent




• Similar PPEMs exist for turbine wakes and wind plants

• Allow for rapid identification of impact of different experiments and their rolesú Some experiments capture limited physics

• Physics – usually captured by measurements

• Boundary conditions- typically well characterized

ú Some experiments capture most of the physics

• Physics – not always captured by measurements

• Boundary conditions - typically limited characterization

• Poorly understood scaling effects are also designed into experiments

Multi-TurbineWakeEffects

Interaction,M

erging,M

otion

Steerin

g(Yaw

/TiltEffe

cts)

WakeDissipation

WakeIm

pingem

ent(Full/Ha

lf/Near)

Inflo

wTurbu

lenceWakeInteraction

WindDirection

SurfaceCo

nditions

TurbulenceStatistics

Mom

entumTranspo

rt

Acou

sticPropagatio

n



TestingIssues

BoundaryCon

ditio

ns

ScaleEffects

Wake/TurbineInteractioninWT(~2mrotor)

PhysicsPresent


IndustrialScaleWindPlant(~120mrotor)

PhysicsPresent


InfiniteWindFarminWindTunnel(~0.2mrotor)

PhysicsPresent


ScaledWindFarminField(~30mrotor)

PhysicsPresent


MultiWakeswithInflowTurbulence(~0.2mrotor)

PhysicsPresent


ScaledWindFarminVLWT(~2mrotor)

PhysicsPresent


WakeSteer/Veer(~0.2mrotor)

PhysicsPresent



Impact of V&V of WT and WP on Blade Design

• Path for validating codes is now availableú Experimental validationú High fidelity/low fidelity code

comparison• Blades of the future can be

designed using rigorously validated design tools

• Industry, government labs, and academia can all play a role in the validation processú Share data

• Details!ú Perform validationú Provide feedback

• Blades design may be fundamentally changed as understanding of wind farm performance increasesú What attributes of a blade

produce the most favorable wake?

• Site specific• Condition specific


Impact of V&V of WT and WP on Blade Design

• Blades will have to be designed for scaled experimentsú Goal is to capture the physics

relevant to the industrial wake with sub-scale blades

• Two design approachesú Sandia – circulation based

approachú UW – normalized blade force

approach• Two applications

ú SWIFTú 1-m blade in controlled inflow


Summary and Next Steps

• Integrated Program Planning nearly completeú Application identifiedú PIRT completed

• SMEs involved• Consensus identified

ú Validation Hierarchy developedú Validation experiments mapped

onto prioritized phenomena (PPEM)

ú Report to appear soon• In review• Expected release in near future

ú Contact David Maniaci

• Integrated Experiment and Model Planning and Executionú Underway for some prioritized

validation experiments• Experiments proposed for all

levels of validation hierarchyú Planning for other experiments to

take place as opportunity allowsú Other groups may use this

document as well and identify other gaps in scenarios available for validation


Acknowledgements• Jonathan Naughton’s contribution to this work is supported by

Sandia National Laboratory• Details of applying the V&V process to wind energy guided and

refined in collaboration with Rich Hills and David Maniaci of Sandia National Labs

• Input from many experts in the wind energy area are too many to mention, but are acknowledged here

• Particular thanks to contributions from ú Steve Hammond, NREL ú Daniel Laird, NRELú Brian Resor, Sandiaú Mike Robinson, NREL/DOEú Scott Schreck, NRELú Fotis Sotiropoulos, UMú Paul Veers, NRELú Steve Wombold,Sandia

Technology

Jonathan Naughton - V&V of Models for Wind Turbine and Wind Plant Aerodynamics: the Relationship to Blade Design