High quality PIV data for numerical...

High quality PIV data for numerical validation

Eric Roosenboom1, Arne Stürmer2

25 Years of Particle Image Velocimetry in Aerodynamics

Göttingen, September 24, 2009

DLR -

German Aerospace CenterInstitute of Aerodynamics and Flow Technology1: Department Experimental Methods2: Department Transport Aircraft

Eric Roosenboom > September 24, 2009PIV-CFD > Sheet 2

High quality PIV data for numerical validation

IntroductionComparisonValidationVerification

Examples PIV-CFD validation

Conclusions & Outlook


Overview of validation measurements in DLR

CRUF: stereo-PIV behind counter-rotating ultra high bypass-fanAerostabil: transonic shock boundary layer interactions and buffetingHEG: Comparison Mach 7 flow at atmospheric pressureTrailing edge noise: Time-resolved PIV as input for CAA codeRTO generic delta wing: PSP as input for CFD stereo PIV Time-resolved stereo PIV for 1:1 scale car sunroof buffeting

Various industrial validation projects for propeller flow

Focus of today’s topic on PIV and CFD analysis of propeller flow on behalf of Airbus

Reference: Roosenboom (et al), AIAA 2009-3626


Role of EFD in CFD development [EFD: Experimental Fluid Dynamics]

Ref.: Marvin (1988) NASA-TM-100087Ref.: Oberkampf (2002) PROG AEROSP SCI (38)


1.

Jointly designed by experimentalists, model developers, code developers and code users

2.

Capture all essential physics of interest, including all physical modeling data and initial and boundary conditions required by code

3.

Strive to emphasize inherent synergism between computational and experimental approaches

4.

Maintain independence in obtaining computational and experimental results (but develop experimental design cooperatively)

5.

Create hierarchy of measurements of increasing computation difficulty, i.e. from globally integrated quantities to local measurements

6.

Analyze and estimate components of random (precision) and bias (systematic) experimental (and computational) errors

Guidelines for validation experiments Ref.: Oberkampf

(2002) PROG AEROSP SCI (38)


1.


2.


3.


4.


5.


6.




•

Accurate measurement of actual model dimensions•

Surface roughness conditions (including any imperfections)•

Location of BL transition for all conditions•

Free-stream measurement of turbulence quantities•

Accurate location and dimensions of model and all instrumentation

•

For subsonic free-stream:-

Location where conditions were measured-

Wall pressure measurements: inside test section & near end of computational domain


1.


2.


3.


4.


5.


6.




•

Flight vehicle forces and moments•

Control-surface forces and moments•

Surface-pressure distributions•

Surface heat-flux and/or shear stress•

Flow-field distributions of pressure, temperature and velocity•

Flow-field distribution of Reynolds stresses


Requirements for CFD validation

Any CFD code needs validation: Highly accurate, well documented experiments (model geometry, tunnel conditions, flow conditions), also/even for unsteady flow

PIV is valuable for investigation of local flow field phenomena (and comparison with CFD)

Lots of details: deformation, tunnel wall boundary flow information, tunnel disturbances

Cross-check with CFD for necessary input data

Standardized storage of experimental data:

feed into analysis process and software tool

RPM

Bending/torsion (IPCT)+

-Pressure (PSP)

0

-

cp

Comparison/validation

--> CFD & PIV

Velocity & vorticity (PIV)

PSIPSP


Flow simulation:

Numerical Experimental

Real

PIV


Particle Image Velocimetry Velocity gradient tensor

Progress towards 4D-3C measurements:

)()()()(

tvtutvtu

V yy

xx

Mono-PIV 2D(t)-2C

)()()(

)()()(twtvtutwtvtu

V yyy

xxx

Stereoscopic PIV 2D(t)-3C

)()()()()()()()()(

twtvtutwtvtutwtvtu

V

zzz

yyy

xxx

High-speed (tomographic) PIV 3D(t)-3C


Objective Comparison of EFD and CFD for propeller flow

Assessment of vortex systemsAccuracy of unsteady CFD calculationsIndication of experimental limitationsSimilarities and differences incomparative results (comparison)Outlook for further validation needs


Motivation

Complex aerodynamic interactions require careful engine-airframe integration designUnsteady CFD is valuable tool:

Compute unsteady

interactions of propeller and airframe with minor simplifications or assumptions Propeller blade loads only available with CFDInput/validation data for simpler computational methods(actuator disk)

©

Craig Hoyle/Flight

International

ExperimentReal CFD


DLR TAU Grid generation & Calculation

3 Block Chimera mesh generated with CentaurSoftComplete mesh –

Aircraft & 2 propellers:

36.437.330 nodesUnstructured finite volume RANS-flow solverUnsteady computation with dual time stepping scheme using a central scheme with matrix dissipationFully turbulent computation using 1-equation Spalart-Allmaras

turbulence

model with Edwards modification55 propeller rotations computed


PIV Set-up Wind tunnel arrangement

Field of view from4x PCO Sensicam

(2C)

2 Laskin

seeding generatorsDEHS droplets (1 µm)

Big Sky 200 Nd:YAG 350 mJ per pulse


PIV results indicate presence of blade vortices, but less pronounced (more smeared) effects in numerical results

Inviscid

modeling of blades

TAU computed slipstream vorticity shows generally good agreement in development of blade wakes and tip vortices

Comparison Plane 3 –

Symmetry plane


Inviscid/viscous blade treatment Plane 3 –

Symmetry plane

CFD results show slightly higher slipstream velocities than PIV results

6% overprediction

in peak magnitudeInviscid

blade modelingGenerally good agreement in terms of profile shape show CFD captures relevant flow phenomena wellGenerally good agreement in slipstream development (compare x/D=1.0 and x/D=1.5 for PIV and CFD results)


Determination of circulation

Circulation as summation over areas with positive vorticity:

Normalized by first tip vortex

Numerical dissipation causes decrease of circulation

Decreasing

Fairly constant

1 2 3 4 5 6 7


Conclusions

Propeller flow analyzed using PIV and CFDValidation of EFD and CFD not straightforward for propeller flowCFD: capable of unsteady RANS calculations for complex configurationsPIV: capable of measuring phase-locked velocity field

Comparison: Overall good agreement between unsteady RANS and phase-

locked PIVSimilarities in vortex position and wake developmentDifferences in velocities, mainly due to inviscid

modeling

In between propellers: complex vortex interactionsCalculation of circulation identifies numerical dissipation as probable cause for difference


Conclusions General

Particular issues for CFD:Full, comprehensive aerodynamic field data availableGeneration of appropriate density for grids (size versus resolution requirements, numerical dissipation) not easyTurbulence models for adequate vortex predictionDifficulties of stall characteristics (e.g. separated flow)

Particular issues for PIV:Provides instantaneous velocity data, 2-

or 3 components

Triggering at specific phase complex, but allows (phase-)averagingRelies on sufficient optical accessVolumetric data still in development stage (research wind tunnels)


Outlook, possibilities, needs

Establishment of required grid accuracy (limit grid size and complexity)Perform ‘real’

unsteady PIV (e.g. time-resolved)

Compare and validate with other available dataInvestigate effects of numerical dissipation, turbulence modelsEnhance both CFD and PIV capabilities with specific validation projects where both CFD and experiment are optimizedUse PIV data as:

‘Boundary conditions’

or input for CFD (steady/unsteady)Evaluation of geometry effects e.g. span wise circulation proportional to span wise lift

Incorporation of wind tunnel effects (sting support etc.) in CFD

analysisConcurrent design optimization: Fast turnaround times for PIV and CFD will lead to fewer design iterations in less total time


: [email protected]

Thank you for your attentionQuestions?

http://www.dlr.de/as/en


©

AIRBUS DEUTSCHLAND GMBH. All rights reserved. Confidential and proprietary document.

This document and all information contained herein is the sole property of AIRBUS DEUTSCHLAND GMBH. No intellectual property rights are granted by the delivery of this document or the disclosure of its content. This document shall not be reproduced or disclosed to a third party without the express written consent of AIRBUS DEUTSCHLAND GMBH. This document and its content shall not be used for any purpose other than that for which it is supplied.

The statements made herein do not constitute an offer. They are based on the mentioned assumptions and are expressed in good faith. Where the supporting grounds for these statements are not shown, AIRBUS DEUTSCHLAND GMBH will be pleased to explain the basis thereof.

AIRBUS, its logo, A300, A310, A318, A319, A320, A321,

A330, A340, A350, A380, A400M are registered trademarks.

High quality PIV data for numerical...

Documents

Transcript of High quality PIV data for numerical...