1CEAS BBN Workshop 2008, Bilbao EU Framework 6 Research
PROBAND: Improvement of Fan Broadband Noise Prediction: Experimental investigation
and computational modelling
- Selected Final Results -
Lars Enghardt, DLR BerlinProject Coordinator
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EU FP6, Call 2, STREP PROBAND
Consortium:DLR - Deutsches Zentrum für Luft und Raumfahrt (DE) RR - Rolls-Royce plc (UK)SnM - Snecma Moteurs (FR)ECL - Ecole Centrale de Lyon (FR)Flu - Fluorem SAS (FR)ONERA - Office National d’Études et Recherches Aérospatiales (FR)UPMC - Université Pierre et Marie Curie (FR)ISVR - Institute of Sound and Vibration Research (UK) UCAM - University of Cambridge (UK)TUB - Technische Universität Berlin (DE)VKI - Von Karman Institute (BE)UR3 - Università Roma Tre (IT)KTH - Kungliga Tekniska Högskolan (SW)NLR - Nationaal Lucht- en RuimtevaartLaboratorium (NL)ACAT - Anecom Aerotest (DE)
• Budget: 5 M€• Project start: 1. April 2005 • Duration: 3,75 years
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Motivation: Broadband Fan Noise Sources
Interaction mechanism between
• The blade-tip of the rotor fan and the turbulent boundary layer on the inlet-duct (rotor boundary layer interaction noise)
• Turbulent eddies convected in the rotor boundary layer and the rotor trailing edge (rotor self noise)
• The rotor wake and the downstream outlet guide vanes (OGV interaction noise)• Turbulent eddies convected in the vane boundary layer and the vane trailing edge
(OGV self noise)
Rotor boundary layer interaction noise OGV self noise
Rotor self noise OGV interaction noise
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Project Structure
WP1: Co-ordination, specifications
WP2: Single source studies and model development
WP3: Laboratory scale fan rig test : Development of novel
measurement and CFD prediction techniques
WP4: Industrial Fan-OGV noise: Methods Validation
and Demonstration
WP1: Assessment, exploitation
WP2
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WP2: Single source studies and modeldevelopment
Objective• Develop and assess improved existing and future broadband
noise prediction tools
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Features• NACA5510: c =200 mm ; span: 200mm • High lift: 5% camber and 15o AoA• Gap: h~ 10 mm= 5% c • U0= 70 m/s (M~0.2; Rec~9.3 105)• Low turbulence inflow (0.7%)• Incoming TBL: d~ 1.8h (99% thickness)
Variations of parameters: U0 , AoA and h
• TE noise• Tip/casing noise
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1-1.5
-1
-0.5
0
0.5
1
1.5
2
x/c
-CP
a = 5°
a = 10°
a = 15°
Cp at mid span
Measurements
• PIV, LDA, HWA • Wall pressure• Far field • Combined measurements
Single Airfoil experiment (ECL)
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Implementation
B& K “low cost” ICP -microphones Pressure tube
HW probeGapPin hole
Single Airfoil experiment, unsteady pressure measurements (ECL)
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Steady Flow in gap region : mid-gap sectionU0 = 70 m/s ; a= 15o ; h= 10 mm ;
Single Airfoil experiment, PIV and HWA (ECL)
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Velocity spectra (HWA); gap=10 mmx/c=0.95 ; mid gap
Hump between 1 and 3 kHz and global amplification above 500 Hz
10370
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105
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PS
D (d
B -
ref 4×
10-1
0 Pa2 )
frequency (Hz)
AoA = 15 deg - U0= 70 m/s : spectra for probe: 29
gap 0gap 1gap 2gap 3gap 5gap 10
Frequency (Hz)
PSD
(dB
–re
f10−
10Pa
2 )
pressure spectrax/c=0.95 ; 1.5 mm from tip
Single Airfoil experiment, unsteady velocity/pressure spectra (ECL)
TIP flowPress. side
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BBN modeling: TE noise model (ECL)
• Mechanism: Pressure perturbations are scattered as acoustic waves at the TE
• The far-field sound pressure PSD is related to the wall-pressure statistics closely upstream of the trailing-edge
• For a large aspect ratio airfoil, this relation comes down to
Convection speed
Wall-pressure spec. Spanwisecoherence scale
Analytical response function
Input from exp. and/or CFD
New: Wall pressure spectrum can be inferred from RANS computed TBL properties [Rozenberg et al (2008)]
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Wall pressure spec. predicted from RANS
Exp. data: Far field
TE model
BBN modeling: Application (ECL)
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Wall pressure spec. predicted from RANS
Exp. data: Far field
TE model
BBN modeling: Application (ECL)
today
tomorrow
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Wavelet analysis of pressure fluctuations (UR3, ECL)
Conditional statistics of pressure or velocity based on localized pressure events extracted using wavelet indicators
Local Intermittency Measure:equivalent to a 2D representation of the Fourier auto-spectrum
(Camussi et al., AIAA 2007-3685, Grilliatet al., AIAA 2008-2845 )
Cross-Wavelet: equivalent to a 2D representation of the Fourier cross-spectrum(Camussi et al., JFM 2008 )
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Averaged signatures (UR3, ECL)
• Oscillations are due to the gap• Event duration scales with U0
1/2
• Potential point-vortex model: pressure induced by co-rotating vortices
• Events are originated at about 50-60% the chord length
• Results confirmed from the far-field pressure conditioning: noise source?
Averaged PIV signatures
Averaged wall-pressure signatures
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Averaged signatures (UR3, ECL)
• Oscillations are due to the gap• Event duration scales with U0
1/2
• Potential point-vortex model: pressure induced by co-rotating vortices
• Events are originated at about 50-60% the chord length
• Results confirmed from the far-field pressure conditioning: noise source?
Averaged PIV signatures
Averaged wall-pressure signatures
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• Simulation of boundary layer broadband noise with IDDES
CFD on Selfnoise (TUB)
• grid: 5.3 million cells• 40 cells in span wise
• span wise extent 1cm (d/c = 0.05) • LES like grid on suction side
• dx = 2*dz = 0.5 mm
• coarser grid on pressure side
Vortex structures colored with velocity magnitude (λ2),on slice: visualization of radiated sound (dp/dt)
Grid slice
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• Simulation of boundary layer broadband noise with IDDES
→ Simulation shows fully attached resolved boundary layer
– RANS/LES blending inside turbulent boundary layer
→ Interaction of turbulent boundary structures with TE generates broadband noise in the far field
→ broadband noise directivity shows typical dipol directivity
broadband noise directivity in dB from 100 Hz to 30 kHz
Boundary layer analysis at x/c=0.25red: u+- y+ plotblack: blending function RANS/LES(lines – averaged, symbols - instanteneous)
CFD on Selfnoise (TUB)
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• Simulation of boundary layer broadband noise with IDDES
→ Simulation shows fully attached resolved boundary layer
– RANS/LES blending inside turbulent boundary layer
→ Interaction of turbulent boundary structures with TE generates broadband noise in the far field
→ broadband noise directivity shows typical dipol directivity
broadband noise directivity in dB from 100 Hz to 30 kHz
Boundary layer analysis at x/c=0.25red: u+- y+ plotblack: blending function RANS/LES(lines – averaged, symbols - instanteneous)
CFD on Selfnoise (TUB)
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LES of a Fan-Tip with gap: characteristics (FLU)
10 mm gap
NACA 5510 : 200 mm chord & height
70 m/s
• Single airfoil configuration with gap,representative of an engine fan-tip / turbulent boundary layer interaction, generator of broadband noise
• 3D N.S. compressible simulation realized at Fluorem with Turb'Flow®
≈ 3 000 000 grid nodesMultiblock structured finite volume Jameson centered spatial scheme 4th orderExplicit 3 steps Runge Kutta of Wray time marching, Δt = 2 10-9 sLES filtered structure function turbulence model (following Ducros, Comte and Lesieur) Computations realized on 16 CPU cores (AMD Opteron® @2400 Mhz)
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• A fully unsteady configuration• Time-averaging of aerodynamic fields• Large tip-vortex flow interaction with incoming
boundary layer + TE vortex shedding: associated to broadband noise sources
LES of a Fan-Tip with gap: aerodynamics (FLU)
Velocity profiles :Mean and ...
Flow
str
uctu
re :
The
tip v
orte
x flo
w... fluctuations(e.g. Ptgap15)
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ListenerProp
agati
on
Different integration surfaces
• Ffowcs Williams and Hawkings (FWH) acoustic analogy associated with a retarded time formulation
• FWH pressure surfaces time series, recorded during
LES of a Fan-Tip with gap: acoustics (FLU)
Surface 0 Surface 1
Surface 3Surface 2
LES computation– Observers
placed on a 2D circle
– Example :
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WP3: Laboratory scale fan rig test : Development of novel measurement and CFD prediction techniques
• Objectives• provide a parametric study on broadband noise sources in a
laboratory-scale fan rig • develop advanced measurement techniques on this fan rig • evaluate the predictions of the broadband noise of the laboratory
fan rig using the RANS/semi-analytic methods and validated LES/DES models
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Low speed scalefan rig (DLR Berlin)
24-blade rotor
16-vanestator
D = 0.5 mMtip = 0.22Re = 220 000
Setup of laboratory scale experiment (DLR)
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Rotor shaft extension to increase rotor-stator gap
32-vanestator
Setup of laboratory scale experiment (DLR)
Grid for increased inflow turbulence
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wall flush mountedmicrophones
+1 ref. microphone
inlet
inter-stagesection
pressure side
microphone rakes+ 1 ref. microphone
24-blade rotor 16/32-vane stator
Anechoic termination
throttle
X hot-wire probesrotor & stator
pressure sensors
wall staticpressure sensors
- performance measurements- hot-wire velocity measurements- acoustic measurements- blade unsteady pressure measurements
Setup of laboratory scale experiment (DLR)
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Effects on acoustic spectra:
Max. levels near Blade PassingFrequency
Nearly constant decay
Increasing levels with increasing speed
Experimental result: Effect of fan speed (DLR)outlet duct
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0 10 20 30 40 50 60 70 80 90 100 110 120 130engine order
PSD
[dB/
eo]
100% speed 85% speed75% speed65% speed50% speed
Total broadband power vs fan speed
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1,65 1,70 1,75 1,80 1,85 1,90 1,95 2,00 2,05
log( fan speed [%] )
PWL
[dB
]
measuredpower fit
2.5tipBBN UP ∝
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Effects on acoustic spectra:
Max. levels near Blade PassingFrequency
Nearly constant decay
Increasing levels with increasing speed
Experimental result: Effect of fan speed (DLR)outlet duct
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0 10 20 30 40 50 60 70 80 90 100 110 120 130engine order
PSD
[dB/
eo]
100% speed 85% speed75% speed65% speed50% speed
Total broadband power vs fan speed
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1,65 1,70 1,75 1,80 1,85 1,90 1,95 2,00 2,05
log( fan speed [%] )
PWL
[dB
]
measuredpower fit
2.5tipBBN UP ∝
tomorrow
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RANS Calculations for DLR Low Speed Fan (RR)
Centrebody added upstream of rotor blade
RANS study of effect of including upstream centrebody as part of the CFD mesh
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Axial Velocity at plane X2, Downstream of Rotor
Original k-ω/SST k-ω/SST with Centrebody
RANS Calculations for DLR Low Speed Fan (RR)
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Turbulence Energy at plane X2, Downstream of Rotor
Original k-ω/SST k-ω/SST with CentrebodyExperiment
RANS Calculations for DLR Low Speed Fan (RR)
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(Semi)analytical modelling (ISVR)
Upstream PWL Downstream PWL
The broadband noise model was fed with Tu-levels from theexperiments and with the outcome of a RANS calculation.
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(Semi)analytical modelling (ISVR)
Upstream PWL Downstream PWL
The broadband noise model was fed with Tu-levels from theexperiments and with the outcome of a RANS calculation.
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LES computations (DLR)
Multi-block structure of the LES mesh
Domain:– Resolves 1 rotor passage and 1
stator passage– Upper and lower boundaries
directly connected (flowassumed periodic)
– Extends 1 rotor chordlengthupstream/downstream of stage
Mesh:– 100x106 cells over 1100 blocks– Span resolved with 600 cells– Tip resolved with 45 cells– Low-Reynolds
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Iso-surfaces of the axial component of vorticity in rotor system.
Rotor leading edge
Rotor tip vortex
Rotor wake region
Stator leading edge
Successive rotor wakes
Iso-surfaces of the axial component of vorticity in stator system.
Rotor trailing edge
Stator trailing edge
LES computations (DLR)
Computed turbulent flow structures
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Rotor-stator interactionClose view of
blade-vane interaction
Iso-surface of Q colored by entropy
LES computations (ONERA)
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Far-field acoustic radiation
0 1 2 3 4 5 67 8 9 10
015
3045
6075
90
05
1015202530354045505560
Frequency (kHz)on Angle (deg)
SP
L (d
B/H
z, re
. 20
µPa)
Radiation Angle (deg)
Input: LES data on OGV
LES computations (ONERA)
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0 2000 4000 6000 8000 10000Frequency (Hz)
PW
L (d
B/H
z, re
. 1 p
W)
Broadband (test)Mean spectrumAnalytic spectrumCoherent sources
PSD of in-duct sound power
LES computations (ONERA)
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0 2000 4000 6000 8000 10000Frequency (Hz)
PW
L (d
B/H
z, re
. 1 p
W)
Broadband (test)Mean spectrumAnalytic spectrumCoherent sources
PSD of in-duct sound power
LES computations (ONERA)
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WP4: Industrial Fan-OGV noise: Methods Validation and Demonstration
Objective• Validation and demonstration of the computational methods
developed and assessed in WP2 and WP3
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Setup of industrial fan experiment (ACAT, RR, VKI)
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Pressure measurements on OGV (DLR)
5 dB
Pressure sensor arragement on stator vane surfaces
Variation of total broadband surface autopower levels for five working lines
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stator
intake array
bypass array
rotor
Induct Beamforming (NLR)
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stator
intake array
bypass array
rotor
Induct Beamforming (NLR)
tomorrow
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Fan Blade
High Fan Speed (transonic flow)
k-ω/SST RANS
Wake data extracted on OGV “leading edge plane” Noise Models
Turbulence Energy, k (m2/s2)
Industrial Test Rig RANS result (RR)
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Radius
OGV Leading Edge Peak Turbulence Energy (m2/s2)
Fan Working Line Variation
Hub Casing
Industrial Test Rig RANS result (RR)
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Radius
OGV Leading Edge Peak Turbulence Energy (m2/s2)
Fan Working Line Variation
Hub Casing
Industrial Test Rig RANS result (RR)
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CFD of FAN-OGV-ESS: characteristics (FLU)
• Industrial test rig, including rotating fan and two stator vanes (bypass and core ducts)
• Number of blades: FAN=20, OGV=44 modelled by a 1:2 ratio
• 3D N.S. compressible simulation realized at Fluorem with Turb'Flow® :
High fan speed (transonic flow) ≈ 6500000 grid nodes, Multiblock structured finite volumeUpwind spatial scheme 3rd order with limiters (because flow field with shocks)Explicit 5 steps Runge Kutta time marching with 1500000 Δt per 360° rotation Rotor-stator interactions modeled by a sliding mesh technique using DFTHybrid RANS-Wilcox / LES-WALE (Wall Adapting Large Eddy following Nicoudand Ducros, Flow turbulence and combustion 62:183-200, 1999) Computations realized on 24 CPU cores (AMD Opteron® @2400 Mhz)
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CFD of FAN-OGV-ESS: Mean meridian flow (FLU)
Sample hyb. RANS-LES results :
Azimuthal and temporal averagesof aerodynamic fields
Locations of experimentalmeasurement sectionsin the x-r meridian mesh
Meridian mean total velocities
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CFD of FAN-OGV-ESS: Acoustics (FLU)
Instantaneous velocity divergence
Wake visualizations (entropy)
Pres
sure
and
Vel
ocity
spec
tra
at th
e st
ator
inle
t
Next steps :• Characterization of near field acoustic
sources• Far field noise propagation
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Summary: Final results
• PROBAND enables improved physical understanding of the source mechanisms of self noise, interaction noise, and tip clearance noise. The fundamental experiments provide, in conjunction with advanced CFD, a deeper insight into the flow physics in the source regions.
• PROBAND has developed new tools allowing large scale advanced CFD, and validated them in a realistic experimental environment.
• PROBAND delivers an improved prediction capability for broadbandnoise that will be exploited by the European engine industry to develop low broadband noise fan concepts.