2 nd Workshop on Benchmark Problems for Airframe Noise Computations (BANC-II) 7-8 June 2012 Colorado...
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2 nd Workshop on Benchmark Problems for Airframe Noise Computations (BANC-II) 7-8 June 2012 Colorado Springs, Colorado, USA Category 1: Trailing-Edge Noise
2 nd Workshop on Benchmark Problems for Airframe Noise
Computations (BANC-II) 7-8 June 2012 Colorado Springs, Colorado,
USA Category 1: Trailing-Edge Noise M. Herr, German Aerospace
Center, DLR C. Bahr, NASA Langley Research Center M. Kamruzzaman,
University of Stuttgart (IAG) www.DLR.de Chart 1> M. Herr >
BANC-II > 07.06.2012, Colorado Springs, Colorado, USA BANC-II-1:
(TBL-)Trailing-Edge Noise
Slide 2
Introduction -Problem statement -Overview on contributions
& participants -Overview of used codes Participants
presentations on computational approach & on selected results
-Cristobal A. Albarracin et al., University of Adelaide, Australia
(UoA) -Mohammad Kamruzzaman, University of Stuttgart, Germany (IAG)
-Roland Ewert et al., German Aerospace Center (DLR) -Lawrence
Cheung & Giridhar Jothiprasad, GE Global Research, NY (GE-GRC)
-Damiano Casalino et al., EXA GmbH, Stuttgart, Germany (EXA)
Overall comparisons, summary, conclusions & outlook Discussion
Agenda 7 June 2012 BANC-II-1: Trailing-Edge Noise
Slide 3
Conclusions from BANC-I-1 During BANC-I we faced (low number of
participants) -the need for improvements of the problem statement
(definition of tripping, wing span for far field noise data,
definition of a single core case for those who can not afford
working on the full matrix, ) -the need to offer benchmark data
together with the updated problem statement. This should allow the
participants to elaborate deeper on their data and to give their
view on linking flow features with noise. For generating a
benchmark data base it was agreed that we do not focus -on a single
facility/measurement technique but take all available data from
different facilities/measurement techniques. -Obviously, there will
be a few dB deviation among different datasets which needs to be
handled as a tolerance range. -Thus, gathering trailing edge noise
data will be a big multidimensional puzzle. -Very probably, the
first set of data will consider a NACA0012 configuration. -The
updated problem statement should define input data which will be
-particularly linked to this configuration, i.e. inflow turbulence,
tripping details BANC-II-1 Problem Statement Introduction
Slide 4
Preparation of BANC-II-1 Unfortunately: Definition of the final
problem statement for BANC-II was late due to the necessary
collection and review of usable test data, clearance of GE
proprietary DU-96 data (many thanks to GE!), data scaling, were
necessary BANC-II-1 is understood as warm-up (majority of
participants apply faster prediction methods based on SNT) and will
hopefully activate multiplied follow- on activity by anyone
interested to join the community. The finally provided comparison
data is not perfect due to the non-existence of a fully consistent
data set covering the full measurement chain from near field source
quantities to farfield noise. BANC-II-1 Problem Statement
Introduction
Slide 5
BANC-II-1 Problem Statement Simulation Matrix BANC-II-1 Test
Cases Provide c p (x 1 ), c f (x 1 ), near-wake mean flow/
turbulence profiles, G pp (f), L p (f c ) and FF noise
directivities for CASES#1-5 Case#1 56 m/s 0 Case#2 55 m/s 4 Case#3
53 m/s 6 Case#4 38 m/s 0 Case#5 60 m/s 4 Full problem statement
with more specified definitions of Profile coordinates (sharp TE!)
Tripping devices (TBL-TE noise!) TBL transition locations Ambient
conditions, etc. Data formatting instructions including templates
is available at the BANC-II homepage:
https://info.aiaa.org/tac/ASG/FDTC/ DGBECAN_files_/BANCII_category1
CASE#1: single core test case for those who can not afford the full
matrix
Slide 6
BANC-II-1 Problem Statement Simulation Matrix BANC-II-1 Test
Cases Coordinate System and Parameter Definition Orientation of
flow profiles Position @ 100.38 % l c WPF sensor position @ 99 % l
c PSDs (measurement data normalized to f = 1 Hz) SS PS b = 1 m r =
1 m in 1/3-octave bands = 90 chord-normal view direction for noise
prediction
Slide 7
BANC-II-1 Problem Statement Simulation Matrix BANC-II-1 Test
Cases Available comparison data sets for CASES#1-5: Case#1 56 m/s 0
c p (x 1 ), flow/turb. profiles, G pp (f), L p(1/3) (f c ) Case#2
55 m/s 4 c p (x 1 ), flow/turb. profiles, G pp (f), L p(1/3) (f c )
Case#3 53 m/s 6 c p (x 1 ), flow/turb. profiles, G pp (f), L p(1/3)
(f c ) Case#4 38 m/s 0 Flow/turb. profiles, G pp (f), L p(1/3) (f c
) Case#5 60 m/s 4 L p(1/3) (f c )
Slide 8
Near-Wake Data CASES#1-4 IAG-LWT (Herrig et al.) BANC-II-1
Problem Statement Overview of Comparison Data IAG-LWT 2- point
correlation measurements
Slide 9
Acoustical Data Sets CASES#1 and #2 (IAG, DLR, UFL, BPM)
Scaling to problem statement conditions required for both G pp (f)
and L p(1/3) (f c )! BANC-II-1 Problem Statement Overview of
Comparison Data +/3 dB scatter among all available data sets
Slide 10
Acoustical Data Sets CASES#3 and #5 (CASE#4 not shown) Scaling
to problem statement conditions required! BANC-II-1 Problem
Statement Overview of Comparison Data
Slide 11
BANC-II-1 Contributions & Participants Overview
Configuration/ Participant UoAIAGDLRGE-GRCEXA Case#1 56 m/s 0 --
Case#2 55 m/s 4 - - Case#3 53 m/s 6 - - Case#4 38 m/s 0 - - Case#5
60 m/s 4 Different case! AIAA-2012-2055 - Overview on
Contributions
Slide 12
Fast TE noise prediction method, based on a statistical model
of the turbulent velocity cross-spectrum. Overview of Methods
Contribution Albarracin et al.: UoAs RSNM code RSNM: RANS-based
Statistical Noise Model RANS CFD RANS CFD Turbulent velocity
cross-spectrum model + Half-Plane Greens function Turbulent
velocity cross-spectrum model + Half-Plane Greens function OpenFOAM
package k-omegaSST model CFD Mesh RSNM Acoustic spectrum in the far
field Example results: 30.48 cm chord NACA 0012 airfoil at AoA=0
and flow velocities of 31.7 m/s, 39.6 m/s, 55.5 m/s and 71.3 m/s
cf. AIAA-2012-2181
Slide 13
Simplified theoretical airfoil trailing-edge far-field noise
prediction model based on steady RANS: highly accurate and very
fast Overview of Methods Contribution Kamruzzaman et al.: IAGs
simplified theoretical prediction code Rnoise Rnoise: RANS Based
Trailing-edge Noise Prediction Model Governing Eqns. Source
Modeling RANS Simulation Noise Spectra WPF BL & Correlations
Wind Tunnel Exp. & Validation
Slide 14
CAA APE CAA APE mean flow; here: DLR code TAU with RSM
turbulence Sound Field source Overview of Methods Contribution
Ewert et al.: DLRs CAA-Code PIANO with stochastic source model FRPM
PIANO: Perturbation Investigation of Aeroacoustic Noise Low-cost
steady RANS-based CAA with stochastic source models: 2-4 orders
faster than LES k Spectral analysis CFD RANS CFD RANS 4D-Stochastic
Sound Sources FRPM 4D-Stochastic Sound Sources FRPM vortex sound
sources
Slide 15
High-fidelity incompressible LES calculation combined with
Amiets theory for far-field noise Overview of Methods Contribution
GE GRC: LES with Amiets Theory (CharLES code, Cascade Technologies)
CharLES: LES-based trailing edge noise prediction Unstructured mesh
LES simulation Amiets Theory Far-field Sound High-fidelity grid
near TE and airfoil surface Capture boundary layer, wall-pressure
spectra, and correlation data near TE Project TE information to
far-field observer locations cf. AIAA-2012-2055
Slide 16
1.Unsteady-flow simulations performed with Lattice Boltzmann
based solver PowerFLOW 4.3 D3Q19 LBM Cubical Lattices (Voxels)
Surface elements (Surfels) Explicit solver Fully transient
Turbulence model Modified RNG k- model Swirl model Anisotropic
large eddies resolved Statistically universal eddies modeled
Extended wall model Taking pressure gradient effect into account
Acoustic fluctuations directly simulated with low-dispersion and
low dissipation 2.Far-field noise computed using a FW-H acoustic
analogy (PowerACOUSTICS 2.0) Solid/permeable formulation
Forward-time formulation based on the retarded-time formulation 1A
by Farassat Mean flow convective effects (wind-tunnel modality)
taken into account 3.Spectral analyses carried out using
PowerACOUSTICS 2.0 Overview of Methods Contribution Damiano
Casalino et al.: EXAs PowerFlow / PowerAcoustics code PowerFLOW /
PowerACOUSTICS 123 cf. AIAA-2012-2235
Slide 17
Thank you for your attention!
Slide 18
Agenda 7 June 2012 BANC-II-1: Trailing-Edge Noise Introduction
-Problem statement -Overview on contributions & participants
-Overview of used codes Participants presentations on computational
approach & on selected results -Cristobal A. Albarracin et al.,
University of Adelaide, Australia (UoA) -Mohammad Kamruzzaman,
University of Stuttgart, Germany (IAG) -Roland Ewert et al., German
Aerospace Center (DLR) -Lawrence Cheung & Giridhar Jothiprasad,
GE Global Research, NY (GE-GRC) -Damiano Casalino et al., EXA GmbH,
Stuttgart, Germany (EXA) Overall comparisons, summary, conclusions
& outlook Discussion
Slide 19
Code-to-code comparisons for the following parameters: 4
slides: c p, c f for CASES#1, #2, #3, #5 5 slides (1 per case):
Near-wake profiles of mean velocity and turb. characteristics 1
survey slide on integral TBL properties 2 slides: Surf. pressure
(WPF) PSD for CASES#1, #2, #3, #5 2 slides: FF TBL-TE noise spectra
for CASES#1, #2, #3, #5 1 slide: Selected FF noise directivities
Changed representation format to extract principle relative effects
on noise and on WPF spectra (are those well-predicted?) -Effect of
test velocity CASES#1, #4 -Effect of a-o-a CASES#1, #2, #3 -Effect
of profile shape CASES #2, #5 Overall Comparisons Introduction
Case#156 m/s Case#255 m/s Case#353 m/s Case#438 m/s Case#560 m/s
Scope
Slide 20
Aerodynamical data C p -Distributions CASES#1 & #2 Overall
Comparisons Format: comparison data in black! UoA: OpenFOAM - SST
IAG: FLOWER (DLR) - SST DLR: TAU (DLR) - RSM
Slide 21
Aerodynamical data C p -Distributions CASES#3 & #5 Overall
Comparisons Format: comparison data in black! UoA: OpenFOAM - SST
IAG: FLOWER (DLR) - SST DLR: TAU (DLR) - RSM
Slide 22
Overall Comparisons Aerodynamical data C f -Distributions
CASES#1 & #2 UoA: OpenFOAM - SST IAG: FLOWER (DLR) - SST DLR:
TAU (DLR) - RSM UoA: fully turbulent, no transition!
Slide 23
Overall Comparisons Aerodynamical data C f -Distributions
CASES#3 & #5 UoA: OpenFOAM - SST IAG: FLOWER (DLR) - SST DLR:
TAU (DLR) - RSM UoA: fully turbulent, no transition!
Slide 24
Aerodynamical data Near-Wake Flow Characteristics Overall
Comparisons
Slide 25
Near-Wake Flow Characteristics CASE#1 SS Aerodynamical data
Overall Comparisons UoA IAG DLR
Slide 26
Near-Wake Flow Characteristics CASE#2 SS Aerodynamical data
Overall Comparisons UoA IAG DLR
Slide 27
Near-Wake Flow Characteristics CASE#3 SS Aerodynamical data
Overall Comparisons UoA IAG DLR
Slide 28
Near-Wake Flow Characteristics CASE#4 SS Aerodynamical data
Overall Comparisons UoA IAG DLR
Slide 29
Near-Wake Flow Characteristics CASE#5 SS Aerodynamical data
Overall Comparisons UoA IAG DLR
Surface Pressure Data Overall Comparisons Position @ 99 % l c
PSDs (measurement data normalized to f = 1 Hz) SS PS
Slide 32
Surface Pressure Data Unsteady Surface Pressure PSD G pp (f)
CASES#1 & #2 f, kHz UoA: no surface pressure data provided IAG:
Rnoise DLR: PIANO-FRPM Overall Comparisons G pp, dB ( f = 1
Hz)
Slide 33
Unsteady Surface Pressure PSD G pp (f) CASES#3 & #5 Surface
Pressure Data no measured comparison data available! Overall
Comparisons G pp, dB ( f = 1 Hz) IAG: Rnoise DLR: PIANO-FRPM Data
has been scaled from different case! GE-GRC: CHARLES
Slide 34
TBL-TE FF Noise Data Overall Comparisons b = 1 m r = 1 m
1/3-octave band spectra = 90 chord-normal view direction for noise
prediction
Slide 35
Farfield Noise Data 1/3-Octave Band FF Noise Spectra L p(1/3)
(f c ) CASES#1 & #2 Overall Comparisons UoA: RSNM IAG: Rnoise
DLR: PIANO-FRPM
Slide 36
1/3-Octave Band FF Noise Spectra L p(1/3) (f c ) CASES#3 &
#5 Farfield Noise Data Overall Comparisons UoA: RSNM IAG: Rnoise
DLR: PIANO-FRPM Data has been scaled from different case! GE-GRC:
CHARLES
Slide 37
Selected 1/3-Octave Band FF Noise Directivities: CASE#1
Farfield Noise Data Overall Comparisons IAGDLR
Slide 38
L p(1/3) (f c ) and G pp (f) data revisited to identify common
trends; are relative effects captured by the predictions? Pressure
Data Overall Comparisons
Slide 39
Effect of Flow Velocity on L p(1/3) (f c ) and G pp (f): CASE#1
vs. #4 Pressure Data U = 56 m/s U = 38 m/s Format: measured
comparison data in black!
Slide 40
Overall Comparisons Effect of a-o-a on L p(1/3) (f c ): CASES#1
to #3 Pressure Data a-o-a 0 4 6 Measurement data DLR AWB data IAG
LWT data
Slide 41
Overall Comparisons Effect of a-o-a on L p(1/3) (f c ): CASES#1
to #3 Pressure Data a-o-a 0 4 6 DLR AWB data IAG LWT data Symbols:
Measurement data Lines: Simulation results
Slide 42
SS PS Overall Comparisons Effect of a-o-a on G pp (f): CASES#1
to #3 Pressure Data IAG simulation Measurement data DLR
simulation
Slide 43
Overall Comparisons Effect of Profile on L p(1/3) (f c ) and G
pp (f): CASES#2 vs. #5 Farfield Noise Data Measurement data SS
PS
Slide 44
Overall Comparisons Effect of Profile on L p(1/3) (f c ) and G
pp (f): CASES#2 vs. #5 Farfield Noise Data Symbols: Measurement
data Lines: Simulation results SS PS
Slide 45
Summary Still comparatively low number of participants
(however, increased w.r.t BANC-I!) Mainly results of faster
approaches using SNT have been shown (UoA, IAG, DLR); two last
minute LES contributors joined us; however, overall comparisons
were limited (GE-GRC: existent results for a different test case
have been roughly scaled to correspond to CASE#5 in the statement;
EXA: data provided for single core test CASE#1?). We have seen very
interesting results (with some room for improvement) with many
similarities but also significant differences within the delivered
data: -In most of the cases TBL-TE FF noise predictions were within
the provided data scatter band (reproducing systematic error
between test facilities) -General trends (shape effect, velocity
scaling) are mostly covered -But: spectral shapes/ main spectral
characteristics are not always perfectly predicted (here: expected
measurement data scatter is much smaller; IAG and DLR data collapse
within +/- 1.5 dB!)
Slide 46
Outlook 1/2 Extension of the existing data base by additional
DU-96 data sets by Virginia Tech (c p -distributions and acoustical
data): -Data measured under NREL funding (described in the report
Devenport W., Burdisso R.A., Camargo H., Crede E., Remillieux M.,
Rasnick M., van Seeters P., Aeroacoustic Testing of Wind Turbine
Airfoils, Subcontract Report NREL/SR-500-43471, 2010 ).
63-microphone phased array data with conventional beamforming
processing (test performed in 2007). -New DU-96 data (currently
being processed) at 4 speeds and 5 a-o-a; 0, 4, 8, 12, 16 128
microphone phased array with advanced beamformer. Others? -Data
owners of additional suitable data sets are highly encouraged to
contribute to the BANC-II, III data base; please contact
[email protected][email protected]
Slide 47
Outlook 2/2 BANC-III (if desired) will keep the existing
CASES#1-5, the by now established BANC-II data base is open for use
to anyone interested and will be maintained according to your
feed-back Need for additional test cases, add-ons (wind tunnel
environment, additional mechanisms, etc.)? BANC-II documentation
(presentations, reports, workshop minutes) will be uploaded at the
BANC-II website after the workshop:
https://info.aiaa.org/tac/ASG/FDTC/DGBECAN_files_/BANCII_category1
Slide 48
Thank you for your attention!
Slide 49
Agenda 7 June 2012 BANC-II-1: Trailing-Edge Noise Introduction
-Problem statement -Overview on contributions & participants
-Overview of used codes Participants presentations on computational
approach & on selected results -Cristobal A. Albarracin et al.,
University of Adelaide, Australia (UoA) -Mohammad Kamruzzaman,
University of Stuttgart, Germany (IAG) -Roland Ewert et al., German
Aerospace Center (DLR) -Lawrence Cheung & Giridhar Jothiprasad,
GE Global Research, NY (GE-GRC) -Damiano Casalino et al., EXA GmbH,
Stuttgart, Germany (EXA) Overall comparisons, summary, conclusions
& outlook Discussion
