Landing Gear Noise Modelling – MUSAF III Colloquium Landing Gear Noise Modelling Progresses in LBM industrial use Aloïs SENGISSEN with contributions from Jean-Christophe GIRET, Christophe COREIXAS & Thomas ASTOUL
Landing Gear Noise Modelling – MUSAF III Colloquium
Landing Gear Noise Modelling Progresses in LBM industrial use
Aloïs SENGISSEN
with contributions from Jean-Christophe GIRET, Christophe COREIXAS & Thomas ASTOUL
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
JET TURBINE CORE
FORWARD FAN
REARWARD FAN
AIRFRAME ~50%
Introduction & stakes
Typical noise contribution breakdown
for a long range Aircraft at approach :
SLATS
FLAPS
CLEAN WING
HTP
NOSE L/G MAIN L/G
APPROACH – AIRFRAME only
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 2 / 36
Noise generation mechanisms
way more complex to capture
than noise propagation to farfield
Focus on sources
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
Enablers of Landing Gear noise High Fidelity simulation
Landing Gear Noise Modelling – MUSAF III Colloquium
Solver Scalability
Maintenance, adaptability
Advanced Boundary Conditions
Numerical properties
Solver core Performance
Coupling / far-field acoustic radiation
Turbulence modelling
Wall modelling
Abilities on very complex Geometries
Physical mechanisms
understanding
Assessed with step by step validation
Assessed with seamless
end to end workflow
Page 3 / 36
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Outline on Simulation accuracy
Landing Gear Noise Modelling – MUSAF III Colloquium
Numerical approach overview
Lattice-Boltzmann Solver LaBS
Coupling with FWH solver
Numerical Setup & Grids
Accuracy assessment
Mean & RMS Velocity fields comparison
CL and CD distributions
Wall pressure spectra comparison
Far field PSD & OASPL comparison
Sensitivity analysis to num. parameters
Grid convergence
Subgrid scale model influence
Wall law model components
Relevant test case : simplified LGs « LAGOON »
Full study available in
[AIAA2015–2993]
Page 4 / 36
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Outline on Industrial readiness
Landing Gear Noise Modelling – MUSAF III Colloquium
Physical mechanisms understanding
Wheels inner cavity modes – LAGOON1
Tow bar vortex shedding – LAGOON2
Wheel rim caps removal – LAGOON3
Corner stones towards industrial cases
Core performance & scalability
Flexible & Seamless meshing
of complex configurations
Perspectives of applications
on industrial configurations
Relevant test case : real A/C applications
Page 5 / 36
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Collaboration Airbus-ONERA (2006-2010) [Manoha_AIAA2008, Manoha_AIAA2009]
Highly detailed experimental data
Aerodynamic Measurements (F2 Wind Tunnel)
Acoustic Measurements (CEPRA19 Wind Tunnel)
LAGOON 1: Two wheels + Axle + Main Leg LAGOON 2: + Tow bar + Lights + Steering actuator LAGOON 3: + Torque link – Rim periphery caps
3 configurations of increasing complexity
LAGOON1 disclosed to NASA BANC III workshop, for accuracy & sensitivity assessment [Manoha_AIAA2015]
LAGOON2 & 3 used to cross compare geom. effects
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 6 / 36
LAGOON geometries & objectives
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Numerical Approach
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 7 / 36
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
• Latt & Chopard, “Lattice Boltzmann method with regularized pre-collision distribution functions," Math. & Comp. in Sim., 2006
• Augier & Dubois « Isotropy properties for lattice boltzmann schemes » ICMMES conference ,2012
• Marié, Ricot & Sagaut « Comparison between lattice Boltzmann method and Navier–Stokes high order schemes for
computational aeroacoustics», J. Comput. Phys.228, 1056-1070, 2009
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 8 / 36
Numerical Approach : LaBS solver
Lattice Boltzmann Solver (LaBS)
2010 – 2013 French collaborative project
Led by Renault, Airbus, CS, Univ. Paris VI, ECL
http://www.labs-project.org/
LaBS general numerical method
Classical LB approach, fully transient
D3Q19 BGK collision scheme, improved
with regularization [Latt_MCS2006] [Ricot_2013]
Octree mesh refinement,
specific treatment at resolution interface
Meshing embedded in the solver (and parallel!)
LaBS numerical properties
Low Numerical dispersion & dissipation [Marié_JCP2009]
Excellent isotropy properties [Augier/Dubois_ICMMES2011]
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
7 points filter
3 points filter
5 p
oin
ts filte
r
In-Flow Turbulence modelling
LES-LBM modelling using 2 possible subgrid-scale models
High order filtering “Approximate Deconvolution Model”, [Malaspinas_PoF2011, Malaspinas_JFM2012, Touil_PoF2013]
Subgrid scale model “Shear Improved Smagorinsky Model” [Leveque_JFM2007, Touil_PoF2013]
Near-wall turbulence modelling
Immersed boundaries with Bounce-back principles [Chen/Doolen_IJNMF2014]
Wall Laws with pressure gradient effect [Afzal_IUTAM_Symposium1996][Malaspinas_JCP2014]
Inlet & Outlet Boundary Conditions
Velocity imposed inlet & Pressure imposed outlet
Buffer zone as non-reflecting Boundary conditions [Xu/Sagaut_JCP2013] [Ricot_2013]
• Malaspinas & Sagaut « Consistent subgrid scale modelling for Lattice Boltzmann methods », J. Fluid Mech. 700, 514‐542 (2012)
• Malaspinas & Sagaut « Advanced Large‐eddy simulation for Lattice Boltzmann methods: the Approximate Deconvolution Model » Phys. Fluids. 23, 105-103, 2011
• Malaspinas & Sagaut « Wall model for Large‐eddy simulation on based on Lattice Boltzmann methods », J. Comput. Phys .275, pp. 25–40, 2014
• Xu & Sagaut « Analysis of the absorbing layers for the weakly‐compressible lattice Boltzmann methods », J. Comput. Phys.245, 14‐42, 2013
• Levêque & Bertoglio, « Shear-improved Smagorinsky model for large-eddy simulation of wall-bounded turbulent Flows," J. Fluid Mech. , Vol. 570, 2007, pp. 491-502
Landing Gear Noise Modelling – MUSAF III Colloquium
Numerical Approach : Turbulence Modelling
Page 9 / 36
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Numerical Approach : Grids
Setup
LAGOON LG as installed in anechoic WTT (no ceiling wall)
Constant velocity inlet & constant pressure outlet
Simple setup (meshing directives through GUI)
Meshes
Aim: Try to match the points distribution of a wall-modelled LES [Giret_AIAA2012] with fast turnover times
Wake region : 2mm to 4mm (based on simple shapes)
Near wall region : 0.4mm to 0.625mm (based on offsets of the geometry) ~ Y+ = 60
Rough mesh convergence study COARSE : 20M nodes MEDIUM : 40M nodes FINE : 80M nodes
CPU time on MEDIUM : 2 days on 360 core (0,32s physical time starting from scratch on intel XEON5-2697 @ 2,7Ghz)
10 / 36
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 10 / 36
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Accuracy Assessment
Landing Gear Noise Modelling – MUSAF III Colloquium
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Mean Axial Velocity : Plane Z = 0mm
LaBS_COARSE LaBS_MEDIUM
EXPE (PIV) LES [Giret_AIAA2012]
Results provided to
NASA BANC III workshop
Shear Layer thickness
Too thick on COARSE
mesh
Ok on MEDIUM mesh
Recirculation zone
Size ok
Intensity ok
Wake shape
Wake dimensions
qualitatively satisfying
Better predicted by LBM
than by LES
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 12 / 36
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-0.2
-0.1
0.0
0.1
0.2
y (
mm
)
100806040200 Streamwise velocity (m/s)
PIV X=220 Z=0
LaBS COARSE LaBS MEDIUM LES AVBP
X=220 mm
-0.2
-0.1
0.0
0.1
0.2
y (
mm
)
100806040200 Streamwise velocity (m/s)
PIV X=180 Z=0
LaBS COARSE LaBS MEDIUM LES AVBP
X=180 mm
Mean Velocity profiles
Excellent quantitative agreement
Improvement with MEDIUM mesh in
plane Z = -104 mm
-0.2
-0.1
0.0
0.1
0.2
y (
mm
)
100806040200 Streamwise velocity (m/s)
PIV X=160 Z=0
LaBS COARSE LaBS MEDIUM LES AVBP
X=160 mm
-0.2
-0.1
0.0
0.1
0.2
y (
mm
)
100806040200 Streamwise velocity (m/s)
PIV X=128 Z=-104
LaBS COARSE LaBS MEDIUM LES AVBP
X=128 mm
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Landing Gear Noise Modelling – MUSAF III Colloquium
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
RMS Axial Velocity : Plane Z = 0mm
LaBS_COARSE LaBS_MEDIUM
EXPE (PIV) LES [Giret_AIAA2012]
Shear on wheel flanks:
Size & intensity of
Shedding well predicted
on MEDIUM mesh
(X=0,2 ; Y=0,15)
Results in good
agreement
with LES (AVBP)
Results in good agreement
with PIV despite some
measurement artifacts
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 14 / 36
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-0.2
-0.1
0.0
0.1
0.2
y (
mm
)
3020100 Rms Streamwise velocity (m/s)
PIV X=220 Z=0
LaBS COARSE LaBS MEDIUM LES AVBP
-0.2
-0.1
0.0
0.1
0.2
y (
mm
)
3020100 Rms Streamwise velocity (m/s)
PIV X=128 Z=-104
LaBS COARSE LaBS MEDIUM LES AVBP
-0.2
-0.1
0.0
0.1
0.2
y (
mm
)
3020100 Rms Streamwise velocity (m/s)
PIV X=180 Z=0
LaBS COARSE LaBS MEDIUM LES AVBP
RMS Velocity profiles
-0.2
-0.1
0.0
0.1
0.2
y (
mm
)
3020100 Rms Streamwise velocity (m/s)
PIV X=160 Z=0
LaBS COARSE LaBS MEDIUM LES AVBP
X=220 mm X=180 mm X=160 mm X=128 mm
Fair quantitative agreement
Improvement with MEDIUM mesh
Subgrid scale contribution is NOT included
Landing Gear Noise Modelling – MUSAF III Colloquium
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
110
100
90
80
70
60
50
Pre
ssu
re P
SD
(d
B/H
z)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 1
LaBS COARSE LaBS MEDIUM
PSD at the wall : Wheel Rolling Band
Low freq. filter in the experiments (0 – 200Hz)
Tones @ 1KHz & 1.5kHz well captured
Low freq.
Filter in the
experiments
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 16 / 36
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110
100
90
80
70
60
50
Pre
ssu
re P
SD
(d
B/H
z)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 3 LaBS COARSE LaBS MEDIUM
Gradual increase of PSD levels at the wall
along with boundary layer development
PSD at the wall : Wheel Rolling Band
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 17 / 36
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130
120
110
100
90
80
70
Pre
ssu
re P
SD
(d
B/H
z)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 5 LaBS COARSE LaBS MEDIUM
Landing Gear Noise Modelling – MUSAF III Colloquium
PSD at the wall : Wheel Rolling Band
Page 18 / 36
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
130
120
110
100
90
80
70
Pre
ssu
re P
SD
(d
B/H
z)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 7 LaBS COARSE LaBS MEDIUM
K7 corresponds to the detachment point due to GradP
COARSE mesh predicts slightly earlier separation
Landing Gear Noise Modelling – MUSAF III Colloquium
PSD at the wall : Wheel Rolling Band
Page 19 / 36
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130
120
110
100
90
80
70
Pre
ssu
re P
SD
(d
B/H
z)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 8 LaBS COARSE LaBS MEDIUM
Flow fully detached at K8
Landing Gear Noise Modelling – MUSAF III Colloquium
PSD at the wall : Wheel Rolling Band
Page 20 / 36
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Physical Mechanisms Investigations
Landing Gear Noise Modelling – MUSAF III Colloquium
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
sdfsdf
Observation of cavity modes
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
FEM analysis conducted to cavity eigenmodes identification :
Mode @ 1048Hz
Mode @1529Hz
Superposition of these 2 modes observed in the simulations
Observation of cavity modes
y
x
y
x
Courtesy of EXA [Casalino_JSV_2014]
130
120
110
100
90
80
70
Pre
ssure
PS
D (
dB
/Hz)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 14 LaBS COARSE LaBS MEDIUM
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 23 / 36
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sdfsdf
Shedding of the Tow Bar
24 / 36
Shedding of the Tow Bar Landing Gear Noise Modelling – MUSAF III Colloquium
Page 24 / 36
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Peak around 1100Hz on K1 & K2
Emerging even more behind tow bar
Shedding of the Tow Bar
25 / 36
Pre
ssure
PS
D (
dB
/Hz)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
10
dB
Tow Bar Wake LaBS SISM_FINE
Pre
ssure
PS
D (
dB
/Hz)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
10
dB
Kulite 1 LaBS SISM_FINE LaBS SISM_MEDIUM
Pre
ssure
PS
D (
dB
/Hz)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
10
dB
Kulite 2 LaBS SISM_FINE LaBS SISM_MEDIUM
Landing Gear Noise Modelling – MUSAF III Colloquium
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Corner stones towards industrial cases
26 / 36
Landing Gear Noise Modelling – MUSAF III Colloquium
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Performance & Scalability
Landing Gear Noise Modelling – MUSAF III Colloquium
Numerical
Approach
NS – O(2) Centered + RK3
NS – O(3) DRP Tam + RK3
NS – O(6) Lele + RK6
LBM BGK scheme
Number of
Flop/iteration 711 2862 11295 588
Single core peak performance of LBM algorithm much faster than classical N-S :
Faster than any FD schemes, way faster than FV approaches (Courtesy of Sagaut et al.)
Accuracy of LBM collision scheme [Ricot_JCP2009]
Almost equivalent to O(3) in terms of dispersion
Way better than any classical approaches, incl. O(6), in terms of dissipation
Local time step (gift from octree mesh) yields additional performance benefits without the difficult compromises from implicit schemes
Overall computational cost ~1µs/iteration/cell (7x to 10x faster than fastest NS explicit schemes)
Page 27 / 36
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Performance & Scalability
Landing Gear Noise Modelling – MUSAF III Colloquium
Local algorithm, very suitable for massively parallel computing
Constant performance, and efficient speedup
~ 80% yet not perfect, due to the fast base algorithm
0
2
4
6
8
10
12
14
96 288 480 672 864 1056 1248
Speedup solver
Ideal speedup
number of cores
Page 28 / 36
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Seamless meshing of complex configurations
Landing Gear Noise Modelling – MUSAF III Colloquium
Geometrical details play a significant
role in noise radiated (HF content).
Real life configurations for LG noise
are much more than complex !!!
Structured meshes have given up
Unstructured becomes very tricky
Immersed octree takes the lead
Page 29 / 36
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Seamless meshing of complex configurations
Landing Gear Noise Modelling – MUSAF III Colloquium
Meshing done in parallel by the solver
Example without any wake refinement
Every second cell displayed
Page 30 / 36
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Seamless meshing of complex configurations
Landing Gear Noise Modelling – MUSAF III Colloquium
Scaling up seamlessly
Every second cell displayed
Page 31 / 36
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Perspective of applications
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 32 / 36
For acoustics purpose :
Real configurations can be finally investigated without hazardous simplifications
(unknown impact in terms of physics)
Installation effects reachable
Velocity deficit due to wing circulation,
Interaction between LG, Flaps,
Influence of NLG wake…
For wider purpose :
Steady loads
Unsteady loads
…
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Conclusions
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 33 / 36
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Conclusion & Lessons learned
Conclusions on accuracy of LBM
Level of agreement observed :
Very satisfying on both Mean & RMS velocity fields & integrated aero quantities (not shown today)
Very good agreement on wall PSD
Meaningful physical phenomena well captured
Gradual increase of wall PSD with BL development, then sudden change after detachment point
On LAGOON1, Cavity mode directly visible on time resolved wall pressure [Casalino2014] & [Giret2013]
On LAGOON2, Vortex shedding from tow bar perturbs this cavity mode and yields another peak (1100Hz)
However, everything is not yet perfect in current approach
Wall laws / near wall treatment
Parler des limites des transitions
Conclusions on industrial readiness
Engineer’s daily life game changer wrt unsteady well established NS-CFD methods
Real A/C geometry without simplification
Automatic/Flexible Billion cells mesh if needed
1000+ core scalable on HPC
Turnaround time breakthrough
Landing Gear Noise Modelling – MUSAF III Colloquium
Page 34 / 36
Next step
Take full benefit of LBM
techniques for other industrial
applications of interest.
© AIRBUS Operations S.A.S. All rights reserved. Confidential and proprietary document.
Landing Gear Noise Modelling – MUSAF III Colloquium
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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 S.A.S. This document and its content shall not be
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AIRBUS, its logo, A300, A310, A318, A319, A320, A321, A330, A340, A350, A380, A400M are registered trademarks.
Thank you for your attention !
ACKNOWLEDGEMENTS :
E. Manoha (ONERA) & B. Caruelle (Airbus) for LAGOON initiative
D. Ricot (Renault), B. Gaston & R. Cuidard (CS) for support on LaBS
G. Rahier (ONERA) for providing KIM FW-H solver
HP for powering Airbus’ HPC resources
Page 35 / 36