Development of Simulation Methodologies for Forced Mixers Anastasios Lyrintzis School of Aeronautics...
-
Upload
trista-raven -
Category
Documents
-
view
215 -
download
0
Transcript of Development of Simulation Methodologies for Forced Mixers Anastasios Lyrintzis School of Aeronautics...
Development of Simulation Methodologies for Forced Mixers
Anastasios Lyrintzis
School of Aeronautics & Astronautics
Purdue University
Acknowledgements
• Indiana 21st Century Research and Technology Fund
• Prof. Gregory Blaisdell
• Rolls-Royce, Indianapolis (W. Dalton, Shaym Neerarambam)
• L. Garrison, C. Wright, A. Uzun, P-T. Lew
Motivation
• Airport noise regulations are becoming stricter.
• Jet exhaust noise is a major component of aircraft engine noise
• Lobe mixer geometry has an effect on the jet noise that needs to be investigated.
Methodology
• 3-D Large Eddy Simulation for Jet Aeroacoustics
• RANS for Forced Mixers
• Coupling between LES and RANS solutions
• (Semi-empirical method)
3-D Large Eddy Simulation for Jet Aeroacoustics
Objective
• Development and full validation of a Computational Aeroacoustics (CAA) methodology for jet noise prediction using: A 3-D Large Eddy Simulation (LES) code
working on generalized curvilinear grids that provides time-accurate unsteady flow field data
A surface integral acoustics method using LES data for far-field noise computations
Numerical Methods for LES• 3-D Navier-Stokes equations• 6th-order accurate compact differencing scheme
for spatial derivatives• 6th-order spatial filtering for eliminating
instabilities from unresolved scales and mesh non-uniformities
• 4th-order Runge-Kutta time integration• Localized dynamic Smagorinsky subgrid-scale
(SGS) model for unresolved scales
Tam & Dong' s radiation boundary conditions
Tam & Dong' s radiation boundary conditions
Tam & Dong' soutflow boundaryconditions
Sponge zone
Tam &Dong' sradiationbcs
Vortex ring forcing
Computational Jet Noise Research
• Some of the biggest jet noise computations: Freund’s DNS for ReD = 3600, Mach 0.9 cold
jet using 25.6 million grid points (1999) Bogey and Bailly’s LES for ReD = 400,000,
Mach 0.9 isothermal jets using 12.5 and 16.6 million grid points (2002, 2003)
• We studied a Mach 0.9 turbulent isothermal round jet at a Reynolds number of 100,000
• 12 million grid points used in our LES
Computation Details• Physical domain length of 60ro in streamwise
direction
• Domain width and height are 40ro
• 470x160x160 (12 million) grid points• Coarsest grid resolution: 170 times the local
Kolmogorov length scale• One month of run time on an IBM-SP using 160
processors to run 170,000 time steps• Can do the same simulation on the Compaq
Alphaserver Cluster at Pittsburgh Supercomputing Center in 10 days
x / ro
y/r
o
0 10 20 30 40 50 60 70-20
-10
0
10
20
30
40
z / ro
y/r
0
-20 -10 0 10 20-20
-15
-10
-5
0
5
10
15
20
x = 5ro
z / ro
y/r
0
-20 -10 0 10 20-20
-15
-10
-5
0
5
10
15
20
x = 15ro
z / ro
y/r
0
-20 -10 0 10 20-20
-15
-10
-5
0
5
10
15
20
x = 35ro
Mean Flow Results
• Our mean flow results are compared with: Experiments of Zaman for initially
compressible jets (1998) Experiment of Hussein et al. (1994)
Incompressible round jet at ReD = 95,500
Experiment of Panchapakesan et al. (1993) Incompressible round jet at ReD = 11,000
x / Dj
Uj/U
c(x)
0 10 20 300
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
slope = 0.161
From Zaman' sexperiments (1998):slope 0.155 for Mj = 0.9
Jet Mean Centerline Velocity Decay
x / Dj
Q(x
)/Q
e
10 15 20 25 304
5
6
7
8
9
10
11
slope = 0.267
From Zaman' sexperiments (1998):slope 0.26 for Mj = 0.9
Streamwise Mass Flux
slope = A = 0.092
experimental valuesof A : 0.086 - 0.096
x / ro
r 1/2(
x)/r
o
0 5 10 15 20 25 30 35 40 45 50 55 600
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
Jet Half-Velocity Radius Growth
r / r1/2
u/U
c
0 0.5 1 1.5 2 2.50
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
x = 45ro
x = 50ro
x = 55ro
exp. data of Hussein et. al.exp. data of Panchapakesan et. al.
Mean Streamwise Velocity Profiles
r / r1/2
rx
0 0.5 1 1.5 2 2.50
0.005
0.01
0.015
0.02
0.025
x = 45ro
x = 50ro
x = 55ro
exp. data of Hussein et. al.exp. data of Panchapakesan et. al.
rx = vx' vr' / Uc2
Reynolds Shear Stress Profiles
k1
Eu(1
)(k
1)
5 10 15 2010-7
10-6
10-5
10-4
10-3
10-2
10-1
100
k1-5/3
Grid cutoff
One-dimensional spectrum Eu(1) (k1) of vx'
at x = 20ro on the jet centerline
Jet Aeroacoustics
• Noise sources located at the end of potential core• Far field noise is estimated by coupling near field
LES data with the Ffowcs Williams–Hawkings (FWH) method
• Overall sound pressure level values are computed along an arc located at 60ro from the jet nozzle
• Cut-off Strouhal number based on grid resolution is around 1.0
X
Y
Z
Control Surface
Control Surface
Jet Flow
x = 35 ro x = 45 ro x = 60 ro
30 ro
x / ro
y/r
o
0 10 20-5
0
5
10
15
R
• OASPL results are compared with: Experiment of Mollo-Christensen et al. (1964)
Mach 0.9 round jet at ReD = 540,000 (cold jet)
Experiment of Lush (1971)
Mach 0.88 round jet at ReD = 500,000 (cold jet)
Experiment of Stromberg et al. (1980)
Mach 0.9 round jet at ReD =3,600 (cold jet)
SAE ARP 876C database
Jet Aeroacoustics (continued)
(deg)
OA
SPL
(dB
)
10 20 30 40 50 60 70 80 90 100 110 120100
102
104
106
108
110
112
114
116
118
120
LES + FWH (isothermal jet)SAE ARP 876C predictionexp. of Mollo-Christensen et al. (cold jet)exp. of Lush (cold jet)exp. of Stromberg et al. (cold jet)
St = f Dj / Uj
SPL
(dB
/St)
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.490
100
110
120
130
Our spectrum at x = 29ro and r = 12ro
Bogey and Bailly' s spectrum at x = 29ro and r = 12ro
St = f Dj / Uj
SPL
(dB
/St)
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.490
100
110
120
130 Our spectrum at x = 11ro and r = 15ro
Bogey and Bailly' s spectrum at x = 11ro and r = 15ro
Conclusions
• Localized dynamic SGS model stable and robust for the jet flows we are studying
• Very good comparison of mean flow results with experiments
• Aeroacoustics results are encouraging
• Valuable evidence towards the full validation of our CAA methodology has been obtained
Near Future Work
• Simulate Bogey and Bailly’s ReD = 400,000 jet test case using 16 million grid points 100,000 time steps to run About 150 hours of run time on the
Pittsburgh cluster using 200 processors
• Compare results with those of Bogey and Bailly to fully validate CAA methodology
• Do a more detailed study of surface integral acoustics methods
Can a realistic LES be done for ReD = 1,000,000 ?
• Assuming 50 million grid points provide sufficient resolution:
• 200,000 time steps to run
• 30 days of computing time on the Pittsburgh cluster using 256 processors
• Only 3 days on a near-future computer that is 10 times faster than the Pittsburgh cluster
Future Work
• Extend methodology to handle:
– Noise from unresolved scales
– Supersonic flow
– Solid boundaries (lips)
– Complicated (mixer) geometries
multi-block code
RANS for Forced Mixers
Objective
• Use RANS to study flow characteristics of various flow shapes
What is a Lobe Mixer?
Internally Forced Mixed Jet
Bypass Flow
Mixer
Core Flow
Nozzle
Tail Cone
Exhaust Flow
Exhaust / Ambient Mixing Layer
Lobed Mixer Mixing Layer
Forced Mixer
H
Lobe Penetration (Lobe Height)
H:
3-D Mesh
WIND Code options
• 2nd order upwind scheme• 1.7 million/7 million grid points• 8-16 zones• 8-16 LINUX processors• Spalart-Allmaras/ SST turbulence model• Wall functions
Grid Dependence
Density Contours1.7 million grid points
Density Contours7 million grid points
Grid Dependence
1.7 million grid points 7 million grid points
Density
VorticityMagnitude
Spalart-Allmaras and Menter SST Turbulence Models
Spalart-Allmaras
Menter SST
Spalart-Allmaras and and Menter SST at Nozzle Exit Plane
Spalart SST
Density
VorticityMagnitude
Mean Axial Velocity at x = 2.88”(High Penetration)
¼ Scale Spalartat x = 2.88/4”
experiment Spalart Allmaras
Mean Axial Velocity at x = 2.88”(High Penetration)
¼ Scale Menter SSTat x = 2.88/4”
experiment Menter SST
Spalart-Allmaras vs. Menter SST
• The Spalart-Allmaras model appears to be less dissipative. The vortex structure is sharper and the vorticity magnitude is higher at the nozzle exit.
• The Menter SST model appears to match experiments better, but the experimental grid is rather coarse and some of the finer flow structure may have been effectively filtered out.
• Still unclear which model is superior. No need to make a firm decision until several additional geometries are obtained.
Geometry at Mixer ExitLow Penetration Mid Penetration High Penetration
DENSITY CONTOURS (¼ Scale)
Low Penetration
Mid Penetration
Vorticity Magnitude at Nozzle Exit(¼ Scale Geometry)
Low Penetration Mid Penetration High Penetration
Turbulent Kinetic Energy at Nozzle Exit(¼ Scale Geometry)
Low Penetration Mid Penetration High Penetration
Preliminary Conclusions
• 1.7 million grid is adequate
• Further work is needed comparing the turbulence models and results for different penetration lengths
Future Work
• Analyze the flow fields and compare to experimental acoustic and flow-field data for additional mixer geometries.
• Further compare the two turbulence models.
• If possible, develop qualitative relationship between mean flow characteristics and acoustic performance.
Implementing RANS Inflow Boundary Conditions for 3-D
LES Jet Aeroacoustics
Objectives
• Implement RANS solution and onto 3-D LES inflow BCs as initial conditions.
• Investigate the effect of RANS inflow conditions on:– Reynolds Stresses– Far-field sound generated
Implementation Method
• RANS grid too fine for LES grid to match.
• Since RANS grid has high resolution, linear interpolation will be used.
LES
RANS
Issues and Challenges
• Accurate resolution of outgoing vortex with LES grid.
• Accurate resolution of shear layer near nozzle lip.
• May need to use an intermediate Reynolds number eg. Re = 400,000
Final Conclusion
• Methodologies (LES, RANS, coupling) are being developed to study noise from forced mixers