Research into large-eddy simulation (LES) for application to jet noise is described. The LES efforts include in-house code development and application at NASA Glenn along with NASA Research Announcement sponsored work at Stanford University and Florida State University. Details of the computational methods used and sample results for jet flows are provided

DeBonis, James R.

NASA Technical Reports Server

NASA’s Large-Eddy Simulation Research for Jet Noise 
Applications 
Research into large-eddy simulation (LES) for application to jet noise is described.  
The LES efforts include in-house code development and application at NASA Glenn 
along with NASA Research Announcement sponsored work at Stanford University and 
Florida State University.  Details of the computational methods used and sample 
results for jet flows are provided. 
https://ntrs.nasa.gov/search.jsp?R=20110011996 2019-08-30T15:43:52+00:00Z
1 
National Aeronautics and Space Administration 
www.nasa.gov 
NASAʼs Large-Eddy Simulation Research  
for Jet Noise Applications
2009 Annual Meeting 
September 29-October 1, 2009 
Jim DeBonis 
Inlet and Nozzle Branch 
Glenn Research Center 
NASAʼs LES Research for Jet Noise
•  In-house
–  WRLES code development
–  Jet noise applications
•  NRA sponsored research
–  Prediction and Modeling of Jet Noise Using Large-Eddy Simulation
•  Stanford University
•  Sanjiva Lele & Parviz Moin, PIs
•  Supersonics Project
–  High-Fidelity Jet Noise Simulations
•  Florida State University
•  M. Youssuf Hussaini, PI
•  Subsonics Fixed Wing Project
WaveResolvingLES
•  Time advancement
–  Low dispersion Runge-Kutta time stepping 
–  1st - 4th order
•  Spatial discretization
–  Explicit central differencing
–  Standard schemes 2nd – 12th order
–  DRP schemes
•  Tam
•  Bogey & Bailly 9, 11 and 13 point schemes
•  Filtering
–  Carpenter & Kennedy 2nd – 12th order
–  Bogey and Bailly 9, 11 and 13 point filters
–  Shock capturing filters
•  Hybrid MPI/OpenMP parallel
•  Generalized curvilinear coordinates
Turbulent Jet Flow
•  2-inch Acoustic Reference Nozzle
•  Tested at the NASA Glenn Small Hot Acoustic Rig (SHAR)
•  Particle Image Velocimetry (PIV) measurements (Bridges & Wernet)
•  Flow Conditions
–  Exit Mach number 0.9
–  Cold flow
–  Quiescent freestream
–  Jet Reynolds number ~ 2 million 
Computational Grid
Grid Interior of Nozzle
Exterior 
of Nozzle Nozzle Plume Total
Baseline 45 x 55 x 102 45 x 65 x 102 196 x 148 x 102 3,509,616
Refined 45 x 55 x 132 45 x 65 x 132 294 x 148 x 132 6,456,384
Computational Approach
•  Implicit LES 
–  No sub-grid model
–  Dissipation from filter used to dissipate large-scales
•  Laminar nozzle boundary layers 
–  Accelerating flow reduces turbulence at nozzle exit
–  Transition occurs quickly in the jet mixing layer
•  Simulation Reynolds number, 50,000
•  Solution processing
–  Entire solution saved every 2•10-5 seconds
–  50kHz sampling rate
–  2,048 solutions used in post processing
Axial Velocity Animation
Centerline Velocity
Centerline Turbulent Intensities
Axial turbulent intensity Radial turbulent intensity
Turbulent Spectra - κDj
Baseline grid Refined grid
Spectra - Grid Comparison
x/Dj = 4 x/Dj = 7
•  Stanford University
–  Simon Mendez, Post Doctoral 
Researcher
–  Sanjiva Lele & Parviz Moin, 
Principal Investigators
•  Unstructured LES
–  Non-dissipative schemes
–  Shock capturing
•  Potential benefits
–  Complex Geometry
–  Gain knowledge of unstructured 
methods
density
Vorticity magnitude
Prediction and Modeling of Jet Noise 
Using Large-Eddy Simulation
Approach
•  CDP code
–  2nd order energy conserving finite volume
–  Hybrid explicit/implicit time stepping
•  Unstructured grids
•  Dynamic Smagorinsky sub-grid model
•  Cases
–  Subsonic, M = 0.95
–  Supersonic, M = 1.4
•  Cold
•  Hot
•  Farfield noise
–  Ffwocs-Williams Hawkings solver
Comparison to Experiment
Viswanathan et al. – LES calculation
AIAA J. 45(8) 2007
rm
s(
u)
/U
j
rm
s(
v)
/U
j
Subsonic Jet
Space-Time Correlations, x/D = 7.8
CDP Bridges and Wernet 2007
Subsonic Jet
Farfield Noise, FWH Solver
Closed Open
Subsonic Jet
Comp. 
Expt. 
Farfield Sound (100D), OASPL
Unheated Heated
Supersonic Jets
High-Fidelity Jet Noise Simulations
•  Florida State University
–  Ali Uzun, Post Doctoral Researcher
–  M. Yousuff Hussaini, Principal 
Investigator
•  Very high resolution LES
–  300 – 400 million grid points
–  High resolution numerical schemes
•  Potential benefits
–  Very high accuracy
–  Excellent database for jet noise 
modeling
Approach
•  Numerical Scheme
–  Implicit time advancement
–  Fourth-order compact spatial differencing
•  Overset grids
•  Implicit LES – no sub-grid model
•  Turbulent nozzle boundary layers using a recycling technique
•  Cases
–  Chevron Nozzle
–  Round Jet
•  Farfield noise
–  Ffwocs-Williams Hawkings solver
Axial Velocity
x/Lcore = 1.03 Note: Lcore scaling corrects for disparity between CFD and expt. 
Chevron Nozzle
Turbulent Kinetic Energy
x/Lcore = 1.03 Note: Lcore scaling corrects for disparity between CFD and expt. 
Chevron Nozzle
Nozzle Boundary Layers
Axial Velocity Contours
Round Jet
Centerline Velocity Profiles
Round Jet
Axial Turbulent Intensity
Round Jet
Conclusions 
•  LES methods are now doing a good job of reproducing simple jet 
flowfields
•  Further research needed for…
–  Complex flows
•  Complex geometries: chevrons, mixer/ejectors, etc.
•  Flows with shocks
–  Computing farfield noise
•  FWH closure methods
•  Exploring alternate propagation techniques
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NASA's Large-Eddy Simulation Research for Jet Noise Applications

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