Actran-2012用户大会-Daimler-气动噪声经典案例分析
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DES simulation with StarCCM+ (V6.05) • Turbulence model: IDDES Menter SST • Temporal : 2nd order / Convection: Hybrid-BCD Meshing • Computational domain: 6 m x 4 m x 0.3 m (x, y, z) • Step by step refinement until 0.78 mm in the finest region • Wall resolution y+ < 1 and 3 at the airfoil and cylinder respectively • ~ 95 million cells
x = 0,234 m
Inlet boundary conditions • T = 293 K • P = 899 mbar • Ma = 0.2098 Re = 44 000 (Cylinder) Turbulent intensity = 0.78 % • Simulation time • T = 0.2 s with ∆t = 1*10-5 s
StarCCM+ ICFD (Mapping) ICFD (DFT) Actran AeroAcoustics
Source term data • 3.3 GB per time step 66 TB Reduction of source term data with mapping-on-the-fly routine 8
Hybrid CAA
CFD Mapper • Monitors the CFD output • Starts mapping (ICFD) and monitoring (ActranVi) process if enough data is available • Deletes CFD output if mapping was successful Loops until specified amount of time steps is mapped • CFD Mapper - Settings • actranpy.sh –u CFDmapper … • Processors, memory, batch size, directories, files, …
A hybrid CAA simulation is performed using a DES in StarCCM+ (calculation of acoustic sources) and Actran AeroAcoustics (FEM Lighthill implementation) for source term mapping and acoustic propagation
(
(
))
Export settings • Output quantities: velocity vector and density • ∆texport = ∆tCFD = 1*10-5 s (@5kHz: 20 time steps per period) Texport = 0.2 s (Averaging: 5 x 0.04 s) --> min. 25 Hz with a frequency resolution of 25 Hz • Mapping
y = 0,08 m
∆x = 0,78 mm
Mesh resolution
5
Hydrodynamics
a) b)
Mean
and RMS
Velocity
a)
b)
b)
Experiment [1] LES Berland [2]
• • •
Good agreement of StarCCM+ results at the cylinder Turbulent fluctuations are only resolved in the LES part (RANS TKE) Discrepancies between StarCCM+ and experimental data are comparable or smaller in respect to other CFD simulations ([2],[3])
2
Content
– Motivation – Rod-Airfoil experimental/simulation setup – Hydrodynamic results – Hybrid CAA approach with StarCCM+/Actran AeroAcoustics
• Methodology • Mapping-on-the-fly • Computational effort
?
– Acoustics
• Acoustic model • Acoustic sources • Acoustic far field results
– Summary/Conclusions
3
Experiment: Rod-Airfoil [1]
Experimental setup • • • • Cylinder: ∅ = 10 mm Airfoil: NACA 0012, c = 100 mm Span: 300 mm Far field measurements: R = 1.85 m
∆tCFD Tmesh Tprojection ∆tmap
75 s 600 s 1860 s 200 s
Processor Batch size RAM usage Data storage
4 100 240 GB 330 GB
9
Acoustic Model
Infinite elements
• • •
Actran Users’ Conference 2012
October 3-4, 2012 - Brussels, Belgium
Prediction of far field noise on a rod-airfoil configuration with Actran AeroAcoustics
FEM region
Acoustic sources @ 1375Hz
Experimental data • • • Geometric and hydrodynamic boundary conditions Velocity profiles and spectra Wall pressure and far field spectra
4
Simulation Setup
•
Since Direct Noise Calculations need highly accurate spectral-like numerical methods a coupled DES-CAA simulation seems to be most promising: • LES in highly resolved regions computes the acoustic sources • RANS reduces computational effort (memory/time) • Acoustic calculation can be done separately on coarser acoustic meshes with spectral-like acoustic solvers – Disadvantage: Huge amount of source term data for large engineering applications New mapping-on-the-fly routine to avoid this lack
ICFD ActranVI Settings StarCCM+
Temporary data storage
CFD Mapper
Python script
CFD Mapper – Python script Content of ICFD.edat and ActranVI.sess file • StarCCM+ ICFD - Balance Depending on RAM/hard disk capacity • and the required process times the number of used processors (time parallelism) and the batch size can be estimated The amount of hard disk storage could be decreased significantly (66TB 0.66TB), further potential exists!
Hybrid CAA
Source mapping CFD mesh Unsteady CFD results Acoustic mesh Acoustic sources
Theory Lighthill analogy: •
∂ 2Tij ∂2ρ′ ∂2 2 2 − c0 ∆ρ ′ = = ρ ui u j − τ ij + δ ij p′ − c 0 ρ′ 2 ∂t ∂xi ∂x j ∂xi ∂x j
6
Hydrodynamics
Velocity spectra at x/c = 0.25
x = 25mm / y = 30mm
DES Upwind Blending Factor
• •
Good agreement with experimental data Slightly lower level at y = 30 mm caused by the transition between LES and RANS at this distance 7
Acoustic mesh should resolve up to 5kHz Acoustic wave length @ 5kHz : 0.068m 4 quadratic elements / λ: Δx = 0.017m
Mapping region
Δx = 17mm
•
Slight mesh refinement at cylinder boundary and leading edge to capture the boundary curvature Acoustic model contains 588 000 cells 1 232kdof have to be computed with an IFE interpolation order of 10
Modal duct Rigid walls
• •
Baidu Nhomakorabea
11
Acoustic Sources
Two different source mechanisms can be observed: • Cylinder wake (especially at the vortex shedding frequency) • Cylinder wake – leading edge interaction
Dipl.-Ing. Alexander Schell Daimler AG, Germany
Motivation
• • Wind noise is the dominant cabin noise above 100 – 120 mph To optimize wind noise at an early development stage theoretically reasonable and validated simulation methods for near field acoustics have to be found • 1st step: Far field validation No hydrodynamic pressure/structural coupling
x = 0,234 m
Inlet boundary conditions • T = 293 K • P = 899 mbar • Ma = 0.2098 Re = 44 000 (Cylinder) Turbulent intensity = 0.78 % • Simulation time • T = 0.2 s with ∆t = 1*10-5 s
StarCCM+ ICFD (Mapping) ICFD (DFT) Actran AeroAcoustics
Source term data • 3.3 GB per time step 66 TB Reduction of source term data with mapping-on-the-fly routine 8
Hybrid CAA
CFD Mapper • Monitors the CFD output • Starts mapping (ICFD) and monitoring (ActranVi) process if enough data is available • Deletes CFD output if mapping was successful Loops until specified amount of time steps is mapped • CFD Mapper - Settings • actranpy.sh –u CFDmapper … • Processors, memory, batch size, directories, files, …
A hybrid CAA simulation is performed using a DES in StarCCM+ (calculation of acoustic sources) and Actran AeroAcoustics (FEM Lighthill implementation) for source term mapping and acoustic propagation
(
(
))
Export settings • Output quantities: velocity vector and density • ∆texport = ∆tCFD = 1*10-5 s (@5kHz: 20 time steps per period) Texport = 0.2 s (Averaging: 5 x 0.04 s) --> min. 25 Hz with a frequency resolution of 25 Hz • Mapping
y = 0,08 m
∆x = 0,78 mm
Mesh resolution
5
Hydrodynamics
a) b)
Mean
and RMS
Velocity
a)
b)
b)
Experiment [1] LES Berland [2]
• • •
Good agreement of StarCCM+ results at the cylinder Turbulent fluctuations are only resolved in the LES part (RANS TKE) Discrepancies between StarCCM+ and experimental data are comparable or smaller in respect to other CFD simulations ([2],[3])
2
Content
– Motivation – Rod-Airfoil experimental/simulation setup – Hydrodynamic results – Hybrid CAA approach with StarCCM+/Actran AeroAcoustics
• Methodology • Mapping-on-the-fly • Computational effort
?
– Acoustics
• Acoustic model • Acoustic sources • Acoustic far field results
– Summary/Conclusions
3
Experiment: Rod-Airfoil [1]
Experimental setup • • • • Cylinder: ∅ = 10 mm Airfoil: NACA 0012, c = 100 mm Span: 300 mm Far field measurements: R = 1.85 m
∆tCFD Tmesh Tprojection ∆tmap
75 s 600 s 1860 s 200 s
Processor Batch size RAM usage Data storage
4 100 240 GB 330 GB
9
Acoustic Model
Infinite elements
• • •
Actran Users’ Conference 2012
October 3-4, 2012 - Brussels, Belgium
Prediction of far field noise on a rod-airfoil configuration with Actran AeroAcoustics
FEM region
Acoustic sources @ 1375Hz
Experimental data • • • Geometric and hydrodynamic boundary conditions Velocity profiles and spectra Wall pressure and far field spectra
4
Simulation Setup
•
Since Direct Noise Calculations need highly accurate spectral-like numerical methods a coupled DES-CAA simulation seems to be most promising: • LES in highly resolved regions computes the acoustic sources • RANS reduces computational effort (memory/time) • Acoustic calculation can be done separately on coarser acoustic meshes with spectral-like acoustic solvers – Disadvantage: Huge amount of source term data for large engineering applications New mapping-on-the-fly routine to avoid this lack
ICFD ActranVI Settings StarCCM+
Temporary data storage
CFD Mapper
Python script
CFD Mapper – Python script Content of ICFD.edat and ActranVI.sess file • StarCCM+ ICFD - Balance Depending on RAM/hard disk capacity • and the required process times the number of used processors (time parallelism) and the batch size can be estimated The amount of hard disk storage could be decreased significantly (66TB 0.66TB), further potential exists!
Hybrid CAA
Source mapping CFD mesh Unsteady CFD results Acoustic mesh Acoustic sources
Theory Lighthill analogy: •
∂ 2Tij ∂2ρ′ ∂2 2 2 − c0 ∆ρ ′ = = ρ ui u j − τ ij + δ ij p′ − c 0 ρ′ 2 ∂t ∂xi ∂x j ∂xi ∂x j
6
Hydrodynamics
Velocity spectra at x/c = 0.25
x = 25mm / y = 30mm
DES Upwind Blending Factor
• •
Good agreement with experimental data Slightly lower level at y = 30 mm caused by the transition between LES and RANS at this distance 7
Acoustic mesh should resolve up to 5kHz Acoustic wave length @ 5kHz : 0.068m 4 quadratic elements / λ: Δx = 0.017m
Mapping region
Δx = 17mm
•
Slight mesh refinement at cylinder boundary and leading edge to capture the boundary curvature Acoustic model contains 588 000 cells 1 232kdof have to be computed with an IFE interpolation order of 10
Modal duct Rigid walls
• •
Baidu Nhomakorabea
11
Acoustic Sources
Two different source mechanisms can be observed: • Cylinder wake (especially at the vortex shedding frequency) • Cylinder wake – leading edge interaction
Dipl.-Ing. Alexander Schell Daimler AG, Germany
Motivation
• • Wind noise is the dominant cabin noise above 100 – 120 mph To optimize wind noise at an early development stage theoretically reasonable and validated simulation methods for near field acoustics have to be found • 1st step: Far field validation No hydrodynamic pressure/structural coupling