st04 diffuser 12531jos1
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Stanford 3D Diffuser ST04
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Overview
Goals of the testcase: Corner flow separation often over-
predicted by Eddy Viscosity Models
Question: Can EARSM/RSM predict such flows
s stematicall better than Edd Viscosit
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 2
models? Are all EARSM/RSM about equal or are there
large differences in behavior?
What are the reasons for the differences?
Partners
ANS, NTS, NUM,TUD, UniMan
SST
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Modeling challenges
Flow in a rectangular duct is not unidirectional
secondary flow (Prandtls secondary flow of second kind)
due to anisotropic normal stresses Secondary motion generates vortices in square ducts
which drive momentum into the corner
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 5
stronger pressure gradients than without such secondary features
RANS
LEVM cannot account for secondary flow
properly calibrated RSM should performconsistently better
Turbulence resolving methods
correct capturing of anisotropic turbulence is necessary
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RANS computations
ANSYS
The S-BSL-EARSM using the WJ stress-strain relation has been
optimized and documented (Menter et al, 2009, also report available). NUMECA
S-BSL-EARSM model from ANSYS
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 6
- - -Hellsten, 2005 (WJ-EARSM)
UniMan
Elliptic-Blending RSM (EBRSM)
NTS S-BSL-EARSM model from ANSYS
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RANS Computational
Grids ANSYS
Diffuser 1 and 2: 14591121 NUMECA
Diffuser 1: 14591121
Medium mesh for Diffuser 1:used by ANSYS and NUMECA
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 7
n an Diffuser 1: 21260180
Diffuser 2: 2206090
NTS
Diffuser 1:137 x 77 x 135
NTS RANS mesh for Diffuser 1:
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Inflow conditions for
RANS computations
Experiment Fully developed flow, enabled by a
development channel being 62.9 channelheights long
ANSYS, UniMan
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 8
Fully developed flow from precursorsimulations of a periodic 2D duct using thesame model as for the entire diffuser
NUMECA Developed flow, enabled by the upstream
development channel being 100 channelheights long
Inlet section
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FVM Numerics for RANS ANSYS
Momentum eqs: bounded second order upwind scheme Turbulence eqs: first order upwind
NUMECA
Momentum e s: Jameson central scheme with scalar dissi ation
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 9
Turbulence eqs: second order upwind UniMan
Momentum eqs: second order centered scheme
Turbulence eqs: first order upwind
UniMan
Momentum eqs: fourth (adv.) second (diff.) order centered scheme
Turbulence eqs: ??th order upwind..??
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Locations for cross-
comparisonsPlanes for streamwise velocityand Urms cross-comparisons
Line for Cp cross-comparisons
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 10
58
1215
X/H = 2H
Cp line
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0.5
0.6
0.7
Pressure coefficient
Data for Diffuser 1
In general, all RSM models perform better than LEVM (SST)
Among all models, EBRSM model of UniMan is superior to all other models tested
Reasons for differences can be seen from the streamwise velocity field (next slide)
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 11
X/L
Cp
0 0.5 1 1.5 2-0.2
-0.1
0
0.1
0.2
0.3
0.4
Experiment
S-BSL-EARSM ANSS-BSL-EARSM NTS
S-BSL-EARSM NUMWJ-EARSM NUMEBRSM UniMan
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Streamwise velocity,
Diffuser 1: RANS Results of S-BSL-
EARSM obtained atANSYS and NUMECA
are quite similar
S-BSL-EARSM givestoo strong reverse flow
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 12
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and overestimates thesize of the separationzone
EBRSM, on the contrary,
slightly underestimatesthe size of reverse flowzone and also values ofmaximum streamwise
velocities
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Velocity fluctuations,
Diffuser 1: RANS All the tested EARSM
are capable of
reproducing velocityfluctuations(Urms) quite well
Results of S-BSL-
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 13
Urms/ Ubulk
100
o a ne aANSYS and NUMECAare again very similar
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Turbulence-resolving
computations: TUD,UniMan UniMan: RANS / LES
Two-Velocity hybrid RANS / LES scheme with the underlyingv2f RANS turbulence model
Inflow conditions: fluctuating flow from Synthetic Eddy Method ofJarrin et al. The methods generates synthetic 3D eddies rescaledwith turbulent statistics taken from a precursor EBRSM calculation
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 17
o a uc w ose mens ons ma c e mens ons o e n e
TUD: RANS / LES
LES / RANS formulation represents a zonal, two-layer hybridapproach with a RANS model for near-wall and LES in the remainder
Inflow conditions: precursor simulation of the fully-developed flow TUD: SAS-RSM
SAS-RSM
Inflow conditions: same as for RANS / LES but at the inlet plane
x / H = -0.6, to overcome the problem of decay of fluctuations
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Grids for TUD and UniMantransient simulations
UniMan Diffuser 1: 21260180
Diffuser 2: 22060180
Mesh overview
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 18
Diffuser 1 only
RANS/LES: 22462134
SAS-RSM: 15062134
NTS...
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Turbulence-resolving
computations: NTS NTS: SST-based IDDES
Inflow turbulent content
NTS synthetic turbulence based on SST RANS solution
WJ-BSL-EARSM RANS solution
Recycling (periodic conditions) in an additional upstream
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 19
rectangular channel section with the length L=6H Computational Grids
With synthetic inflow: Domain -3 < x < 55; Grid: 414 x 77 x 135 (~4.3M)
With recycling: Domain: - 9 < x < 55; Grid: 499 x 77 x 135 (~ 5.2 M)
ATAAC, page 19
Sponge layer
Recycling
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Turbulence-resolving
computations: ANSYS ANSYS:
SST-based IDDES and (algebraic) WMLES
Inflow: Recycling (periodic conditions) in an additional upstreamrectan ular channel section with the len th L=6H
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 20
Computational Grid Domain: - 9 < x < 45; Grid: 450 x 77 x 135 (~ 4.7 M)
ATAAC, page 20
Recycling
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Numerics for transient
simulations II NTS
Incompressible branch of the NTS code (Rogers & Kwak scheme)
4th order centered approximation of inviscid fluxes
2nd order centered approximation for viscous fluxes
Implicit, 2nd order (three-layer) time-integration
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 22
ANSYS
FLUENT, unstructured collocated finite volumes codewith cell-centered variables arrangement
SIMPLEC algorithm
Momentum eqs: second order centered scheme
Turbulence eqs: second order upwind
Implicit, 2nd order (three-layer) time-integration
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Pressure coefficient
TUD, UniManData for Diffuser 1
0.5
0.6
0.7
TUD & UniMAN HybridRANS/LES methods predictthe pressure coefficientvery well
SAS-RSM model somewhat
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 23
X/L
Cp
0 0.5 1 1.5 2-0.2
-0.1
0
0.1
0.2
0.3
.
Experiment
TUD RANS-LESTUD R SM-SAS
UniMan RANS-LES
un erest mates Cp.
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TUD SAS-RSM
SAS-RSM somewhatunderpredicts the size of theseparation zone, as well asmaximal values of streamwisevelocities and Urms in the
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 25
of the diffuser
A spotty behaviour of Urms isdue to a small averaging time
(7 through-flow times)
Urms/Ubulk
100
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0.4
0.5
0.6
0.7
Pressure coefficient
NTS (IDDES)Data for Diffuser 1 NTS results:
Best predictions: IDDES with
recycling (etalon no syntheticturbulence) and IDDES with inflowsynthetic turbulence based onS-BSL-EARSM RANS solution
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 26
X/L
Cp
0 0.5 1 1.5 2-0.2
-0.1
0
0.1
0.2
0.3
ExperimentIDDES, recyclingIDDES, synth. turb., SSTIDDES, synth. turb., EARSM
Somewhat worse predictions: IDDES
with synthetic turbulence based onSST RANS (u2=v2 =w2)
IDDES results most probablymay be improved by shifting theinflow farther upstream (toprovide a space for establishingnormal stresses anisotropy)
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NTS IDDES UIDDES
(Synth. EARSM)IDDES
(Recycling)IDDES
(Synth. SST)Experiment Same rating of theapproaches as thatbased on Cpdistributions:
Best predictions:IDDES withrecycling andIDDES with inflow
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 28
synthetic turbulencebased onS-BSL-EARSM
RANS solution
Somewhat worse:IDDES withsynthetic turbulencebased on SST RANS(u2=v2 =w2)
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NTS IDDES Urms/UbulkIDDES
(Synth. EARSM)IDDES
(Recycling)IDDES
(Synth. SST)Experiment
Same rating ofthe approaches asthat based on Cpdistributions (cf. prev. slide)
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 29
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Pressure coefficient:
ANSYS IDDES and WMLESData for Diffuser 1 ANSYS results:
IDDES and (algebraic) WMLES
with recycling overestimate Cpdownstream from X/L = 0.5
Grid sensitivity has to be checked simulations on a finer mesh are in
0.5
0.6
0.7
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 30
progress
Same mesh as used by NTS,but NTS code has higher-orderdiscretisation of advective fluxes
X/L
Cp
0 0.5 1 1.5 2-0.2
-0.1
0
0.1
0.2
0.3
0.4
ExperimentIDDESWMLES
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ANSYS IDDESIDDES
(Recycling)IDDES
(Recycling)Experiment Experiment
U/UbulkUrms/Ubulk
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ANSYS WMLESWMLES
(Recycling)WMLES
(Recycling)Experiment Experiment
U/UbulkUrms/Ubulk
ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 32
C l i
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Conclusions on
transient simulations Good results were obtained by both RANS/LES hybrid computational
models (from TUD and UniMan) with respect to the characteristics of theduct flow expanding into a diffuser section, the consequent separationflow region (onset, shape and size), the mean velocity field andassociated integral parameters (pressure distribution), as well as theturbulence quantities.
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ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 33
location of the inlet plane upstream of the diffuser (decay of resolvedturbulence, SAS reverting gradually into RANS mode)
SST-based IDDES with inflow turbulent content created with the use ofsynthetic turbulence generator developed by NTS and with the use ofturbulence recycling in upstream straight channel section is shown to
be capable of correctly reproducing major features of the mean flow andturbulence statistics
Synthetic turbulence created on the basis of EARSM RANS solutiontangibly improves accuracy of the simulation compared with the case
when the synthetic turbulence is created on the basis of the linear SSTmodel
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