Transcript ATAAC Template - University of Manchester

Stanford 3D Diffuser – ST04
Overview
• Goals of the testcase:
– Corner flow separation often overpredicted by Eddy Viscosity Models
– Question:
• Can EARSM/RSM predict such flows
systematically better than Eddy Viscosity
models?
• Are all EARSM/RSM about equal or are there
large differences in behavior?
• What are the reasons for the differences?
•
SST
Partners
– ANS, NTS, NUM,TUD, UniMan, ONERA,
RRD,TUB
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 2
Flow Description
Diffuser geometries
Schematic of Flow
Separation Zone
• Major flow parameters
– Incompressible fluid
– Re = 10,000 based on inlet channel height and inlet bulk
velocity
– Fully developed flow at diffuser inlet
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 3
Experiment
Flow system schematic
3D Magnetic Resonance Velocimetry (MRV)
Measured Velocity
• Available Data
– Three velocity components (Diffuser 1 and 2)
– Fluctuations of streamwise component, Urms (Diffuser 1)
– Pressure coefficient distribution (Diffuser 1)
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Modeling challenges
• Flow in a rectangular duct is not unidirectional
– secondary flow (Prandtl’s secondary flow of second kind)
due to anisotropic normal stresses
• Secondary motion generates vortices in square ducts
which drive momentum into the corner
– more momentum in the corner allows the flow to overcome
stronger pressure gradients than without such secondary features
• RANS
– LEVM cannot account for secondary flow
– properly calibrated RSM should perform
consistently better
• Turbulence resolving methods
– correct capturing of anisotropic turbulence is necessary
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 5
RANS computations
• ANSYS
– The BSL-EARSM using the WJ stress-strain relation has been
optimized and documented (report available).
• NUMECA
– WJ-BSL-EARSM model from ANSYS with some modifications of the
total Reynolds stress tensor
– High-Re Wallin-Johansson EARSM with k-omega model of Hellsten
• UniMan
– Elliptic-Blending RSM (EBRSM)
• NTS
– S-WJ-BSL-EARSM (partly shown)
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 6
RANS Computational
Grids
• ANSYS
– Diffuser 1 and 2: 145×91×121
Medium mesh for Diffuser 1:
used by ANSYS and NUMECA
• NUMECA
– Diffuser 1: 145×91×121
• UniMan
– Diffuser 1: 212×60×180
– Diffuser 2: 220×60×90
• NTS
– Diffuser 1:
137 x 77 x 135
NTS RANS mesh for Diffuser 1:
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 7
Inflow conditions for
RANS computations
• Experiment
– Fully developed flow, enabled by a
development channel being 62.9 channel
heights long
• ANSYS, UniMan
– Fully developed flow from precursor
simulations of a periodic “2D” duct using the
same model as for the entire diffuser
• NUMECA
– Developed flow, enabled by the upstream
development channel being 100 channel
heights long
Inlet section
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 8
FVM Numerics for RANS
• ANSYS
– Momentum eqs: bounded second order upwind scheme
– Turbulence eqs: first order upwind
• NUMECA
– Momentum eqs: Jameson central scheme with scalar dissipation
– 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..??
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 9
Locations for crosscomparisons
Line for Cp crosscomparisons
Planes for streamwise velocity
and Urms cross-comparisons
12
15
Cp line
8
5
X/H = 2
H
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 10
Pressure coefficient
• 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)
Data for Diffuser 1
0.7
0.6
0.5
0.4
Cp
0.3
0.2
Experiment
ANSYS BSL EARSM
NUMECA BSL EARSM
NUMECA WJ EARSM
UniMan EBRSM
NTS S-WJ-BSL-EARSM
0.1
0
-0.1
-0.2
0
0.5
1
1.5
2
X/L
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 11
Velocities at diagonals,
Diffuser 1
ANSYS BSL EARSM
NTS S-WJ-BSL-EARSM
1.4
1
0.015
0.004
0.01
0.002
0.005
v
0
0
0.6
0.4
0.2
0
0
0.5
1
1.5
z
2
2.5
3
3.5
-0.002
-0.005
-0.004
-0.01
-0.006
0
0.5
1
1.5
z
2
2.5
3
3.5
-0.015
0
1.4
0.06
0.04
1.2
0.05
0.02
0.04
1
v
0.6
0
0
1
1.5
z
2
2.5
3
3.5
-0.02
0
0.5
1
1.5
2
2.5
3
3.5
2
2.5
3
3.5
-0.06
-0.08
-0.01
0.5
z
-0.04
0
0.2
1.5
-0.02
0.02
0.01
0.4
1
w
0.8
0.5
0
0.03
u
X=0H
w
0.8
u
X = -3 H
1.2
0.006
0.5
1
1.5
z
2
2.5
3
3.5
-0.1
0
z
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 12
Streamwise velocity,
Diffuser 1: RANS
• Results of WJ-BSLEARSM obtained at
ANSYS and NUMECA
are quite similar
• WJ-BSL-EARSM gives
too strong reverse flow
in the top-right corner
and overestimates the
size of the separation
zone
• EBRSM, on the contrary,
slightly underestimates
the size of reverse flow
zone and also values of
maximum streamwise
velocities
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 13
Velocity fluctuations,
Diffuser 1: RANS
• All the tested EARSM
are capable of
reproducing velocity
fluctuations
(Urms) quite well
• Results of WJ-BSLEARSM obtained at
ANSYS and NUMECA
are again very similar
Urms / Ubulk  100
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 14
Streamwise velocity,
Diffuser 2
• Conclusions for the
Diffuser 2 are quite
similar to those for the
Diffuser 1
• Both WJ-BSL-EARSM
and EBRSM captures
the velocity field well
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 15
Conclusions on
RANS results
• Inclusion of the stress anisotropy leads to a drastic
improvement of the results for this case. The flow topology
matches much better the experimentally observed flow and
the wall pressure distribution improves significantly.
• The use of EARSM / RSM improves the results
systematically for both of the considered geometries.
• The Cp-distribution was best captured by the EBRSM of
UniMan. Not all details of velocity profiles matched by any
method (Relevance?).
• What is the reason for some EARSM / RSM being better than
others?
• Consistent inlet conditions required for simulations.
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 16
Turbulence-resolving
computations: TUD,UniMan
• UniMan: RANS / LES
– Two-Velocity hybrid RANS / LES scheme with the underlying
v2f RANS turbulence model
– Inflow conditions: fluctuating flow from Synthetic Eddy Method of
Jarrin et al. The methods generates synthetic 3D eddies rescaled
with turbulent statistics taken from a precursor EBRSM calculation
of a “2D” duct whose dimensions match the dimensions of the inlet
• TUD: RANS / LES
– LES / RANS formulation represents a zonal, two-layer hybrid
approach 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
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 17
Grids for TUD and UniMan
transient simulations
• UniMan
Mesh overview
– Diffuser 1: 212×60×180
– Diffuser 2: 220×60×180
• TUD
– Diffuser 1 only
– RANS/LES: 224×62×134
– SAS-RSM: 150×62×134
• NTS...
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 18
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
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)
Sponge layer
Recycling
ATAAC, page 19
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 19
Turbulence-resolving
computations: ANSYS
• ANSYS:
– SST-based IDDES and
– (algebraic) WMLES
– Inflow: “Recycling” (periodic conditions) in an additional upstream
rectangular channel section with the length L=6H
• Computational Grid
– Domain: - 9 < x < 45; Grid: 450 x 77 x 135 (~ 4.7 M)
Recycling
ATAAC, page 20
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 20
Numerics for transient
simulations I
• UniMan
– Code Saturne, unstructured collocated finite volumes code
– SIMPLEC algorithm
– Momentum eqs: second order centered scheme
– Turbulence eqs: first order upwind
• TUD
– In-house code FASTEST, finite volume method for block-structured, bodyfitted, non-orthogonal, hexahedral meshes
– SIMPLEC algorithm with a geometric multi-grid scheme
– Momentum eqs: second-order, central differencing scheme
– Turbulence eqs: ‘‘flux blending” technique with some upwinding
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 21
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
• ANSYS
– FLUENT, unstructured collocated finite volumes code
with cell-centered variables arrangement
– SIMPLEC algorithm
– Momentum eqs: second order centered scheme
– Turbulence eqs: second order upwind
– Implicit, 2nd order (three-layer) time-integration
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 22
Pressure coefficient
TUD, UniMan
Data for Diffuser 1
• TUD & UniMAN Hybrid
RANS/LES methods predict
the pressure coefficient
very well
• SAS-RSM model somewhat
underestimates Cp.
0.7
0.6
0.5
0.4
Cp
0.3
0.2
Experiment
TUD RANS-LES
TUD RSM-SAS
UniMan RANS-LES
0.1
0
-0.1
-0.2
0
0.5
1
1.5
2
X/L
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 23
UniMan RANS/LES
Diffuser 1
Diffuser 2
• Consistently with the adequate prediction of Cp value, the UniMan hybrid LES/RANS method
correctly reproduces the flow field pattern in both Diffusers.
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 24
TUD SAS-RSM
• SAS-RSM somewhat
underpredicts the size of
the separation zone, as
well as maximal values of
streamwise velocities and
Urms in the region close to
the end of the diffuser
• A “spotty” behaviour of Urms
is due to a small averaging
time
(7 through-flow times)
Urms/Ubulk100
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 25
Pressure coefficient
NTS (IDDES)
Data for Diffuser 1
0.7
0.6
0.5
0.4
0.3
Cp
• NTS results:
• Best predictions: IDDES with
recycling (“etalon” – no synthetic
turbulence) and IDDES with inflow
synthetic turbulence based on
WJ-BSL-EARSM RANS solution
• Somewhat worse predictions: IDDES
with synthetic turbulence based on
SST RANS (u’2=v’2 =w’2)
0.2
Experiment
IDDES, recycling
IDDES, synth. turb., SST
IDDES, synth. turb., EARSM
0.1
• IDDES results most probably
may be improved by shifting the
inflow farther upstream (to
provide a space for establishing
normal stresses anisotropy)
0
-0.1
-0.2
0
0.5
1
1.5
2
X/L
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 26
Velocities at diagonals,
NTS IDDES (??)
Recycling
Synth. turb, EARSM
1.4
1
0.004
0.01
0.002
0.005
v
w
0.8
0
0
0.6
0.4
0.2
0
0
0.5
1
1.5
z
2
2.5
3
3.5
-0.002
-0.005
-0.004
-0.01
-0.006
0
0.5
1
1.5
z
2
2.5
3
3.5
-0.015
0
1.4
0.06
0.04
1.2
0.05
0.02
0.04
1
v
0.6
0
0
1
1.5
z
2
2.5
3
3.5
-0.02
0
0.5
1
1.5
2
2.5
3
3.5
2
2.5
3
3.5
-0.06
-0.08
-0.01
0.5
z
-0.04
0
0.2
1.5
-0.02
0.02
0.01
0.4
1
w
0.8
0.5
0
0.03
u
X=0H
0.015
u
X = -3 H
1.2
0.006
0.5
1
1.5
z
2
2.5
3
3.5
-0.1
0
z
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 27
NTS IDDES – U
Experiment
IDDES
(Recycling)
IDDES
(Synth. EARSM)
IDDES
(Synth. SST)
• Same “rating” of the
approaches as that
based on Cp
distributions:
• Best predictions:
IDDES with
recycling and
IDDES with inflow
synthetic turbulence
based on
WJ-BSL-EARSM
RANS solution
• Somewhat worse:
IDDES with
synthetic turbulence
based on SST RANS
(u’2=v’2 =w’2)
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 28
NTS IDDES – Urms/Ubulk
Experiment
IDDES
(Recycling)
IDDES
(Synth. EARSM)
IDDES
(Synth. SST)
• Same “rating” of
the approaches as
that based on Cp
distributions
• (cf. prev. slide)
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 29
Pressure coefficient:
ANSYS IDDES and WMLES
Data for Diffuser 1
0.7
0.6
0.5
0.4
0.3
Cp
• ANSYS results:
• IDDES and (algebraic) WMLES
with recycling overestimate Cp
downstream from X/L = 0.5
• Grid sensitivity has to be checked –
simulations on a finer mesh are in
progress
• Same mesh as used by NTS,
but NTS code has higher-order
discretisation of advective fluxes
0.2
0.1
Experiment
IDDES
WMLES
0
-0.1
-0.2
0
1
0.5
1.5
2
X/L
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 30
ANSYS IDDES
Experiment
IDDES
(Recycling)
Experiment
U/Ubulk
IDDES
(Recycling)
Urms/Ubulk
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 31
ANSYS WMLES
Experiment
WMLES
(Recycling)
Experiment
U/Ubulk
WMLES
(Recycling)
Urms/Ubulk
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 32
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 the
duct flow expanding into a diffuser section, the consequent separation
flow region (onset, shape and size), the mean velocity field and
associated integral parameters (pressure distribution), as well as the
turbulence quantities.
• Simulations using SAS-RSM turned out to be quite sensitive to the
location of the inlet plane upstream of the diffuser (decay of resolved
turbulence, SAS reverting gradually into RANS mode)
• SST-based IDDES with inflow turbulent content created with the use of
synthetic turbulence generator developed by NTS and with the use of
turbulence “recycling” in upstream straight channel section is shown to
be capable of correctly reproducing major features of the mean flow and
turbulence statistics
• Synthetic turbulence created on the basis of EARSM RANS solution
tangibly improves accuracy of the simulation compared with the case
when the synthetic turbulence is created on the basis of the linear SST
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 33
model
Final Comments I
• Diffuser 2 doesn’t add to intelligence gained – don’t pursue
– no experimental Cp or Urms
• For Diffuser 1 RANS, too many different meshes in use.
– Please all consider using the mandatory (“medium”) mesh
• UniMAN, NTS
– Future RANS results “promised” by ONERA & NUMECA
• Should Cp curves really coincide at the first experimental
data point – or should they, as given in the TC description,
all pass through 0 Pa at x = 0..?
– Ohlsson’s DNS (**): Cp(x = 0) <[<?] 0
 Will keep all curves passing through first data point!
– (Ohlsson’s DNS is even slightly above)
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 34
(**) J. Fluid Mech. (2010), vol. 650, pp. 307–318. doi:10.1017/S0022112010000558
Final Comments II
• It would be interesting to understand why the different
EARSM/RSMs give different results and what is the reason
for better predictions by EBRSM vs. other models like
WJ-EARSM-BSL?
• One clue could be the level of secondary flow produced by
the models at the fully developed (?) inlet. Is a stronger
secondary flow responsible for later separation?
– Was it actually fully developed in the experiment?
– Somebody could calculate the 62.9 h of duct with e.g. EARSM
• postprocess secondary flow near outlet
• We could plot the secondary flow
close to the beginning of the Diffuser
for the final report:
– …
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 35
Final Comments III
– Plot V, W or sqrt(V2 + W2) along a diagonal line at constant x
•
•
•
•
x = 0 h (beginning of expansion)?
x = -3 h (mandatory mesh domain inlet)?
x = -6 h (Ohlsson’s picture above)?
x = -10 h (surely unaffected by diffuser…)?
– E.g. at x = -10 h: V, W vs. Z, diagonal line through y = 0, z = 0:
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 37
(**) J. Fluid Mech. (2010), vol. 650, pp. 307–318. doi:10.1017/S0022112010000558
Final Comments IV
•  All contributing partners:
Please provide…
–
–
–
–
Z, U, V, W
along a diagonal line through the duct (Z = 3.33 Y)
in simple tabular format (four-column ascii file: Z, U, V, W)
at the inlet into the computational domain,
i.e., for the mandatory mesh, at X = -3 h
– + (optionally) other locations
(further upstream, e.g. X = -10 h, if available)
ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 38