Stanford 3D Diffuser – ST04. ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser;...

Stanford 3D Diffuser – ST04

ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser; page 2

Overview

• Goals of the testcase:– Corner flow separation often over-

predicted 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?

• Partners– ANS, NTS, NUM,TUD, UniMan, ONERA,

RRD,TUB

SST


Flow Description

• Major flow parameters– Incompressible fluid– Re = 10,000 based on inlet channel height and inlet bulk

velocity– Fully developed flow at diffuser inlet

Separation Zone

Schematic of Flow

Diffuser geometries


Experiment

• Available Data– Three velocity components (Diffuser 1 and 2)– Fluctuations of streamwise component, Urms (Diffuser 1)– Pressure coefficient distribution (Diffuser 1)

3D Magnetic Resonance Velocimetry (MRV)

Flow system schematic

Measured Velocity


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


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)


RANS Computational Grids

• ANSYS– Diffuser 1 and 2: 145×91×121

• 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

Medium mesh for Diffuser 1: used by ANSYS and NUMECA

NTS RANS mesh for Diffuser 1:


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


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..??


Locations for cross-comparisons

58

1215

X/H = 2H

Planes for streamwise velocity and Urms cross-comparisons

Cp line

Line for Cp cross-comparisons


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)

X/L

Cp

0 0.5 1 1.5 2-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

ExperimentANSYS BSL EARSMNUMECA BSL EARSMNUMECA WJ EARSMUniMan EBRSMNTS S-WJ-BSL-EARSM


Velocities at diagonals, Diffuser 1

z

u

0 0.5 1 1.5 2 2.5 3 3.50

0.2

0.4

0.6

0.8

1

1.2

1.4 ANSYS BSL EARSMNTS S-WJ-BSL-EARSM

z

v

0 0.5 1 1.5 2 2.5 3 3.5-0.006

-0.004

-0.002

0

0.002

0.004

0.006

z

w

0 0.5 1 1.5 2 2.5 3 3.5-0.015

-0.01

-0.005

0

0.005

0.01

0.015

z

u

0 0.5 1 1.5 2 2.5 3 3.50

0.2

0.4

0.6

0.8

1

1.2

1.4

z

v

0 0.5 1 1.5 2 2.5 3 3.5-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

z

w

0 0.5 1 1.5 2 2.5 3 3.5-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

X =

-3

HX

= 0

H


Streamwise velocity, Diffuser 1: RANS

• Results of WJ-BSL-EARSM 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


Velocity fluctuations, Diffuser 1: RANS

Urms / Ubulk 100

• All the tested EARSM are capable of reproducing velocity fluctuations(Urms) quite well

• Results of WJ-BSL-EARSM obtained at ANSYS and NUMECA are again very similar


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


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.


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


Grids for TUD and UniMan transient simulations

• UniMan– 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...

Mesh overview


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 upstreamrectangular 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


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)

ATAAC, page 20

Recycling


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, body-

fitted, 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


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


Pressure coefficientTUD, UniMan

Data for Diffuser 1

X/L

Cp

0 0.5 1 1.5 2-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

ExperimentTUD RANS-LESTUD RSM-SASUniMan RANS-LES

• TUD & UniMAN Hybrid RANS/LES methods predict the pressure coefficientvery well

• SAS-RSM model somewhat underestimates Cp.


UniMan RANS/LESDiffuser 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.


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/Ubulk100


X/L

Cp

0 0.5 1 1.5 2-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

ExperimentIDDES, recyclingIDDES, synth. turb., SSTIDDES, synth. turb., EARSM

Pressure coefficientNTS (IDDES)

Data for Diffuser 1 • NTS results:

• Best predictions: IDDES with recycling (“etalon” – no synthetic turbulence) and IDDES with inflow synthetic turbulence based onWJ-BSL-EARSM RANS solution

• Somewhat worse predictions: IDDES with synthetic turbulence based on SST RANS (u’2=v’2 =w’2)

• IDDES results most probably may be improved by shifting the inflow farther upstream (to provide a space for establishing normal stresses anisotropy)


Velocities at diagonals, NTS IDDES (??)

X =

-3

HX

= 0

H

z

u

0 0.5 1 1.5 2 2.5 3 3.50

0.2

0.4

0.6

0.8

1

1.2

1.4 RecyclingSynth. turb, EARSM

z

v

0 0.5 1 1.5 2 2.5 3 3.5-0.006

-0.004

-0.002

0

0.002

0.004

0.006

z

w

0 0.5 1 1.5 2 2.5 3 3.5-0.015

-0.01

-0.005

0

0.005

0.01

0.015

z

u

0 0.5 1 1.5 2 2.5 3 3.50

0.2

0.4

0.6

0.8

1

1.2

1.4

z

v

0 0.5 1 1.5 2 2.5 3 3.5-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

z

w

0 0.5 1 1.5 2 2.5 3 3.5-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04


NTS IDDES – UIDDES

(Synth. EARSM)IDDES

(Recycling)IDDES

(Synth. SST)Experiment• Same “rating” of the approaches as that based on Cp distributions:

•Best predictions: IDDES with recycling and IDDES with inflow synthetic turbulence based onWJ-BSL-EARSM RANS solution

•Somewhat worse: IDDES with synthetic turbulence based on SST RANS (u’2=v’2 =w’2)


NTS IDDES – Urms/UbulkIDDES

(Synth. EARSM)IDDES

(Recycling)IDDES

(Synth. SST)Experiment

• Same “rating” of the approaches as that based on Cp distributions• (cf. prev. slide)


Pressure coefficient:ANSYS IDDES and WMLES

Data for Diffuser 1 • 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

X/L

Cp

0 0.5 1 1.5 2-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

ExperimentIDDESWMLES


ANSYS IDDESIDDES

(Recycling)IDDES

(Recycling)Experiment Experiment

U/Ubulk

Urms/Ubulk


ANSYS WMLESWMLES

(Recycling)WMLES

(Recycling)Experiment Experiment

U/Ubulk

Urms/Ubulk


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 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)

(**) 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 likeWJ-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 flowclose to the beginning of the Diffuserfor the final report:

– …


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:

(**) 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)

Stanford 3D Diffuser – ST04. ATAAC meeting M06 Toulouse 2011/11/22-24: ST 04 3D Stanford Diffuser;...

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