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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

    -

    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

    ATAAC final workshop 2012/6/11-12: ST 04 3D Stanford Diffuser; page 31

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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.

    -

    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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