Home | Project | Software | Gallery | News | Development | Use | Documentation | Search/Ask
 
Software
Presentation
Last delivery
Validation
Porting
Property
Restricted acces either to user or developer of elsA Download
 
 
© 1999-2016 ONERA Terms of use
  

Software validation

Verification and validation process

In order to control the evolution of the software, the elsA project team manages a regression database and a validation database.
Each developer has to run the regression database before integration of his development, in order to demonstrate non-regression of the results of previous capabilities. The regression database is today composed of more than 780 test cases (defined on a small number of iterations, in order to allow all necessary runs of the base, at admissible CPU cost). The elsA project team also insures the first level of software validation, by relying on a validation database including roughly 195 test cases. The validation database is composed of « complete » test cases (that is to say, for example when the flow is steady, defined on a number of iterations high enough to reach convergence). The test cases range from relatively academic test cases allowing the evaluation of a specific capability, to configurations representative of complex applications carried out by industry users. However, the project team preferibly selects reasonable in CPU time test cases, in order to maintain a resonable cost to the run of the complete validation base. A validation report is always associated with a major release version. The validation base is also run to evaluate most of the intermediate versions in order to detect difficulties if any, as soon as possible.
Important validation activities of elsA are also carried out at ONERA by the Applied Aerodynamics Department (DAAP), the Aerodynamics and Energetics modeling Department (DMAE) and the Structural Dynamics and Coupled Systems Department (DADS). This validation relies on detailed experimental results and includes contacts between experiment and CFD scientists.

Delivery version validation

The description of the tests and results, and some global information on validation may be find in the
Validation report for elsA v3.4.

You may have access hereafter, to the scripts (see Script column) of the tests used to validate elsA version V3.3,
and to description of the tests and post-processing of the results obtained (see Label column) .



Validation session

    elsA version is : 3.3.06
    The list of test cases is the following :
LabelScriptTitre
APROF-04-MG-LSAPROF_04_MG_LS.pyA Profil - Multigrid - Low speed
APROF-KL-Wl-D2D1APROF_KL_Wl_D2D1.pyA Profile: Wall law, KL
AS28G-A-KOAS28G_A_KO.pyAS28G Wing
AS28G-A-SAAS28G_A_SA.pyAS28G Wing
AS28G-AMRas28g_amr.pyAS28G Wing with AMR
AS28G-KO-BAS28G_LU.pyAS28G Wing
AS28G-NS-scaas28gv_s5_sca.pyAS28G Wing viscous computation in 2 blocks with wall law
AS28G-ROEO1-GRADas28ge_roeo1_grad.pyAS28G Wing - Shape optimization
AS28G-ROEVA-ADJas28ge_roeva_adj.pyAS28G Wing - Shape optimization
AS28G-ROEVA-GRADas28ge_roeva_grad.pyAS28G Wing - Shape optimization
AS28G-WLMGAS28G_WLMG.pyAS28G Wing with wall law and multigrid
ASF2-LSASF2_LS.pyASF2 helicopter Low Speed Preconditionning
AXI2DEULERNZ-01axi2dnz_01.pyAxisymmetric Nozzle 2D
AXI3DEULERNZ-01axi3dnz_02.pyAxisymmetric Nozzle 3D
Actuator-HelActu_Hel_eu.pyActuator-Disk in Climb, 3D Euler flow
Actuator-Hel-MPI-JOINActuator_Hel_MPI_JOIN.pyActuator-Disk in Climb, 3D Euler flow
Actuator-Hel-NU-LSActu_3D_eu_ff_chance.pyNon-Uniform Actuator-Disk, 3D Euler flow
BPROF-5DOMBPROF_5DOM.pyProfB airfoil with transition
Blade-7A-MPIBlade_7A_MPI.pyBlade 7A Michel:
Blunt-02Blunt_02.pyBlunt Cylinder - Euler -Mach 16
Blunt3D-RealGasBlunt3D_RealGas.pyBlunt Cylinder 3D - Steady real gas flow
Bump-02bBump_Dts.pyBump: Dual time step
Bump-02-chimBump_02_chim_rep.pyBump: 2D Turbulent unsteady flow, dual time step
Bump-gearbump_gear.pyBump: Gear method
BumpB-autoBumpB_auto.pyBump: Dual time step, automatic time step adaptation technique
BumpC-MKFLC2BumpC_MKFLC2.pyBumpC - 2D Turbulent MKFLC2 model
CASING-NMCASING-NM.pyChannel with simulated casing
CHIM-2D-01chim_2d_01.pyNACA0012 under a wall : Chimera, Euler, explicit
CHIM-2D-03chim_2d_03.pyNACA0012 under a wall : Chimera, Euler, IRS
CHIM-2D-ihcCHIM_2D_ihc.pyNACA0012 under a wall : Chimera, Euler
COL2CYGNE-INJ-AXICOL2CYGNE_INJ_AXI.pyCol de cygne avec injecteur axisymetrique decale
COL2CYGNE-INJ-NONAXICOL2CYGNE_INJ_NONAXI.pyCol de cygne avec injecteur non axisymetrique decale
COMPRESSOR-PI9-MXPLCOMPRESSOR_PI9_MXPL.pyAXIAL COMPRESSOR STAGE rotor-stator
COMPRESSOR-STAGE-CHOROCOMPRESSOR_STAGE_CHORO.pySubsonic axial compressor, NS + SA, Chorochronic condition
COMPRESSOR-STAGE-CHORO-2COMPRESSOR_STAGE_CHORO_2.pyReprise du cas COMPRESSOR-STAGE-CHORO
CT6-BW-SA-SSOR-dtsct6_bw_lussorsca_dts_10_spalart.pyCt6 : ALE, Lussor, Spalart, steady
Caimen-05as28Caimen1s2_sca.py3D Wing: Multidimensional slip
Caimen-08as28CaimenPartRac.py3D Wing: Partially Coincident Matching
Caimen-10as28Caimen1s2_mat_LDU.py3D Wing: Matrix Viscosity, LDU
Compressor-CME2-OptAdjCompressor_CME2_OptAdj.pyCompressor CME2 - KL - Shape Optimization (adjoint gradient computation)
DGV-C2-LSC20087_gk6.pyHelico DGV, NS, k-l, Multigrid, Low speed preconditionning
DebitGlobal-01DebitGlobal_01.pyTotal Mass Flow Rate
DebitGlobal-MPIDebitGlobal_MPI.pyTotal Mass Flow Rate
Dyvas-AELelsaflex.pyDyvas - wing - fuselage
ELECTRE-LAMelectre.pyElectre (axisym) configuration
FUS-STRUT-HUBFUS_STRUT_HUB.pyx
FanBlade-S1MA-OptLinFanBlade_S1MA_OptLin.py3D Fan Blade S1MA - Euler - Shape Optimization (linearized gradient computation)
H8YE_LU_MG3W2_cfl50_v3p_1.py3D Wing/Body NS k-omega
H8Y-A-KOH8Y_A_KO.py3D Wing/Body NS k-omega - Lussor
H8Y-A-SAH8Y_A_SA.py3D Wing/Body NS Spalart-Allmaras - Lussor
Hirett-2D-Adjhirett_2d_optadj.pyHiRett 2D - Euler - Shape Optimization
Hirett-A-KOHirett_A_KO.pyHiReTT Wing/Body - komega-wilcox
Hirett-A-SAHirett_A_SA.pyHiReTT Wing/Body - Spalart
Hirett-MS-01LURELAX_1_p10.pyx
Hirett-MS-02LURELAX_2_p10.pyx
Hirett-MS-03LURELAX_3_p10.pyHiReTT Wing/Body - Kok with Zheng limitor
IHT-MULTIMODELIHT_MULTIMODEL.pyHomogeneous isotropic turbulence with free decaying
LS89LS89.pyTurbine Turbulent Spalart
LS89-KOLS89_KO.pyTurbine Turbulent Kok
MARCO-KEPSMARCO_KEPS.pyAxisymmetric MARCO Nozzle
MARCO-KEPS-AXISOURCEMARCO_KEPS_AXISOURCE.pyAxisymmetric MARCO Nozzle
MARCO-VENTI-KEPSMARCO_VENTI_KEPS.pyAxisymmetric MARCO Nozzle with ventilation
NACA-CHIM-DBWALLNACA_DBWALL.pynaca chimere double wall
OAT15AOAT15A.pyOAT15A + Spalart + Unsteady
OAT15A-VrtOAT15A_Vrt.pyOAT15A - KL+Interm.+WL+Vort. - 2 doms
OAT15A-VrtSSTOAT15A_VrtSST.pyOAT15A - k-omega SST - Interm. - WL - Vort. - 2 doms
PF1-3BladesPF1_3Blades.pyPF1-3Blades - 3D Euler - Motion with ALE
PF1Blade-alePF1Blade_ale.pyPF1-Blade - 3D Euler - Motion with ALE
PF1Blade-rigidPF1Blade_rigid.pyPF1-Blade - 3D Euler - Rigid motion
PF1Blade-rigid-ROEpf1_iso_rig.pyPF1-Blade - 3D Euler - Rigid motion
PF1Blade-rigid-dts-ROEpf1_iso_rig_dts.pyPF1-Blade - 3D Euler - Rigid motion
Plate-ASM-TLPlate_ASM_TL.pyFlat Plate Turbulent ASM with two layer modelisation
Plate-BlxflatPlateBaldwin.pyFlat Plate Turbulent: Baldwin Lomax
Plate-Blx-02Plate_Blx_02_LuSca_BE_MG_V1_Serial.pyFlat Plate Turbulent: Baldwin Lomax - 2 blocks
Plate-Blx-MDPARPlate_Blx_MDPAR.pyFlat Plate Turbulent: Baldwin Lomax Parallel
Plate-Collect-SpalPlate_Collect_Spal.pyTranslated flatPlate test case with collect boundary condition
Plate-KEPS-AflatPlateKEPS.pyFlat Plate Turbulent: KEPS
Plate-KEps-KLPlate_KEps_KL.pyFlat Plate Turbulent KEps, Intermittency
Plate-KEps-TLPlate_KEps_TL.pyFlat Plate Turbulent KEps with two layer modelisation
Plate-KL-GPlate_KL_G.pyFlat Plate Turbulent KL
Plate-KL-Iplate_kl_i.pyFlat Plate Turbulent: KL, Scalar LDU
Plate-KL-MGflatPlateKL0_MG.pyFlat Plate Turbulent: KL, MultiGrid
Plate-KL-WlPlate_KL_Wl.pyFlat Plate Turbulent: KL Wall law
Plate-KL-orthdPlate_KL_orthd.pyFlat Plate Turbulent: KL, MultiGrid, orth dist
Plate-KOflatPlateKO.pyFlat Plate Turbulent: KO
Plate-KO-WlPlate_KO_Wl.pyFlat Plate Turbulent: KO - Wall law
Plate-Keps-v2fPlate_Keps_v2f.pyFlat Plate Turbulent k-eps-v2f, Intermittency
Plate-Knut-SpalPlate_Knut_Spal.pyFlat Plate Turbulent Knut-Spalart
Plate-Michel-1flatPlateMichel_1.pyFlat Plate Turbulent: Michel
Plate-Michel-3Plate_Michel_3.pyFlat Plate Turbulent: Michel
Plate-Rough-SpalPlate_Rough_Spal.pyFlat Plate with rough wall (Acharia experiment)
Plate-SA-HF1fp_SA_WallHeatFlux_1.pyFlat Plate Turbulent: Spalart + wall heat flux
Plate-SA-HF2fp_SA_WallHeatFlux_2.pyFlat Plate Turbulent: Spalart + wall heat flux + motion
Plate-SA-Isoth1fp_SA_WallIsoth_1.pyFlat Plate Turbulent: Spalart + wall isoth
Plate-SA-Isoth2Plate_SA_Isoth2.pyFlat Plate Turbulent: Spalart + wall isoth + motion
Plate-SpalflatPlateSpalart.pyFlat Plate Turbulent: Spalart
Plate-Spal-LUflatPlateSpalartLU.pyFlat Plate Turbulent: Spalart + LUrelaxsca
Propeller-EulPropeller_Eul.pyPropeller - Euler
R7A-RANS-DtsR7A_RANS_Dts.pyRotor 7A 1.2-F1 deforming blade :ALE - Turbulent Michel - Dts
R7A-RANS-GearR7A_RANS_Gear.pyRotor 7A 1.2-F1 deforming blade :ALE - Turbulent Michel - Gear
RAE-BLX-02RAE_BLX_02.pyRae2822 Profile: Baldwin-Lomax,2 dom, Intermittency
RAE-KL-02rae2822_KL_2dom.pyRae2822 Profile: KL, 2 domains
RAE-KL-CRITLOCRAE_KL_CRITLOC.pyRae2822 Profile: KL, Abu Ghannam \& Shaw local transition criteria
RAE-KL-CRITLOC-1S2RAE_KL_CRITLOC_1S2.pyRae2822 Profile: KL,Abu Ghannam \& Shaw local transition criteria
RAE-KL-VGRD-5PCORRAE_KL_VGRD_5PCOR.pyRae2822 Profile: KL, 1 domain
RAE-KO-AMRrae_ko_amr.pyrae2822 - KOMEGA - Local Multigrid
RAE-KO-CAVITYRAE_KO_CAVITY.pyRae2822 Profile: KO, Double BC Chimera
RAE-KO-CHIMrae_ko_chim.pyRae2822 Profile : Chimera, IRS, KO, Intermittency
RAE-KO-LU-SSTRAE_KO_LU_SST.pyrae2822 - KOMEGA with SST Correction
RAE-KO-LU-SST-SCHEMERAE_KO_LU_SST_SCHEME.pyrae2822 - KOMEGA with SST Correction
RAE-KO-LU-SST-ausmpRAE_KO_LU_SST_ausmp.pyrae2822 - KOMEGA with SST Correction - ausmp scheme
RAE-KO-LU-SST-jamesonRAE_KO_LU_SST_jameson.pyrae2822 - KOMEGA with SST Correction - Jameson scheme
RAE-KO-LU-SST-rbciRAE_KO_LU_SST_rbci.pyrae2822 - KOMEGA with SST Correction - rbci scheme
RAE-KO-LU-SST-rbco3RAE_KO_LU_SST_rbco3.pyrae2822 - KOMEGA with SST Correction - rbco3 scheme
RAE-KO-SSTRAE_KO_SST.pyrae2822 - KOMEGA with SST Correction
RAE-KO-TRArae_ko_tra.pyRae2822 Profile: KO, Intermittency
RAE-KW-MG-MPIrae_kw_mg_2d_mpi.pyRae2822 Profile: KOmega Parallel
RAE-SA-CRITNOLOCRAE_SA_CRITNOLOC.pyRae2822 Profile: Spalart-Allmaras, non-local transition criterion
RAE-SA-SSORRAE_SA_SSOR.pyRae2822 Profile: Spalart
RAE-TUR-D0rae2822_2dom_dist0.pyRae2822 Profile: Distance to wall
RAE-TUR-D1rae2822_2dom_dist1.pyRae2822 Profile: Distance to wall
ROTOR-01ROTOR_01.pyRotor in hover 3D: Inviscid flow
ROTOR-7A-12F1ROTOR_7A_12F1.pyRotor 7A 1.2-F1 deforming blade :ALE - Euler
ROTOR-7A-CHIM-01rotor_7A_chim_01.pyStandard Rotor 7A : Chimera
ROTOR-7A-KOROTOR_7A_KO.pyRotor 7A K-Omega:
ROTOR-7A-KO-MDPARROTOR_7A_KO_MDPAR.pyRotor 7A K-Omega Parallel:
ROTOR-AIX-CHIMROTOR_AIX_CHIM.pyRotor Chimere
ROTOR-CHIMERE6rotor_chimere.pyRotor Chimere
ROTOR-Michel-01ROTOR_Michel_01.pyRotor in hover 3D: Turbulent flow
ROTOR-NS-MGINTERPROTOR_NS_MGINTERP.pyRotor 7A - CHIMERE - K-OMEGA
ROTOR-STATROTOR_STAT.pyx
ROTOR37-KEPSROTOR37_KEPS.pyRotor 37: Turbulent flow
ROTOR37-MICHELROTOR37_MICHEL.pyRotor 37: Turbulent flow
RodInCavity-A06RodInCavity_A06.py2-D cavity with heated rod
S-tube-B-roeshockTube.pyShockTube 3D
S-tube-CshockTube1D.pyShockTube 1D
S-tube-p05shockTubeUpw.pyShockTube UpWind
S3CH-02elsa_fin.pyS3CH - MonoGrid
S3CH-A-KOS3CH_A_KO.py3D Wing Part
S3CH-A-SAS3CH_A_SA.py3D Wing Part
S3CH-MG-LUSSORS3CH_MG_LUSSOR.pyS3CH - MultiGrid - Lussor
S3CH-MS-01S3CH_MS_01.py3D Wing Part
S3CH-SSOR-MATS3CH_SSOR_MAT.pyS3CH - MultiGrid - Lussor
SPOILER-CHIMERASPOILER_CHIMERA.py3D Wing profile with spoiler resolved by a Chimera Technique
SQNZ-MDPAR-01eu8dompar.pySquaredNozzle MultiDomain Parallel
SQNZ-MDPAR-03eu2domi_2node.pySquaredNozzle MultiDomain Parallel
SQNZ-NS-06SQNZ_NS_06.pySquared Nozzle: Laminar, 3 domains
SQNZ-OptAdjSQNZ_OptAdj.pySquared Nozzle - Euler - Shape Optimization (adjoint gradient computation)
SQNZ10eu2dom_nm.pyNozzle: NoMatch
StatorBlade-OptLinStatorBlade_OptLin.pyStator vane 3D - Euler - Shape Optimization (linearized gradient computation)
Step-ASM-TLStep_ASM_TL.pyStep - 2D ASM two layer
Tube-Collect-SpalTube_Collect_Spal.pyPipe - Collect and injrot boundary condition
VEGA-2HOHvega_2hoh.pyS/R MultiStage - 3D turbulent Michel
VEGA-2HOH-02VEGA_2HOH_02.pyS/R Multistage with Blade Reduction - 3D Laminar
VEGA2-STAGE-MXPLVEGA2_STAGE_MXPL.pySteady - Stage-MXPL
VEGA2-STAGE-MXPL-MGVEGA2_STAGE_MXPL_MG.pyMultistage - Multigrid
VEGA2-STAGE-REDVEGA2_STAGE_RED.pyUnsteady - Stage-Red
Wing-Body-F4-Linf4_va_lin_2r_nrg.pyF4 Wing with body- 3D Euler - Shape Optimization
WingDefRoeAdjWingDefRoeAdj.pyWing - turbulent SA - parallel - Adjoint method
WingF4-KLWingF4_KL.pyF4 Wing - 3D NS turbulent KL
WingM6-Blx-OptLinwingm6_BL2_optlin.pyM6 Wing - 3D NS turbulent Blx - Shape optimization
WingM6-KLWingM6_KL.pyM6 Wing - 3D NS turbulent KL
WingM6-KO-SST-SCHEMEWingM6_KO_SST_SCHEME.pyM6 Wing - 3D NS turbulent Blx
WingM6-KO-SST-ausmpWingM6_KO_SST_ausmp.pyM6 Wing - 3D NS turbulent Blx - AUSMP scheme
WingM6-KO-SST-jamesonWingM6_KO_SST_jameson.pyM6 Wing - 3D NS turbulent Blx - Jameson scheme
WingM6-KO-SST-rbciWingM6_KO_SST_rbci.pyM6 Wing - 3D NS turbulent Blx - rbci scheme
WingM6-KO-SST-rbco2WingM6_KO_SST_rbco2.pyM6 Wing - 3D NS turbulent Blx - rbco2 scheme
WingM6-KO-SST-rbco3WingM6_KO_SST_rbco3.pyM6 Wing - 3D NS turbulent Blx - rbco3 scheme
WingM6-KOucpd-Adjwingm6_KO_optlin_bas.pyM6 Wing - 3D NS turbulent KO uncoupled - Shape optimization
WingM6-Michel-LinWingM6_Michel_Lin.pyM6 Wing 1972 - 3D config. - Linearization of Michel \& al. turbulent model
WingM6-SA-OptAdj-MPIWingM6_SA_OptAdj_MPI.pyM6 Wing - 3D NS turbulent SA - parallel - Adjoint methode
naca-KL-LSnaca_KL_LS.pyNACA0012: Preconditionning Low Speed Turbulent Multigrid
naca-LMG-nmnaca_LMG_nm.pyNACA: AMR and nomatch
naca-alenaca_ale.pyNACA0064 : deformation ALE
naca-rigidnaca_rigid.pyNACA0064: Rigid motion
naca-rigid-BLX-dtsnaca_rigid_BLX_dts.pyNACA0064: Rigid motion
naca-slidingelsa_dts_configvol.pyNACA0064: Rigid motion Sliding meshes
naca-sliding-MPIelsa_dts_configvol_mpi.pyNACA0064: Rigid motion Sliding meshes
naca-underwallnaca_underwall.pyNACA0012 under a wall : Chimera, Euler
naca01-EXTRACTnaca01_EXTRACT.pyNACA0012
naca10naca10.pyNACA0012: Multigrid, Scalar Dissipation
naca11naca11.pyNACA0012: Backward Euler, LDU, Multigrid, Scalar Dissipation
naca6naca6.pyNACA0012: Matrix Viscosity
naca64-Eul-Linprofil_roeva_optim_lin.pynaca Euler shape optimization
naca64-Eul-Lurnaca64_Eul_Lur.pynaca Euler Linearized - Aeroelasticity
naca64-KOcpld-Linprofilva_lin_cpld.pynaca k-omega - coupled systems - shape optimization
naca64-KOucpd-Adjprofilva_adj_nrg.pynaca k-omega shape optimization
naca7-LSnaca7_LS.pyNACA0012: Preconditionning Low Speed Multigrid
naca7-MARTnaca7_MART.pyNACA0012: Scalar Viscosity, Martinelli
naca8naca8.pyNACA0012: Scalar Viscosity
naca9naca2d.pyNACA0012: Coarse-Fine Matching
nacaUp2nacaUp2.pyNACA0012: Roe fluxes
nacaUp3nacaUp3.pyNACA0012: Direct Coquel fluxes
turbine-Michelvega.pyTurbine stator Turbulent Michel

APROF-04-MG-LS

(Back to top of page)

A Profil - Multigrid - Low speed

APROF_04_MG_LS.py2D-Plane configuration
Navier-Stokes
KL turbulence model
Prescribed transition
Runge-Kutta
Jameson fluxes
Scalar Dissipation with Martinelli correction
IRS
Multi-Grid
Low speed preconditionning
  • 2D wing profile (A-profile) : M~=~0.144~\alpha~=~13.3~Re_{inf}~=~2.1~10^6.
  • Steady subsonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Intermittency file.
  • Mesh:~257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dismrt'.
  • avcoef:0.5, 0.008, 1.; avcoef coarse grid : 1., 0.064
  • Jameson centered fluxes with Roe correction for transport equations
  • (Low value of Harten correction coefficient : 0.01).
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid (1 coarse grid, V cycle)
  • Low speed preconditionning
  • Local time step.
  • 10000 iterations, CFL=5.
  • APROF-04-MG-LS/APROF-03-MG-LS_1.jpeg
    APROF-04-MG-LS/APROF-03-MG-LS_2.jpeg
    APROF-04-MG-LS/APROF-03-MG-LS_3.jpeg
    APROF-04-MG-LS/zresidu.jpeg

    APROF-KL-Wl-D2D1

    (Back to top of page)

    A Profile: Wall law, KL

    APROF_KL_Wl_D2D1.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Wall law
    Prescribed transition
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • 2D wing profile (A-profile) : M~=~0.144~\alpha~=~13.3~Re_{inf}~=~2.1~10^6.
  • Steady subsonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Wall law.
  • Intermittency file.
  • Mesh:~257 \times 46 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca':[0.5,0.032,1.], av\_type=2 (4th order artificial viscosity = " d2\_rspec\_d1" )
  • Jameson centered fluxes with Roe correction for transport equations
  • (Low value of Harten correction coefficient : 0.01).
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 15000 iterations, CFL=4.
  • APROF-KL-Wl-D2D1/APROF-KL-Wl-D2D1_1.jpeg
    APROF-KL-Wl-D2D1/APROF-KL-Wl-D2D1_2.jpeg
    APROF-KL-Wl-D2D1/APROF-KL-Wl-D2D1_3.jpeg
    APROF-KL-Wl-D2D1/zresidu.jpeg

    AS28G-A-KO

    (Back to top of page)

    AS28G Wing

    AS28G_A_KO.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • AS28G Wing/Body/Pylon/Nacelle
  • M~=~0.8~\alpha~=~2.2~deg~Re_{AMC}~=~9.972~10^6.
  • Mesh : 56 blocks, 4 608 804 nodes
  • Steady transonic turbulent flow.
  • Turbulence model : (k,omega) Wilcox model, Zheng limitor, no SST correction
  • Wall distance calculation "mininterf"
  • Jameson centered fluxes (skew-symmetric form) for mean flow
  • with artificial dissipation "dissca" : 0.5 0.016 1.0
  • with dissipation reduction in all directions based on normal speed values
  • Border treatment "dif0null" for artificial viscosity
  • First-order centered fluxes for transport equations
  • Gradients calculated on cell centers, then corrected on interfaces ("5p\_cor")
  • Extrapolation to wall border for mean gradients and turbulent gradients
  • Time integration : backward Euler
  • Implicit scalar LU-SSOR : 4 relaxation sweeps
  • Multigrid acceleration method on the mean equation sub-system :
  • volumetric correction transfer on coarse grid,
  • 1 coarse grid, synchronous restriction,
  • volumetric correction transfer on coarse grid,
  • correction transfer 'bilin\_topo' from coarse to fine grid,
  • cell to cell prolongation 'cell2cell\_c',
  • artificial viscosity coefficients in coarse grid : 0.5 0.
  • 1 sub-iteration for the turbulence sub-system
  • Filter "incr\_new+prolong"
  • Initialization : uniform flow
  • Timestep evaluation per direction ("timestep\_type directional")
  • 700 iterations, CFL=50. (with linear evolution from CFL=1. during first 57 it.)
  • AS28G-A-KO/as28g_kpi_1.jpeg
    AS28G-A-KO/as28g_kp_2.jpeg
    AS28G-A-KO/zresidu.jpeg

    AS28G-A-SA

    (Back to top of page)

    AS28G Wing

    AS28G_A_SA.py3D configuration
    Multi-Domain
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • AS28G Wing/Body/Pylon/Nacelle
  • M~=~0.8~\alpha~=~2.2~deg~Re_{AMC}~=~9.972~10^6.
  • Mesh : 56 blocks, 4 608 804 nodes
  • Steady transonic turbulent flow.
  • Turbulence model : Spalart-Allmaras
  • Wall distance calculation "mininterf"
  • Jameson centered fluxes (skew-symmetric form) for mean flow
  • with artificial dissipation "dissca" : 0.5 0.016 1.0
  • with dissipation reduction in all directions based on normal speed values
  • Border treatment "dif0null" for artificial viscosity
  • First-order centered fluxes for transport equations
  • Gradients calculated on cell centers, then corrected on interfaces ("5p\_cor")
  • Extrapolation to wall border for mean gradients and turbulent gradients
  • Time integration : backward Euler
  • Implicit scalar LU-SSOR : 4 relaxation sweeps
  • Multigrid acceleration method on the mean equation sub-system :
  • volumetric correction transfer on coarse grid,
  • 1 coarse grid, synchronous restriction,
  • volumetric correction transfer on coarse grid,
  • correction transfer 'bilin\_topo' from coarse to fine grid,
  • cell to cell prolongation 'cell2cell\_c',
  • artificial viscosity coefficients in coarse grid : 0.5 0.
  • 1 sub-iteration for the turbulence sub-system
  • Filter "incr\_new+prolong"
  • Initialization : uniform flow
  • Timestep evaluation per direction ("timestep\_type directional")
  • 700 iterations, CFL=50. (with linear evolution from CFL=1. during first 57 it.)
  • AS28G-A-SA/as28g_kpi_1.jpeg
    AS28G-A-SA/as28g_kp_2.jpeg
    AS28G-A-SA/zresidu.jpeg

    AS28G-AMR

    (Back to top of page)

    AS28G Wing with AMR

    as28g_amr.py3D configuration
    Multi-Domain
    Euler
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Local Multi-Grid (AMR)
  • AS28G wing + local multigrid. M_{\inf}~=~0.8~,~\alpha~=~2.2~,~Re_{\inf}~=~1.493~10^6.
  • Steady transonic inviscid flow.
  • Initial conditions~: from uniform state.
  • Mesh:~ 2 blocks and 3 levels.
  • Jameson centered fluxes with artificial dissipation `dissca':[~1.~,~0.064~].
  • Time integration :~ Backward Euler.
  • Implicit:~LU-Relax scalar.
  • Local time step.
  • 3500 iterations, CFL=5.
  • AS28G-AMR/mesh.jpeg
    AS28G-AMR/isomach.jpeg
    AS28G-AMR/pressure_13.jpeg
    AS28G-AMR/pressure_5.jpeg
    AS28G-AMR/zresidu.jpeg

    AS28G-KO-B

    (Back to top of page)

    AS28G Wing

    AS28G_LU.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • AS28G Wing/Body/Pylon/Nacelle
  • M~=~0.8~\alpha~=~2.2~deg~Re_{AMC}~=~9.972~10^6.
  • Mesh : 56 blocks, 4 608 804 nodes
  • Steady transonic turbulent flow.
  • Turbulence model : (k,\omega) Kok with Zheng limitor (kok\_diff\_cor=0)
  • Wall distance calculation along grid lines
  • Jameson centered fluxes (divergence form) for mean flow
  • with artificial dissipation "dismrt" : 0.5 0.016 1.0 0.5
  • Border treatment "dif0null" for artificial viscosity
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction : 0.01
  • Gradients calculated on cell centers
  • Extrapolation to wall border for mean gradients and turbulent gradients
  • Time integration : backward Euler
  • Implicit scalar LU-Relax : 4 relaxation sweeps, relaxscatype=viscous\_5p
  • Multigrid acceleration method on the mean equation sub-system :
  • 1 coarse grid, synchronous restriction,
  • arithmetic correction transfer on coarse grid,
  • correction transfer'inv\_topo' from coarse to fine grid,
  • cell to node prolongation
  • artificial dissipation coefficients in coarse grid : 1. 0.032
  • 1 sub-iteration for the turbulence sub-system.
  • No filter to force field positivity.
  • Initialization : uniform flow
  • 1000 iterations, CFL=100.
  • AS28G-KO-B/as28g_kpi_1.jpeg
    AS28G-KO-B/zresidu.jpeg
    AS28G-KO-B/as28g_kp_2.jpeg

    AS28G-NS-sca

    (Back to top of page)

    AS28G Wing viscous computation in 2 blocks with wall law

    as28gv_s5_sca.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Wall law
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
  • AS28G wing. M_{\inf}~=~0.8~,~\alpha~=~2.2~,~Re_{\inf}~=~1.493~10^6.
  • Steady transonic flow.
  • Turbulence model~: 2 transport equations (k,\Omega).
  • Initial conditions~: from uniform state.
  • Mesh:~ 2 blocks including 207025 nodes per block.
  • Jameson centered fluxes with artificial dissipation `dissca':[~1.0~,~0.032~,~1.0~].
  • Harten correction coefficient = 0.1
  • Time integration :~backwardeuler.
  • LU relaxation with upwind scalar linearization of convective terms and 5 point-scalar linearization of diffusive terms.
  • Local time step.
  • 5000 iterations, CFL=2000.
  • AS28G-NS-sca/AS28G_KO_cp_int_ext_sym_sca.jpeg
    AS28G-NS-sca/zresidu.jpeg

    AS28G-ROEO1-GRAD

    (Back to top of page)

    AS28G Wing - Shape optimization

    as28ge_roeo1_grad.py3D configuration
    Shape optimization linearized equation
    Euler
    Backward-Euler
    Roe fluxes
    LU
  • AS28G wing. M_{\inf}~=~0.8~,~\alpha~=~2.2~
  • Mesh: 257 \times 49 \times 33.
  • Steady transonic inviscid flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=10.
  • lorsque la convergence est obtenueunsteady solution at t=16.
  • First order Roe Upwind fluxes.
  • Time integration: backward Euler.
  • Gradient computation: linearized method.
  • One shape parameter: angular twist.
  • Calculation of lift coefficient CL and pressure drag coefficient CD_{p} gradients.
  • AS28G-ROEO1-GRAD/drhoda1.jpeg
    AS28G-ROEO1-GRAD/zresidu1.jpeg
    AS28G-ROEO1-GRAD/zresidu2.jpeg

    AS28G-ROEVA-ADJ

    (Back to top of page)

    AS28G Wing - Shape optimization

    as28ge_roeva_adj.py3D configuration
    Shape optimization adjoint equation
    Euler
    Backward-Euler
    Roe fluxes
    LU
  • AS28G wing. M_{\inf}~=~0.8~,~\alpha~=~2.2~
  • Mesh: 257 \times 49 \times 33.
  • Steady transonic inviscid flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=10.
  • Second order Roe Upwind flux (van Albada limiter).
  • Time integration: backward Euler.
  • Gradient computation: adjoint method.
  • Calculation of lift coefficient CL and pressure drag coefficient CD_{p} gradients.
  • Shape parameter : angular twist.
  • AS28G-ROEVA-ADJ/adj1-ro.jpeg
    AS28G-ROEVA-ADJ/zresidu1.jpeg
    AS28G-ROEVA-ADJ/zresidu2.jpeg

    AS28G-ROEVA-GRAD

    (Back to top of page)

    AS28G Wing - Shape optimization

    as28ge_roeva_grad.py3D configuration
    Shape optimization linearized equation
    Euler
    Backward-Euler
    Roe fluxes
    LU
  • AS28G wing. M_{\inf}~=~0.8~,~\alpha~=~2.2~
  • Mesh: 257 \times 49 \times 33.
  • Steady transonic inviscid flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=10.
  • Two order Roe Upwind fluxes (van Albada limiter).
  • Time integration: backward Euler.
  • Gradient computation: linearized method.
  • One shape parameter: angular twist.
  • Calculation of gradients of lift CL, pressure drag CD_{p}, wave drag CD_{w} and induced drag CD_{i} coefficients.
  • AS28G-ROEVA-GRAD/drhoda1.jpeg
    AS28G-ROEVA-GRAD/zresidu1.jpeg
    AS28G-ROEVA-GRAD/zresidu2.jpeg

    AS28G-WLMG

    (Back to top of page)

    AS28G Wing with wall law and multigrid

    AS28G_WLMG.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Wall law
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
  • AS28G wing + wall law + muligrid. M_{\inf}~=~0.8~,~\alpha~=~2.2~,~Re_{\inf}~=~1.493~10^6.
  • Steady subsonic perfect gas flow.
  • Turbulence model~: 2 transport equations (k,\Omega).
  • Initial conditions~: from uniform state.
  • Mesh:~ 2 blocks including 181585 nodes per block.
  • Jameson centered fluxes with artificial dissipation `dismrt':[~0.5~,~0.016~,~1.0~,~0.5~].
  • \chi_{2}~=~0.5 and \chi_{4}~=~0.032 on coarse grids.
  • Harten correction coefficient = 0.1
  • Time integration :~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration : V-cycle on 3 coarse grids, 3 iterations on turbulent equations
  • Local time step.
  • 1000 iterations, CFL=6.
  • AS28G-WLMG/flux-as28g.jpeg
    AS28G-WLMG/p-as28g.jpeg
    AS28G-WLMG/zresidu.jpeg

    ASF2-LS

    (Back to top of page)

    ASF2 helicopter Low Speed Preconditionning

    ASF2_LS.py3D configuration
    Multi-Domain
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
    Low speed preconditionning
  • Helicopter fuselage, Mach = 0.01, alpha = -5 deg.
  • Steady transonic perfect gas flow.
  • Mesh:~ 8 blocks including 230400 cells.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration :~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration
  • Low speed preconditionning.
  • Local time step.
  • 500 iterations.
  • ASF2-LS/ASF2-LS_1.jpeg
    ASF2-LS/zresidu.jpeg

    AXI2DEULERNZ-01

    (Back to top of page)

    Axisymmetric Nozzle 2D

    axi2dnz_01.py2D-Axi configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    Explicit
  • 2D axisymmetric nozzle.
  • Steady transonic perfect gas flow.
  • Mesh:~45 \times 17 \times 2.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Explicit. Local time step.
  • 1200 iterations, CFL=1.
  • AXI2DEULERNZ-01/AXI2DEULERNZ-01_1.jpeg
    AXI2DEULERNZ-01/zresidu.jpeg

    AXI3DEULERNZ-01

    (Back to top of page)

    Axisymmetric Nozzle 3D

    axi3dnz_02.py2D-Axi configuration
    3D treatment
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    Explicit
  • 3D axisymmetric nozzle.
  • Steady transonic perfect gas flow.
  • Mesh:~45 \times 17 \times 73.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Explicit. Local time step.
  • 1500 iterations, CFL=1.
  • AXI3DEULERNZ-01/AXI3DEULERNZ-01_1.jpeg
    AXI3DEULERNZ-01/AXI3DEULERNZ-01_2.jpeg
    AXI3DEULERNZ-01/zresidu.jpeg

    Actuator-Hel

    (Back to top of page)

    Actuator-Disk in Climb, 3D Euler flow

    Actu_Hel_eu.py3D configuration
    Multi-Domain
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
  • Actuator-Disk in climb.
  • Steady subsonic perfect gas flow.
  • Mesh:~ 4 blocks including 245 760 cells.
  • Jameson centered fluxes with artificial dissipation `dissca':[~0.0~,~0.016~,~1.0~].
  • Time integration :~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration : W-cycle on 2 coarse grids,
  • Local time step.
  • 500 iterations, CFL=5.
  • Actuator-Hel/Actuator-Hel_1.jpeg
    Actuator-Hel/Actuator-Hel_2.jpeg
    Actuator-Hel/Actuator-Hel_3.jpeg
    Actuator-Hel/zresidu.jpeg

    Actuator-Hel-MPI-JOIN

    (Back to top of page)

    Actuator-Disk in Climb, 3D Euler flow

    Actuator_Hel_MPI_JOIN.py3D configuration
    Multi-Domain
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
    Parallel
  • Actuator-Disk in climb.
  • Steady subsonic perfect gas flow.
  • Mesh:~ 4 blocks including 245 760 cells.
  • Jameson centered fluxes with artificial dissipation `dissca':[~0.0~,~0.016~,~1.0~].
  • Time integration :~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration : W-cycle on 2 coarse grids,
  • Local time step.
  • Paralle computation, 4 processors
  • 500 iterations, CFL=5.
  • Actuator-Hel-MPI-JOIN/Actuator-Hel_1.jpeg
    Actuator-Hel-MPI-JOIN/Actuator-Hel_2.jpeg
    Actuator-Hel-MPI-JOIN/Actuator-Hel_3.jpeg

    Actuator-Hel-NU-LS

    (Back to top of page)

    Non-Uniform Actuator-Disk, 3D Euler flow

    Actu_3D_eu_ff_chance.py3D configuration
    Multi-Domain
    Euler
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
    Low speed preconditionning
  • Actuator-Disk in Forward Flight.
  • Steady subsonic perfect gas flow.
  • Mesh:~ 4 blocks including 245 760 cells.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration :~ Backward Euler.
  • Implicit : scalar LU-SSOR.
  • Low speed preconditionning.
  • Multigrid convergence acceleration : V-cycle on 2 coarse grids,
  • Local time step.
  • 1000 iterations, CFL=10.
  • Actuator-Hel-NU-LS/gamma.jpeg
    Actuator-Hel-NU-LS/mach.jpeg
    Actuator-Hel-NU-LS/zresidu.jpeg

    BPROF-5DOM

    (Back to top of page)

    ProfB airfoil with transition

    BPROF_5DOM.py3D configuration
    Multi-Domain
    Navier-Stokes
    KL turbulence model
    Transition criteria
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Low speed preconditionning
  • "B airfoil" from Airbus (ONERA F2 experiment)
  • M_0=0.15, R_C=1.5\,10^{6}, T_i=295.5K, \alpha=7^\circ
  • Steady laminar/turbulent viscous flow
  • Turbulence model~: k-L Smith model
  • Transition criterion : "Arnal-Habiballa-Delcourt" with Gleyzes extension for
  • separation bubbles
  • T_u=0.1\%
  • Mesh : "C+H" 257x91 81x201. The "C" 257x91 domain is cut in 4 parts to check
  • the multidomain capbility of the transition computation
  • walldistcompute = 'mininterf'
  • Jameson centered flux with artificial dissipation 'dismrt' for mean flow
  • Jameson centered flux with Roe correction for transport equations.
  • Initial conditions : uniform state.
  • Time integration : backward Euler.
  • Convergence acceleration : low velocity preconditioning, mono-grid.
  • Implicit LU relaxation 'lussorsca'.
  • Local time step
  • 10000 iterations, CFL=10
  • BPROF-5DOM/Cf_gros_3C3D.jpeg
    BPROF-5DOM/Kp_gros_expe.jpeg
    BPROF-5DOM/r_theta_gros_3C3D.jpeg
    BPROF-5DOM/zresidu.jpeg

    Blade-7A-MPI

    (Back to top of page)

    Blade 7A Michel:

    Blade_7A_MPI.py3D configuration
    Multi-Domain
    Moving frame
    Navier-Stokes
    Michel turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
    Parallel
  • NS calculation
  • Rotationnal tip Mach number ---> M\_T = 0.617
  • Tip Rey ---> ReTIP=1930000.
  • aspect ratio ---> AR =15.
  • Rotation speed ---> \omega = M\_T / AR
  • Rotation axis ---> OZ
  • Translation speed ---> (0.,0.,0.)
  • Steady transonic turbulent viscous flow.
  • Turbulence model: Michel model .
  • Absolute velocity formulation.
  • Mesh 1:~69 \times 29 \times 97.
  • Mesh 2:~69 \times 29 \times 97.
  • Mesh 3:~69 \times 41 \times 33.
  • Mesh 4:~69 \times 41 \times 33.
  • Mesh 5:~41 \times 33 \times 81.
  • Mesh 6:~33 \times 29 \times 41.
  • Mesh 7:~113 \times 29 \times 41.
  • Jameson centered fluxes with artificial dissipation `dismrt'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration method (V cycle)
  • Local time step.
  • Adiabatic wall
  • Parallel computation, 4 processors
  • 1000 iterations, CFL=4.
  • Blade-7A-MPI/zresidu.jpeg
    Blade-7A-MPI/difftorque-row.jpeg

    Blunt-02

    (Back to top of page)

    Blunt Cylinder - Euler -Mach 16

    Blunt_02.py2D-Plane configuration
    Euler
    Backward-Euler
    Van Leer fluxes
    LU
  • Blunt Cylinder. Mach 16
  • Steady perfect gas flow.
  • Mesh :~31 \times 41 \times 2.
  • Van Leer fluxes with minmod limiter
  • Time integration: Backward Euler.
  • Implicit : lurelaxsca
  • 3000 iterations, CFL=50.
  • Blunt-02/Blunt-02-01.jpeg
    Blunt-02/Blunt-02-02.jpeg
    Blunt-02/zresidu.jpeg

    Blunt3D-RealGas

    (Back to top of page)

    Blunt Cylinder 3D - Steady real gas flow

    Blunt3D_RealGas.py3D configuration
    Multi-Domain
    Euler
    Backward-Euler
    LU
  • Blunt Cylinder 3D.
  • Steady real gas flow.
  • Mesh: 26 x 29 x 30
  • Roe scheme with minmod limiter.
  • Time integration: Backward Euler
  • 1000 iterations, variable CFL= 0.1 to 5.
  • Blunt3D-RealGas/blunt.jpeg
    Blunt3D-RealGas/gamp.jpeg
    Blunt3D-RealGas/zresdu.jpeg

    Bump-02

    (Back to top of page)

    Bump: Dual time step

    bBump_Dts.py2D-Plane configuration
    Navier-Stokes
    KEps turbulence model
    Runge-Kutta
    Dual time step
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
    Unsteady
  • 2-D transonic nozzle (B-bump).
  • Unsteady turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,\epsilon ).
  • Mesh:~ 181 \times 65 \times 2 .
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~Issued from unsteady solution at t=16.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Uniform time step = 0.1 .
  • 1 iteration on turbulent sub-system corresponding to 1 iteration on mean sub-system.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration (2 coarse grids, 3 iterations on coarse grids).
  • Dual time stepping method with maximum number of dual time step iterations = 500.
  • and convergence test on density = 1.e-2
  • 40 iterations in physical time step.
  • Final time ~:~20.
  • Bump-02/Bump-02_1.jpeg
    Bump-02/Bump-02_2.jpeg

    Bump-02-chim

    (Back to top of page)

    Bump: 2D Turbulent unsteady flow, dual time step

    Bump_02_chim_rep.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Runge-Kutta
    Dual time step
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Unsteady
  • 2-D transonic nozzle (B-bump).
  • Unsteady turbulent viscous flow.
  • Chimera context : Masks precise, depth = 2, interp : adt, explicit interpolation, DTS.
  • Turbulence model: 2 transport equations (k,\omega ).
  • Mesh:~ 125 \times 49 \times 2 , 57 \times 49 \times 2 , 181 \times 25 \times 2 .
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~Issued from 400 iterations of unsteady computation, itself coming from a converged steady solution.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Uniform time step = 0.1 .
  • 1 iteration on turbulent sub-system corresponding to 1 iteration on mean sub-system.
  • Implicit residual smoothing.
  • Dual time stepping method with maximum number of dual time step iterations = 100.
  • and convergence test on density = 1.e-2
  • 40 iterations in physical time step.
  • Final time ~:~44.
  • Bump-02-chim/Bump-02-chim_1.jpeg

    Bump-gear

    (Back to top of page)

    Bump: Gear method

    bump_gear.py2D-Plane configuration
    Navier-Stokes
    KEps turbulence model
    Runge-Kutta
    Dual time step
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
    Unsteady
  • 2-D transonic nozzle (B-bump).
  • Unsteady turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,\epsilon ).
  • Mesh:~ 181 \times 65 \times 2 .
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~Issued from unsteady solution at t=16.
  • Time integration:~Backwardeuler.
  • Uniform time step = 0.01 .
  • 1 iteration on turbulent sub-system corresponding to 1 iteration on mean sub-system.
  • Lurelaxsca.
  • Gear method with maximum number of sub time step iterations = 500.
  • and convergence test on density = 1.e-2
  • 4600 iterations in physical time step.
  • Final time ~:~62.
  • Bump-gear/Bump-gear_1.jpeg
    Bump-gear/Bump-gear_2.jpeg
    Bump-gear/Bump-gear_3.jpeg

    BumpB-auto

    (Back to top of page)

    Bump: Dual time step, automatic time step adaptation technique

    BumpB_auto.py2D-Plane configuration
    Navier-Stokes
    KEps turbulence model
    Runge-Kutta
    Dual time step
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
    Unsteady
  • 2-D transonic nozzle (B-bump).
  • Unsteady turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,\epsilon ).
  • Mesh:~ 181 \times 65 \times 2 .
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions: steady solution.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Automatic adaptation of time step.
  • 1 iteration on turbulent sub-system corresponding to 1 iteration on mean sub-system.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration (1 coarse grid, 3 iterations on coarse grid).
  • Dual time stepping method with maximum number of dual time step iterations = 800.
  • and convergence test on density = 5.e-3
  • Final time~:~16.49
  • BumpB-auto/BumpB-auto_1.jpeg

    BumpC-MKFLC2

    (Back to top of page)

    BumpC - 2D Turbulent MKFLC2 model

    BumpC_MKFLC2.py2D-Plane configuration
    Navier-Stokes
    MKFLC2 model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
  • 2-D transonic nozzle (c-bump).
  • Steady turbulent viscous flow.
  • Turbulence model: 4 transport equations (MKFLC2).
  • Mesh:~ 153 \times 65 \times 2 .
  • Jameson centered fluxes with scalar artificial dissipation
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions : from a converged computation.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid.
  • Local time step.
  • 4000 iterations, CFL=2.
  • BumpC-MKFLC2/BumpC-MKFLC2_1.jpeg
    BumpC-MKFLC2/zresidu.jpeg

    CASING-NM

    (Back to top of page)

    Channel with simulated casing

    CASING-NM.py3D configuration
    Multi-Domain
    Non-coincident quasi-conservative match
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Parallel
    Unsteady
  • Channel with simulated casing.
  • Steady subsonic turbulent viscous flow.
  • Wilcox turbulence model: 2 transport equations (k, w).
  • Adiabatic wall.
  • 4 blocks including about 60 000 cells.
  • Jameson centered fluxes for mean flow
  • with artificial dissipation `dissca': ~[1.0,~0.064].
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction coefficient :~0.03
  • Time integration:~backwardEuler.
  • Implicit :~scalar LU-SSOR.
  • Solved with the unsteady Gear method.
  • Initialization : uniform state at infinity.
  • 600 iterations, CFL 10..
  • CASING-NM/rate.jpeg
    CASING-NM/zresidu.jpeg

    CHIM-2D-01

    (Back to top of page)

    NACA0012 under a wall : Chimera, Euler, explicit

    chim_2d_01.py2D-Plane configuration
    3D treatment
    Multi-Domain
    Chimera
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    Explicit
  • No description

  • CHIM-2D-03

    (Back to top of page)

    NACA0012 under a wall : Chimera, Euler, IRS

    chim_2d_03.py2D-Plane configuration
    Multi-Domain
    Chimera
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • No description

  • CHIM-2D-ihc

    (Back to top of page)

    NACA0012 under a wall : Chimera, Euler

    CHIM_2D_ihc.py2D-Plane configuration
    Multi-Domain
    Chimera
    Euler
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
  • No description

  • COL2CYGNE-INJ-AXI

    (Back to top of page)

    Col de cygne avec injecteur axisymetrique decale

    COL2CYGNE_INJ_AXI.py3D configuration
    Multi-Domain
    Chimera
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • Turbomachinery configuration.
  • Inter-blade channel (col de cygne) with injector in shifted axisymmetric configuration.
  • Field of calculation: 2 blocks for the azimuth field of the channel
  • and one for the system of blowing covering the channel partially.
  • Multi-block Chimera mesh.
  • Chimera periodic technique.
  • Steady Navier-Stokes equations with Spalart-Allmaras model.
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction (dismrt).
  • Time integration: Runge-Kutta 4 steps with freezing.
  • Implicit Residual Smoothing.
  • CFL=2, 10000 iterations.
  • COL2CYGNE-INJ-AXI/mesh_channel_injector.jpeg
    COL2CYGNE-INJ-AXI/coupe_i38.jpeg
    COL2CYGNE-INJ-AXI/coupes_jmin_centre_jmax.jpeg
    COL2CYGNE-INJ-AXI/zresidu.jpeg

    COL2CYGNE-INJ-NONAXI

    (Back to top of page)

    Col de cygne avec injecteur non axisymetrique decale

    COL2CYGNE_INJ_NONAXI.py3D configuration
    Multi-Domain
    Chimera
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • Turbomachinery configuration.
  • Inter-blade channel (col de cygne) with injector in shifted non-axisymmetric configuration.
  • Field of calculation: 2 blocks for the azimuth field of the channel
  • and one for the system of blowing covering the channel partially.
  • Multi-block Chimera mesh.
  • Chimera periodic technique.
  • Steady Navier-Stokes equations with Spalart-Allmaras model.
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction (dismrt).
  • Time integration: Runge-Kutta 4 steps with freezing.
  • Implicit Residual Smoothing.
  • CFL=2, 10000 iterations.
  • COL2CYGNE-INJ-NONAXI/export1.jpeg
    COL2CYGNE-INJ-NONAXI/coupes_jmin_centre_jmax.jpeg
    COL2CYGNE-INJ-NONAXI/zresidu.jpeg

    COMPRESSOR-PI9-MXPL

    (Back to top of page)

    AXIAL COMPRESSOR STAGE rotor-stator

    COMPRESSOR_PI9_MXPL.py3D configuration
    Multi-Domain
    Turbomachinery multi-stage match
    Moving frame
    KL turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
    Parallel
  • AXIAL COMPRESSOR STAGE rotor-stator.
  • Steady subsonic turbulent viscous flow.
  • Turbulence model :~ k-l Smith 2-transport equation model.
  • Moving Frame :~ No translation - Rotation axis Ox
  • Formulation :~ relative velocity / rotating frame.
  • Jameson centered fluxes with artificial dissipation `dismrt' for mean flow.
  • Roe scheme for transport equations.
  • Harten correction :~ 0.15.
  • Time integration :~ Backward Euler.
  • Implicit scalar LU-Relax :~ 4 relaxation sweeps.
  • Mixing plane condition at stator-rotor interface.
  • Multigrid convergence acceleration method (2 coarse grids).
  • Parallel computation on 5 processors.
  • 3000 iterations, CFL=40.
  • COMPRESSOR-PI9-MXPL/convflux_ro.jpeg
    COMPRESSOR-PI9-MXPL/mixingplane_view.jpeg

    COMPRESSOR-STAGE-CHORO

    (Back to top of page)

    Subsonic axial compressor, NS + SA, Chorochronic condition

    COMPRESSOR_STAGE_CHORO.py3D configuration
    Multi-Domain
    Turbomachinery multi-stage match
    Moving frame
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • No description

  • COMPRESSOR-STAGE-CHORO-2

    (Back to top of page)

    Reprise du cas COMPRESSOR-STAGE-CHORO

    COMPRESSOR_STAGE_CHORO_2.py3D configuration
    Multi-Domain
    Turbomachinery multi-stage match
    Moving frame
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • AXIAL COMPRESSOR STAGE rotor-stator : light configuration at mid-span.
  • Unsteady subsonic turbulent viscous flow on one unsteady Stator period (240 time-steps).
  • Rerun of former unsteady computation performed on 90 stator periods.
  • Turbulence model :~ k-l Smith 2-transport equation model.
  • Moving Frame :~ No translation - Rotation axis Ox
  • Formulation :~ relative velocity / rotating frame.
  • Mesh :~8 blocks (Total : 86040 cells) with (OHHH)-(OHHH) topology, 7 radial planes at mid-span.
  • Jameson centered fluxes with artificial dissipation `dissca' for mean flow.
  • Roe scheme for transport equations.
  • Harten correction :~ 0.1
  • Time integration :~ Runge-Kutta
  • Implicit Residual Smoothing
  • Global time step.
  • Initial conditions :~ unsteady computation with chorochronic technique (90 stator periods)
  • Adiabatic walls.
  • Chorochronic condition applied on periodic azimutal boundaries.
  • Chorochronic condition applied on rotor-stator interface boundaries.
  • COMPRESSOR-STAGE-CHORO-2/rok.jpeg
    COMPRESSOR-STAGE-CHORO-2/debit.jpeg

    CT6-BW-SA-SSOR-dts

    (Back to top of page)

    Ct6 : ALE, Lussor, Spalart, steady

    ct6_bw_lussorsca_dts_10_spalart.py2D-Plane configuration
    Multi-Domain
    ALE
    Spalart-Allmaras turbulence model
    Backward-Euler
    Dual time step
    Jameson fluxes
    Scalar Dissipation
    LU
  • 2D-Plane multiblock configuration
  • Two Meshes:~209 \times 97 \times 2.
  • Unsteady inviscid perfect gas flow.
  • Turbulence model: 1 transport equation (Spalart-Allmaras).
  • Deformation without rigid body motion.
  • Transfinite interpolation algorithm for mesh deformation
  • Rotation speed ---> ~\omega~=~0., no translation speed
  • Mean angle and harmonics of deformation:
  • alp0~=~0.
  • alp1s~=~1.01 degre
  • alp1c~=~alp2c~=~alp2s~=~0.
  • Wing motion ---> alp(t)~=~alp0 + alp1s*sin(\omega*t)
  • Dual time stepping, 50 dual iterations.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~.5~,~0.016~,~.5~].
  • Time integration:~ Backward-Euler.
  • Implicit scalar LU-SSOR (4 sub-sycles)
  • Time step = 0.41283815
  • Multigrid convergence acceleration (2 coarse grids, 2 iterations on coarse grid).
  • 100 iterations.
  • CT6-BW-SA-SSOR-dts/mach.jpeg
    CT6-BW-SA-SSOR-dts/frictionmodulus.jpeg
    CT6-BW-SA-SSOR-dts/convflux_rou.jpeg
    CT6-BW-SA-SSOR-dts/convflux_row.jpeg

    Caimen-05

    (Back to top of page)

    3D Wing: Multidimensional slip

    as28Caimen1s2_sca.py3D configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • 3D S3CH wing part.
  • Steady transonic perfect gas flow.
  • Mesh:~`1 point over 2' 101 \times 23 \times 26.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Multi-dimensional extrapolation slip boundary condition.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 1200 iterations, CFL=5.
  • Caimen-05/Caimen-05_1.jpeg
    Caimen-05/zresidu.jpeg

    Caimen-08

    (Back to top of page)

    3D Wing: Partially Coincident Matching

    as28CaimenPartRac.py3D configuration
    Multi-Domain
    Partially coincident match
    Euler
    Runge-Kutta
    Jameson fluxes
    IRS
  • 3D S3CH wing part.
  • Steady transonic perfect gas flow.
  • Mesh cut into 2 blocks:~51 \times 23 \times 51 and 101 \times 45 \times 51
  • with fine-coarse matching.
  • Jameson centered fluxes with artificial dissipation 'dissca',('av\_type'=1).
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 1500 iterations, CFL=10.
  • Caimen-08/Caimen-08_1.jpeg
    Caimen-08/zresidu.jpeg

    Caimen-10

    (Back to top of page)

    3D Wing: Matrix Viscosity, LDU

    as28Caimen1s2_mat_LDU.py3D configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Matrix Dissipation
    LU
  • 3D S3CH wing part.
  • Steady transonic perfect gas flow.
  • Mesh : 1 domain with 101x23x26 mesh points (1 point over 2).
  • Jameson centered fluxes with artificial dissipation `dismat'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit:~LU-Relax matrix.
  • Local time step.
  • 1500 iterations, CFL=5.
  • Caimen-10/Caimen-10_1.jpeg
    Caimen-10/Caimen-10_2.jpeg
    Caimen-10/Caimen-10_3.jpeg

    Compressor-CME2-OptAdj

    (Back to top of page)

    Compressor CME2 - KL - Shape Optimization (adjoint gradient computation)

    Compressor_CME2_OptAdj.py3D configuration
    Multi-Domain
    Shape optimization adjoint equation
    Moving frame
    Navier-Stokes
    KL turbulence model
    Backward-Euler
    Roe fluxes
    LU
  • Rotating blade. k-l model Navier-Stockes
  • Gradient computation by adjoint method, seconde order Roe upwind fluxes.
  • Relative velocity and relative frame
  • Time integration :~ Backward Euler.
  • Implicit LU.
  • CFL =~ 40.
  • Compressor-CME2-OptAdj/zresidu1.jpeg
    Compressor-CME2-OptAdj/zresidu2.jpeg

    DGV-C2-LS

    (Back to top of page)

    Helico DGV, NS, k-l, Multigrid, Low speed preconditionning

    C20087_gk6.py3D configuration
    Multi-Domain
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
    Low speed preconditionning
  • Helicopter fuselage ASF1-C2, Mach=0.087
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 10 blocks including 1242642 cells.
  • Jameson centered fluxes with artificial dissipation `dismrt'.
  • Time integration :~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration method (V cycle)
  • Low speed preconditionning.
  • Local time step.
  • 4980 iterations, cfl=4.
  • DGV-C2-LS/ASF1-C2-LS_1.jpeg
    DGV-C2-LS/ASF1-C2-LS_2.jpeg
    DGV-C2-LS/CP.jpeg
    DGV-C2-LS/zresidu.jpeg

    DebitGlobal-01

    (Back to top of page)

    Total Mass Flow Rate

    DebitGlobal_01.py3D configuration
    Multi-Domain
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • 3D nacelle, alpha=5 deg.
  • Steady transonic perfect gas flow.
  • Meshes: ~ 5 blocks (31 \times 19 \times 7, 51 \times 19 \times 7, 99 \times 19 \times 7, 9 \times 19 \times 13, 65 \times 19 \times 9 ).
  • Global mass flow rate condition.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~1.~,~0.032~,~0.5~].
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 5000 iterations, variable CFL = 5.
  • DebitGlobal-01/debit.jpeg
    DebitGlobal-01/mach.jpeg
    DebitGlobal-01/iterro.jpeg

    DebitGlobal-MPI

    (Back to top of page)

    Total Mass Flow Rate

    DebitGlobal_MPI.py3D configuration
    Multi-Domain
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Parallel
  • 3D nacelle, alpha=5 deg.
  • Steady transonic perfect gas flow.
  • Meshes: ~ 5 blocks (31 \times 19 \times 7, 51 \times 19 \times 7, 99 \times 19 \times 7, 9 \times 19 \times 13, 65 \times 19 \times 9 ).
  • Global mass flow rate condition.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~1.~,~0.032~,~0.5~].
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Parallel computation, 4 processors
  • 5000 iterations, variable CFL = 5.
  • DebitGlobal-MPI/debit.jpeg
    DebitGlobal-MPI/mach.jpeg
    DebitGlobal-MPI/iterro.jpeg

    Dyvas-AEL

    (Back to top of page)

    Dyvas - wing - fuselage

    elsaflex.py3D configuration
    Multi-Domain
    ALE
    KO turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
    Parallel
  • DYVAS wing/fuselage configuration.
  • M_{\inf}~=~0.839~,~\alpha~=~0.53~,~Re_{\inf}~=~3.62~10^6.
  • Static fluid/structure coupling using a reduced flexibility matrix (turbulent transonic flow).
  • Turbulence model~: 2 transport equations Wilcox (k,\Omega) with Zheng limitor.
  • Initial conditions~: from uniform state.
  • Mesh:~16 blocks, around 1 100 000 nodes.
  • Jameson centered fluxes for mean equations with scalar artificial dissipation [~0.5~,~0.032~,~1.0~] and Martinelli correction [~0.3~].
  • Jameson centered fluxes with Roe correction for transport equations (Value of Harten correction coefficient : 0.01)
  • Time integration :~Runge-Kutta.
  • Implicit Residual Smoothing.
  • Multigrid : V-cycle, 1 coarse grid, 3 iterations on coarse grid.
  • Local time step, CFL=4.
  • 2000 iterations = 20 cycles of fluid/structure coupling (each cycle = 100 CFD iterations)
  • Parallel calculation on 2 processors.
  • Dyvas-AEL/surfdef.jpeg
    Dyvas-AEL/cp.jpeg
    Dyvas-AEL/zresidu.jpeg

    ELECTRE-LAM

    (Back to top of page)

    Electre (axisym) configuration

    electre.py2D-Axi configuration
    Navier-Stokes
    Laminar
    Backward-Euler
    Roe fluxes
    LU
  • 2D axisymmetric Electre configuration
  • Steady laminar viscous flow.
  • Mesh: ~ 1 block (70 \times 140 \times 2)
  • Initial field : uniform external state.
  • Second order Roe upwind fluxes (minmod limiter).
  • Positivity forced: cutoff\_dens=.01, cutoff\_pres=.002
  • Time integration:~ Backward Euler.
  • Implicit : LUSSOR scalar.
  • Local time step.
  • 10000 iterations, variable CFL = 0.5 to 3.
  • ELECTRE-LAM/isoMach.jpeg
    ELECTRE-LAM/Mach.jpeg
    ELECTRE-LAM/Temp.jpeg
    ELECTRE-LAM/zresidu.jpeg

    FUS-STRUT-HUB

    (Back to top of page)

    x

    FUS_STRUT_HUB.py3D configuration
    Multi-Domain
    Chimera
    KL turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
    Low speed preconditionning
  • Dauphin helicopter configuration : ~V~=15~m/s~~\alpha~=~-3~deg..
  • Fuselage + hub + strut + actuator for the unique rotor.
  • Steady transonic turbulent viscous flow.
  • Smith turbulence model: 2 transport equations (k , l).
  • Adiabatic wall.
  • Multi-block Chimera mesh :
  • 108 blocks (among them, 97 for the fuselage) including about 8.3 million points.
  • Chimera context : Mask "cartesian elts", depth=1, interp=adt, explicit interpolation, "double wall".
  • Jameson centered fluxes for mean flow
  • with artificial dissipation `dismrt': ~[0.5,~0.016,~1.,~0.33].
  • and "av\_border" = current ; "av\_formul" = current .
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction coefficient :~0.01
  • Time integration:~backwardEuler.
  • Implicit :~scalar LU-SSOR.
  • Multigrid convergence acceleration method (1 coarse grid).
  • Multigrid : extrapolation boundary conditions for the Chimera boundary conditions.
  • Low speed preconditioning :
  • "gk" parameter decreasing from 300. to 10. from IT=100 to IT=500~ .
  • Local time step.
  • Initialization : uniform state at infinity.
  • 750 iterations, CFL increasing from 10. to 100. from IT=100 to IT=400~.
  • FUS-STRUT-HUB/Kp.jpeg
    FUS-STRUT-HUB/drag_distcomp.jpeg
    FUS-STRUT-HUB/lift_distcomp.jpeg
    FUS-STRUT-HUB/Kp_up_down.jpeg
    FUS-STRUT-HUB/zresidu.jpeg

    FanBlade-S1MA-OptLin

    (Back to top of page)

    3D Fan Blade S1MA - Euler - Shape Optimization (linearized gradient computation)

    FanBlade_S1MA_OptLin.py3D treatment
    Multi-Domain
    Shape optimization linearized equation
    Moving frame
    Euler
    Backward-Euler
    Roe fluxes
    LU
  • Rotating blade (S1 Modane wind tunel blades).
  • Euler equations, gradient computation by linearized method, second order Roe upwind fluxes.
  • Relative velocity and relative frame
  • Time integration :~ Backward Euler.
  • Implicit LU
  • CFL =~ 3.
  • FanBlade-S1MA-OptLin/zresidu2.jpeg

    H8Y

    (Back to top of page)

    3D Wing/Body NS k-omega

    E_LU_MG3W2_cfl50_v3p_1.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
    Low speed preconditionning
  • 3-Element Wing/Body high lift configuration
  • M~=~0.175~\alpha~=~16.~deg~Re_{AMC}~=~1.341~10^6
  • Mesh : 46 blocks, 3 079 630 nodes
  • Steady subsonic turbulent flow.
  • Low speed preconditioning.
  • Turbulence model : (k,\omega) Wilcox with Zheng limitor (kok\_diff\_cor=1)
  • Wall distance calculation along grid lines
  • Jameson centered fluxes (divergence form) for mean flow
  • with artificial dissipation "dismrt" : 0.5 0.032 1.0 0.5
  • Border treatment "dif0null" for artificial viscosity
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction : 0.05
  • Gradients calculated on cell centers
  • Time integration : backward Euler
  • Implicit scalar LU-Relax : 4 relaxation sweeps, relaxscatype=viscous\_3p
  • Multigrid acceleration method on the mean equation sub-system :
  • 2 coarse grids, W cycle, synchronous restriction,
  • arithmetic correction transfer on coarse grid,
  • correction transfer 'inv\_topo' from coarse to fine grid,
  • cell to node prolongation
  • artificial dissipation coefficients in coarse grids : 0.5 0.032 (1st) 1. 0. (2nd)
  • 2 sub-iterations for the turbulence sub-system
  • No filter to force field positivity.
  • Initialization : uniform flow (coeffmutinit =1. after 10 it.)
  • 1001 iterations, CFL=50. (option timestep\_div 'divided')
  • H8Y/Cp.jpeg
    H8Y/zresidu.jpeg

    H8Y-A-KO

    (Back to top of page)

    3D Wing/Body NS k-omega - Lussor

    H8Y_A_KO.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
    Low speed preconditionning
  • 3-Element Wing/Body high lift configuration
  • M~=~0.175~\alpha~=~16.~deg~Re_{AMC}~=~1.341~10^6
  • Mesh : 46 blocks, 3 079 630 nodes
  • Steady subsonic turbulent flow.
  • Low speed preconditioning.
  • Turbulence model : (k,\omega) Wilcox with Zheng limitor, no SST correction
  • Wall distance calculation : "mininterf" option
  • Jameson centered fluxes (skew-symmetric form) for mean flow
  • with artificial dissipation "dissca" : 0.0 0.032 1.0 (only 4th order dissipation)
  • Border treatment "dif0null" for artificial viscosity
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction : 0.01
  • Gradients calculated on cell centers with correction on interfaces (5p\_cor)
  • Time integration : backward Euler
  • Implicit scalar LU-SSOR : 4 relaxation sweeps
  • Multigrid acceleration method on the mean equation sub-system :
  • 2 coarse grids, V cycle, synchronous restriction,
  • Volume correction transfer on coarse grid,
  • correction transfer 'bilin\_topo' from coarse to fine grid,
  • cell to cell prolongation 'cell2cell\_c'
  • Zero artificial dissipation on coarse grids
  • 2 sub-iterations for the turbulence sub-system
  • Initialization : uniform flow
  • 700 iterations, CFL=5. (option timestep 'directional')
  • H8Y-A-KO/Cp.jpeg
    H8Y-A-KO/zresidu.jpeg

    H8Y-A-SA

    (Back to top of page)

    3D Wing/Body NS Spalart-Allmaras - Lussor

    H8Y_A_SA.py3D configuration
    Multi-Domain
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
    Low speed preconditionning
  • 3-Element Wing/Body high lift configuration
  • M~=~0.175~\alpha~=~16.~deg~Re_{AMC}~=~1.341~10^6
  • Mesh : 46 blocks, 3 079 630 nodes
  • Steady subsonic turbulent flow.
  • Low speed preconditioning.
  • Turbulence model : Spalart-Allmaras (k,\omega) Wilcox with Zheng limitor, no SST correction
  • Wall distance calculation : "mininterf" option
  • Jameson centered fluxes (skew-symmetric form) for mean flow
  • with artificial dissipation "dissca" : 0.5 0.032 1.0
  • Border treatment "dif0null" for artificial viscosity
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction : 0.01
  • Gradients calculated on cell centers with correction on interfaces (5p\_cor)
  • Time integration : backward Euler
  • Implicit scalar LU-SSOR : 4 relaxation sweeps
  • Multigrid acceleration method on the mean equation sub-system :
  • 2 coarse grids, V cycle, synchronous restriction,
  • Volume correction transfer on coarse grid,
  • correction transfer 'bilin\_topo' from coarse to fine grid,
  • cell to cell prolongation 'cell2cell\_c'
  • Zero artificial dissipation on coarse grids
  • 2 sub-iterations for the turbulence sub-system
  • Initialization : uniform flow
  • 700 iterations, CFL=5. (option timestep 'directional')
  • H8Y-A-SA/zresidu.jpeg
    H8Y-A-SA/Cp.jpeg

    Hirett-2D-Adj

    (Back to top of page)

    HiRett 2D - Euler - Shape Optimization

    hirett_2d_optadj.py2D-Plane configuration
    Multi-Domain
    Shape optimization adjoint equation
    Euler
    Backward-Euler
    Roe fluxes
    LU
  • Hirett 2D Airfoil. M_{\inf}~=~0.78~,~\alpha~=~0.3~.
  • Mesh: 2 blocks with 65~\times~33~\times~2 nodes in each block.
  • Steady transonic inviscid flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=5.
  • Second order Roe Upwind flux (van Albada limiter).
  • Time integration: backward Euler.
  • Gradient computation: adjoint method.
  • Calculation of pressure drag coefficient CD_{p} gradient.
  • One shape parameter : cf Airbus F.
  • Hirett-2D-Adj/adj1-rho.jpeg
    Hirett-2D-Adj/zresidu1.jpeg
    Hirett-2D-Adj/zresidu2.jpeg

    Hirett-A-KO

    (Back to top of page)

    HiReTT Wing/Body - komega-wilcox

    Hirett_A_KO.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • HiReTT Wing/Body
  • M~=~0.848~\alpha~=~1.573~deg~Re_{AMC}~=~32.37~10^6.
  • Mesh : 19 blocks, 4 062 755 nodes
  • Steady transonic turbulent flow.
  • Turbulence model : (k, \omega) Wilcox model, Zheng limitor, no SST correction
  • Wall distance calculation "mininterf"
  • Jameson centered fluxes (skew-symmetric form) for mean flow
  • with artificial dissipation "dissca" : 0.5 0.016 1.0
  • with dissipation reduction in all directions based on normal speed values
  • Border treatment "dif0null" for artificial viscosity
  • First-order centered fluxes for transport equations
  • Gradients calculated on cell centers, then corrected on interfaces ("5p\_cor")
  • Extrapolation to wall border for mean gradients and turbulent gradients
  • Time integration : backward Euler
  • Implicit scalar LU-SSOR : 4 relaxation sweeps
  • Multigrid acceleration method on the mean equation sub-system :
  • 2 coarse grids, V-cycle, synchronous restriction,
  • volumetric correction transfer on coarse grid,
  • correction transfer 'bilin\_topo' from coarse to fine grid,
  • cell to cell prolongation 'cell2cell\_c',
  • artificial viscosity coefficients in coarse grid : 0.5 0.
  • 1 sub-iteration for the turbulence sub-system
  • Filter "incr\_new+prolong" to force field positivity.
  • Initialization : uniform flow
  • Timestep evaluation per direction ("timestep\_type directional")
  • 500 iterations, CFL=100. (with linear evolution from CFL=1. during first 68 it.)
  • Hirett-A-KO/profiles_extrados.jpeg
    Hirett-A-KO/profiles_intrados.jpeg
    Hirett-A-KO/coupes_pression.jpeg
    Hirett-A-KO/residus_efforts_time.jpeg
    Hirett-A-KO/residus_efforts_cycles.jpeg
    Hirett-A-KO/residus_efforts_cycles_2.jpeg
    Hirett-A-KO/zresidu.jpeg

    Hirett-A-SA

    (Back to top of page)

    HiReTT Wing/Body - Spalart

    Hirett_A_SA.py3D configuration
    Multi-Domain
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • HiReTT Wing/Body
  • M~=~0.848~\alpha~=~1.573~deg~Re_{AMC}~=~32.37~10^6.
  • Mesh : 19 blocks, 4 062 755 nodes
  • Steady transonic turbulent flow.
  • Turbulence model : Spalart-Allmaras
  • Wall distance calculation "mininterf"
  • Jameson centered fluxes (skew-symmetric form) for mean flow
  • with artificial dissipation "dissca" : 0.5 0.016 1.0
  • with dissipation reduction in all directions based on normal speed values
  • Border treatment "dif0null" for artificial viscosity
  • First-order centered fluxes for transport equations
  • Gradients calculated on cell centers, then corrected on interfaces ("5p\_cor")
  • Extrapolation to wall border for mean gradients and turbulent gradients
  • Time integration : backward Euler
  • Implicit scalar LU-SSOR : 4 relaxation sweeps
  • Multigrid acceleration method on the mean equation sub-system :
  • 2 coarse grids, V-cycle, synchronous restriction,
  • volumetric correction transfer on coarse grid,
  • correction transfer 'bilin\_topo' from coarse to fine grid,
  • cell to cell prolongation 'cell2cell\_c',
  • artificial viscosity coefficients in coarse grid : 0.5 0.
  • 1 sub-iteration for the turbulence sub-system
  • Filter "incr\_new+prolong" to force field positivity.
  • Initialization : uniform flow
  • Timestep evaluation per direction ("timestep\_type directional")
  • 500 iterations, CFL=100. (with linear evolution from CFL=1. during first 68 it.)
  • Hirett-A-SA/profiles_extrados.jpeg
    Hirett-A-SA/profiles_intrados.jpeg
    Hirett-A-SA/coupes_pression.jpeg
    Hirett-A-SA/residus_efforts_time.jpeg
    Hirett-A-SA/residus_efforts_cycles.jpeg
    Hirett-A-SA/residus_efforts_cycles_2.jpeg
    Hirett-A-SA/zresidu.jpeg

    Hirett-MS-01

    (Back to top of page)

    x

    LURELAX_1_p10.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • No description

  • Hirett-MS-02

    (Back to top of page)

    x

    LURELAX_2_p10.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • No description

  • Hirett-MS-03

    (Back to top of page)

    HiReTT Wing/Body - Kok with Zheng limitor

    LURELAX_3_p10.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • HiReTT Wing/Body
  • M~=~0.848~\alpha~=~1.573~deg~Re_{AMC}~=~32.37~10^6.
  • Mesh : 19 blocks, 4 062 755 nodes
  • Steady transonic turbulent flow.
  • Turbulence model : (k,\omega) Kok with Zheng limitor (kok\_diff\_cor=0)
  • Wall distance calculation along grid lines
  • Jameson centered fluxes (divergence form) for mean flow
  • with artificial dissipation "dismrt" : 0.5 0.016 1.0 0.5
  • Border treatment "current" for artificial viscosity
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction : 0.01
  • Gradients calculated on cell centers
  • Time integration : backward Euler
  • Implicit scalar LU-Relax : 2 relaxation sweeps, relaxscatype=viscous\_5p
  • Multigrid acceleration method on the mean equation sub-system :
  • 2 coarse grids, V-cycle, synchronous restriction,
  • arithmetic correction transfer on coarse grid,
  • correction transfer 'inv\_topo' from coarse to fine grid,
  • cell to node prolongation
  • artificial dissipation coefficients in coarse grids : 1.0 0.032
  • 2 sub-iterations for the turbulence sub-system
  • No filter to force field positivity.
  • Initialization : from mesh sequencing (500 it. on each of the 2 coarse grids)
  • 1002 iterations, CFL=50.
  • Hirett-MS-03/residus_efforts_time.jpeg
    Hirett-MS-03/zresidu.jpeg
    Hirett-MS-03/residus_efforts_cycles_2.jpeg
    Hirett-MS-03/profiles_extrados.jpeg
    Hirett-MS-03/coupes_pression.jpeg
    Hirett-MS-03/residus_efforts_cycles.jpeg
    Hirett-MS-03/profiles_intrados.jpeg

    IHT-MULTIMODEL

    (Back to top of page)

    Homogeneous isotropic turbulence with free decaying

    IHT_MULTIMODEL.py3D configuration
    Large Eddy Simulation model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    Explicit
    Unsteady
  • Homogeneous isotropic turbulence (HIT) with free decaying.
  • Mesh : cubic box of size 2*Pi.
  • Periodicity applied on all the boundaries of the cubic box.
  • Computation with the following subb-grid scale models :
  • - Smagorinsky with selective function
  • - Smagorinsky without selective function
  • - Structure function
  • - Filtered structure function
  • Time discretization : Runge-Kutta (RK4).
  • Space discretization : Jameson centered scheme with artificial dissipation.
  • Resolution method : Explicit phase.
  • 4000 iterations. Cfl = 1.0
  • IHT-MULTIMODEL/thi_1.jpeg

    LS89

    (Back to top of page)

    Turbine Turbulent Spalart

    LS89.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • VKI LS89 - 3D.
  • Steady Navier-Stokes equations with Spalart model.
  • Mesh : O block domain with 273~\times~37~\times~2 points ;
  • H2 block domain with 25~\times~49~\times~2 points ;
  • H3 block domain with 129~\times~33~\times~2 points ;
  • H4 block domain with 25~\times~65~\times~2 points ;
  • Translation periodicity.
  • Initial field : from K-L solution.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~1~,~0.064~,~1~].
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=10.
  • LS89/LS89_1.jpeg
    LS89/LS89_2.jpeg
    LS89/zresidu.jpeg

    LS89-KO

    (Back to top of page)

    Turbine Turbulent Kok

    LS89_KO.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • VKI LS89 - 3D.
  • Steady Navier-Stokes equations with Spalart model.
  • Mesh : O block domain with 273~\times~37~\times~2 points ;
  • H2 block domain with 25~\times~49~\times~2 points ;
  • H3 block domain with 129~\times~33~\times~2 points ;
  • H4 block domain with 25~\times~65~\times~2 points ;
  • Translation periodicity.
  • Initial field : from K-L solution.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.032~,~1~].
  • Time integration : Backward-Euler
  • Implicit phase: LUssor-sca
  • Local time step.
  • Multigrid: V-cycle, 1 coarse grid
  • 3000 iterations, CFL=100.
  • LS89-KO/LS89_1.jpeg
    LS89-KO/LS89_2.jpeg
    LS89-KO/zresidu.jpeg

    MARCO-KEPS

    (Back to top of page)

    Axisymmetric MARCO Nozzle

    MARCO_KEPS.py2D-Axi configuration
    Multi-Domain
    Navier-Stokes
    KEps turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • 2D axisymmetric MARCO nozzle.
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (k,\epsilon ).
  • Meshes: ~ 3 blocks (349 \times 49 \times 2, 349 \times 49 \times 2, 349 \times 13 \times 2).
  • Initial field : 20 laminar iterations starting from uniform external state.
  • Jameson centered fluxes with artificial dissipation `dismrt' : [~1.~,~0.032~,~1~,~0.333~].
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 5000 iterations, CFL = 2.
  • MARCO-KEPS/marco-mach.jpeg
    MARCO-KEPS/marco-mut.jpeg
    MARCO-KEPS/marco-pi.jpeg
    MARCO-KEPS/marco-axis.jpeg
    MARCO-KEPS/zresidu.jpeg

    MARCO-KEPS-AXISOURCE

    (Back to top of page)

    Axisymmetric MARCO Nozzle

    MARCO_KEPS_AXISOURCE.py2D-Axi configuration
    Multi-Domain
    Navier-Stokes
    KEps turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
  • 2D axisymmetric MARCO nozzle.
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (k,\epsilon ).
  • Meshes: ~ 3 blocks (349 \times 49 \times 2, 349 \times 49 \times 2, 349 \times 13 \times 2).
  • Initial field : 20 laminar iterations starting from uniform external state.
  • Jameson centered fluxes with artificial dissipation `dismrt' : [~1.~,~0.032~,~1~,~0.333~].
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Scalar LUSSOR implicit.
  • Axisymmetric formulation with source terms.
  • 2 coordinates input mesh.
  • Local time step.
  • 5000 iterations, CFL = 3.
  • MARCO-KEPS-AXISOURCE/marco-mach.jpeg
    MARCO-KEPS-AXISOURCE/marco-mut.jpeg
    MARCO-KEPS-AXISOURCE/marco-pi.jpeg
    MARCO-KEPS-AXISOURCE/marco-axis.jpeg
    MARCO-KEPS-AXISOURCE/zresidu.jpeg

    MARCO-VENTI-KEPS

    (Back to top of page)

    Axisymmetric MARCO Nozzle with ventilation

    MARCO_VENTI_KEPS.py2D-Axi configuration
    Multi-Domain
    Navier-Stokes
    KEps turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • 2D axisymmetric MARCO nozzle.
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (k,\epsilon ).
  • Meshes: ~ 3 blocks (397 \times 49 \times 2, 497 \times 49 \times 2, 497 \times 81 \times 2).
  • Initial field : a converged solution with inj1 boundary condition for ventilation.
  • Local mass flow rate injection condition.
  • Jameson centered fluxes with artificial dissipation `dismrt' : [~0.5~,~0.032~,~1~,~0.333~].
  • Harten correction : 0.1.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Multigrid.
  • 1000 iterations, CFL=3.
  • MARCO-VENTI-KEPS/marco-venti.jpeg
    MARCO-VENTI-KEPS/zresidu.jpeg

    NACA-CHIM-DBWALL

    (Back to top of page)

    naca chimere double wall

    NACA_DBWALL.py3D treatment
    Multi-Domain
    Chimera
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
  • NACA0012 wing profile double wall.
  • Chimera context : Masks carts\_elmts \& infinite plane, depth = 2, interp : icg, explicit interpolation, double wall.
  • Infinite flow conditions : {M\_\infty}~=~0.80, {p\_\infty}~=~10.000~Pa, {\rho\_\infty}~=~1.29~kg.m^{-3}.
  • Multi-domain with overlapping (Chimera).
  • Steady transonic turbulent flow.
  • Turbulence model : (k, \omega)
  • Mesh NACA0012 :~33 \times 193 \times 2.
  • Mesh Wall :~100 \times 88 \times 2.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration: Backwardeuler.
  • LU-Relax scalar.
  • Local time step.
  • 3000 iterations, CFL=50.
  • NACA-CHIM-DBWALL/NACA_DBWALL_portance.jpeg
    NACA-CHIM-DBWALL/zresidu.jpeg

    OAT15A

    (Back to top of page)

    OAT15A + Spalart + Unsteady

    OAT15A.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Backward-Euler
    Dual time step
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
    Unsteady
  • 2D wing profile with troncated trailing edge (OAT15A profile)
  • Infinite flow : M~=~0.73~~\alpha~=~5.~~Re_{inf}~=~4.3~10^6
  • Unsteady turbulent viscous flow.
  • Turbulence model : Spalart
  • Mesh : 2 blocks 317 \times 121 \times 2 and 93 \times 289 \times 2
  • Jameson centered fluxes with artificial dissipation "dismrt" (Martinelli correction)
  • Jameson centered fluxes with Roe correction for transport equations
  • (Low value of Harten correction coefficient : 0.01).
  • Time integration : Backward Euler.
  • Dual time stepping.
  • Implicit LuSsorSca.
  • Multigrid (2 coarse grids, V cycle)
  • Initial conditions : uniform conditions at infinity.
  • 300 iterations.
  • OAT15A/OAT15A-1.jpeg
    OAT15A/OAT15A-2.jpeg

    OAT15A-Vrt

    (Back to top of page)

    OAT15A - KL+Interm.+WL+Vort. - 2 doms

    OAT15A_Vrt.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    KL turbulence model
    Wall law
    Prescribed transition
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • 2D wing profile with troncated trailing edge (OAT15A profile)
  • Infinite flow : M~=~0.74~~\alpha~=~0.9~~Re_{inf}~=~3.0~10^6
  • Steady transonic turbulent viscous flow.
  • Turbulence model : 2 transport equations (k,l)
  • Wall law.
  • Intermittency file :
  • Exact (i.e. min. values) calculation of distance to wall.
  • Flow is assumed to be laminar around the leading edge.
  • (from i~=~75 to i~=~119,
  • i.e. x~=~0.0703 on the lower side and x~=~0.0656 on the upper side).
  • On outer boundary, non-reflective vorticity boundary condition is used.
  • (A meaningful comparison with experiment requires the use of the vorticity condition.)
  • Mesh : 2 blocks 193 \times 48 \times 2 and 49 \times 105 \times 2
  • Jameson centered fluxes with artificial dissipation "dissca".
  • Jameson centered fluxes with Roe correction for transport equations
  • (Low value of Harten correction coefficient : 0.02).
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Initial conditions : uniform conditions at infinity.
  • 10000 iterations, CFL=2
  • OAT15A-Vrt/OAT15A-Vrt_1.jpeg
    OAT15A-Vrt/OAT15A-Vrt_2.jpeg
    OAT15A-Vrt/zresidu.jpeg

    OAT15A-VrtSST

    (Back to top of page)

    OAT15A - k-omega SST - Interm. - WL - Vort. - 2 doms

    OAT15A_VrtSST.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Wall law
    Prescribed transition
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • 2D wing profile with troncated trailing edge (OAT15A profile)
  • Infinite flow : M~=~0.73~~\alpha~=~2.75~~Re_{inf}~=~3.0~10^6
  • Steady transonic turbulent viscous flow.
  • Turbulence model : 2 transport equations (k,\omega) with SST correction.
  • Wall law.
  • Intermittency file :
  • Exact (i.e. min. values) calculation of distance to wall.
  • Flow is assumed to be laminar around the leading edge.
  • (from i~=~75 to i~=~119,
  • i.e. x~=~0.0703 on the lower side and x~=~0.0656 on the upper side).
  • On outer boundary, non-reflective vorticity boundary condition is used.
  • (A meaningful comparison with experiment requires the use of the vorticity condition.)
  • Mesh : 2 blocks 193 \times 48 \times 2 and 49 \times 105 \times 2
  • Jameson centered fluxes with artificial dissipation "dissca".
  • Jameson centered fluxes with Roe correction for transport equations
  • (Low value of Harten correction coefficient : 0.02).
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Initial conditions : uniform conditions at infinity.
  • 8000 iterations, CFL=3
  • OAT15A-VrtSST/OAT15A-VrtSST_1.jpeg
    OAT15A-VrtSST/OAT15A-VrtSST_2.jpeg
    OAT15A-VrtSST/zresidu.jpeg

    PF1-3Blades

    (Back to top of page)

    PF1-3Blades - 3D Euler - Motion with ALE

    PF1_3Blades.py3D configuration
    Multi-Domain
    Moving frame
    ALE
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Unsteady
  • Three-bladed ONERA Rotor with PF1 tip (3D).
  • Unsteady inviscid perfect gas flow.
  • Motion frame with ALE, absolute velocity formulation.
  • Three "C-H" meshes (each:~115 \times 32 \times 26).
  • Jameson centered fluxes with artificial dissipation `dissca' : [~1~,~0.064~,~1~].
  • Slip condition .
  • Initial state : uniform.
  • Time integration:~ Runge-Kutta 4 steps without freezing.
  • Implicit residual smoothing.
  • Time step = 0.019836393
  • 8100 iterations.
  • PF1-3Blades/zresidu.jpeg

    PF1Blade-ale

    (Back to top of page)

    PF1-Blade - 3D Euler - Motion with ALE

    PF1Blade_ale.py3D configuration
    Moving frame
    ALE
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Unsteady
  • PF1 Blade (3D)
  • Unsteady inviscid perfect gas flow.
  • Motion frame with ALE, absolute velocity formulation.
  • Mesh:~115 \times 32 \times 26.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~1~,~0.064~,~1~].
  • Slip condition .
  • Initial state : uniform.
  • Time integration:~ Runge-Kutta 4 steps without freezing.
  • Implicit residual smoothing.
  • Time step = 0.019836393
  • 7200 iterations.
  • PF1Blade-ale/PF1Blade-ale_1.jpeg
    PF1Blade-ale/PF1Blade-ale_2.jpeg
    PF1Blade-ale/zresidu.jpeg

    PF1Blade-rigid

    (Back to top of page)

    PF1-Blade - 3D Euler - Rigid motion

    PF1Blade_rigid.py3D configuration
    Moving frame
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Unsteady
  • PF1 Blade (3D)
  • Unsteady inviscid perfect gas flow.
  • Rigid motion, absolute velocity formulation.
  • Mesh:~115 \times 32 \times 26.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.032~,~1~].
  • Slip condition .
  • Initial state : uniform, farfield.
  • Time integration:~ Runge-Kutta 4 steps without freezing.
  • Implicit residual smoothing.
  • Time step = 0.019836393
  • 7200 iterations.
  • PF1Blade-rigid/PF1Blade-rigid_1.jpeg
    PF1Blade-rigid/PF1Blade-rigid_2.jpeg
    PF1Blade-rigid/zresidu.jpeg

    PF1Blade-rigid-ROE

    (Back to top of page)

    PF1-Blade - 3D Euler - Rigid motion

    pf1_iso_rig.py3D configuration
    Moving frame
    Euler
    Backward-Euler
    Roe fluxes
    LU
    Unsteady
  • PF1 Blade (3D)
  • Unsteady inviscid perfect gas flow.
  • Rigid motion, absolute velocity formulation.
  • Mesh:~115 \times 32 \times 26.
  • Second order Roe upwind fluxes (van Albada limiter).
  • Slip condition .
  • Initial state : restart after 1 rotor revolution.
  • Time integration:~ backward Euler.
  • Implicit matrix LU-Relax
  • Time step = 0.019836393
  • 900 iterations.
  • PF1Blade-rigid-ROE/Cp.jpeg

    PF1Blade-rigid-dts-ROE

    (Back to top of page)

    PF1-Blade - 3D Euler - Rigid motion

    pf1_iso_rig_dts.py3D configuration
    Moving frame
    Euler
    Backward-Euler
    Dual time step
    Roe fluxes
    LU
    Unsteady
  • PF1 Blade (3D)
  • Unsteady inviscid perfect gas flow.
  • Rigid motion, absolute velocity formulation.
  • Mesh:~115 \times 32 \times 26.
  • Second order Roe upwind fluxes (van Albada limiter).
  • Slip condition .
  • Initial state : restart after 1 rotor revolution.
  • Time integration:~ backward Euler.
  • Implicit matrix LU-Relax
  • Time step = 0.019836393
  • Dual time stepping method
  • 900 iterations.
  • PF1Blade-rigid-dts-ROE/Cp.jpeg

    Plate-ASM-TL

    (Back to top of page)

    Flat Plate Turbulent ASM with two layer modelisation

    Plate_ASM_TL.py2D-Plane configuration
    Navier-Stokes
    ASM turbulence model
    Two layer
    Jameson fluxes
    Scalar Dissipation
    IRS
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (ASM) + two layer modelisation
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~uniform state
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Low value of Harten correction~: 0,01
  • Local time step.
  • 6000 iterations, CFL=6.
  • Plate-ASM-TL/Plate-ASM-TL_1.jpeg
    Plate-ASM-TL/Plate-ASM-TL_2.jpeg
    Plate-ASM-TL/Plate-ASM-TL_3.jpeg
    Plate-ASM-TL/Plate-ASM-TL_4.jpeg
    Plate-ASM-TL/Plate-ASM-TL_5.jpeg
    Plate-ASM-TL/Plate-ASM-TL_6.jpeg
    Plate-ASM-TL/Plate-ASM-TL_7.jpeg
    Plate-ASM-TL/Plate-ASM-TL_8.jpeg
    Plate-ASM-TL/Plate-ASM-TL_9.jpeg
    Plate-ASM-TL/Plate-ASM-TL_10.jpeg
    Plate-ASM-TL/zresidu.jpeg

    Plate-Blx

    (Back to top of page)

    Flat Plate Turbulent: Baldwin Lomax

    flatPlateBaldwin.py2D-Plane configuration
    Navier-Stokes
    Baldwin-Lomax turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • Flat Plate
  • Steady turbulent viscous flow.
  • Algebraic turbulence model: Baldwin-Lomax.
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ backward Euler
  • Implicit scalar LU-SSOR.
  • Multigrid (W cycle)
  • Initial conditions:~ uniform state.
  • Local time step.
  • 3000 iterations, CFL=1000.
  • Plate-Blx/Plate-Blx_1.jpeg
    Plate-Blx/Plate-Blx_2.jpeg
    Plate-Blx/Plate-Blx_3.jpeg
    Plate-Blx/Plate-Blx_4.jpeg
    Plate-Blx/zresidu.jpeg

    Plate-Blx-02

    (Back to top of page)

    Flat Plate Turbulent: Baldwin Lomax - 2 blocks

    Plate_Blx_02_LuSca_BE_MG_V1_Serial.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    Baldwin-Lomax turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • Flat Plate
  • Steady turbulent viscous flow.
  • Algebraic turbulence model: Baldwin-Lomax.
  • Meshs:~ 45 \times 51 \times 2 and 45 \times 31 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Initial conditions:~Issued from a CANARI (k,l) calculation.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid (V cycle)
  • Local time step.
  • 500 iterations, CFL=1000.
  • Plate-Blx-02/friction.jpeg
    Plate-Blx-02/Plate-Baldwin_1.jpeg
    Plate-Blx-02/Plate-Baldwin_2.jpeg
    Plate-Blx-02/Plate-Baldwin_3.jpeg
    Plate-Blx-02/Plate-Baldwin_4.jpeg
    Plate-Blx-02/zresidu.jpeg

    Plate-Blx-MDPAR

    (Back to top of page)

    Flat Plate Turbulent: Baldwin Lomax Parallel

    Plate_Blx_MDPAR.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    Baldwin-Lomax turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Parallel
  • Flat Plate
  • Steady turbulent viscous flow.
  • Algebraic turbulence model: Baldwin-Lomax.
  • Meshs:~ 45 \times 51 \times 2 and 45 \times 31 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Initial conditions:~Issued from a CANARI (k,l) calculation.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Parallel mode, 2 processors.
  • 6000 iterations, CFL=6.
  • Plate-Blx-MDPAR/Plate-Baldwin_1_corr.jpeg
    Plate-Blx-MDPAR/Plate-Baldwin_2_corr.jpeg
    Plate-Blx-MDPAR/Plate-Baldwin_3_corr.jpeg
    Plate-Blx-MDPAR/Plate-Baldwin_4_corr.jpeg
    Plate-Blx-MDPAR/zresidu.jpeg

    Plate-Collect-Spal

    (Back to top of page)

    Translated flatPlate test case with collect boundary condition

    Plate_Collect_Spal.py2D-Plane configuration
    Moving frame
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • This test case is a flat Plate in translation along the flow direction ;
  • A collect condition is used for the boundary j=jmin ;
  • Three conditions are imposed on that boundary :
  • 1) injmfr1
  • 2) wallisoth
  • 3) outpress
  • Steady turbulent viscous flow.
  • Turbulence model: 1 transport equation (Spalart-Allmaras).
  • Mesh:~ 61 \times 29 \times 73 ;
  • Jameson centered fluxes with artificial dissipation `dismrt';
  • Time integration : Runge-Kutta 4 steps with freezing ;
  • Implicit residual smoothing ;
  • 3000 iterations, CFL=8.
  • Plate-Collect-Spal/fp_SA_collect.jpeg
    Plate-Collect-Spal/zresidu.jpeg

    Plate-KEPS-A

    (Back to top of page)

    Flat Plate Turbulent: KEPS

    flatPlateKEPS.py2D-Plane configuration
    Navier-Stokes
    KEps turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (k,\epsilon ).
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~Issued from 50 iterations with laminar assumption
  • (and setting \mu_t ~=~ 100~\mu).
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 6000 iterations, CFL=5.
  • Plate-KEPS-A/Plate-KEPS-A_6.jpeg
    Plate-KEPS-A/Plate-KEPS-A_1.jpeg
    Plate-KEPS-A/Plate-KEPS-A_4.jpeg
    Plate-KEPS-A/Plate-KEPS-A_7.jpeg
    Plate-KEPS-A/Plate-KEPS-A_5.jpeg
    Plate-KEPS-A/Plate-KEPS-A_3.jpeg
    Plate-KEPS-A/Plate-KEPS-A_2.jpeg
    Plate-KEPS-A/Plate-KEPS-A_9.jpeg
    Plate-KEPS-A/Plate-KEPS-A_8.jpeg
    Plate-KEPS-A/Plate-KEPS-A_10.jpeg
    Plate-KEPS-A/zresidu.jpeg

    Plate-KEps-KL

    (Back to top of page)

    Flat Plate Turbulent KEps, Intermittency

    Plate_KEps_KL.py2D-Plane configuration
    Navier-Stokes
    KEps turbulence model
    Prescribed transition
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (k,\varepsilon) with forced transition.
  • Wall law.
  • Transition : from file.
  • Cut-off : 1.e-08 on k and 1.e-06 on \varepsilon.
  • Mesh : 45 \times 50 \times 2.
  • Flat plane cell thickness : from 2.e-4 to 9.e-4.
  • Jameson centered fluxes with artificial dissipation `dissca' for mean flow.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions : converged k-l solution and transformation k-l --> k-\varepsilon.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 1000 iterations, CFL=6.
  • Plate-KEps-KL/zresidu.jpeg
    Plate-KEps-KL/Plate-KEPS-KL-k.jpeg
    Plate-KEps-KL/Plate-KEPS-KL.jpeg

    Plate-KEps-TL

    (Back to top of page)

    Flat Plate Turbulent KEps with two layer modelisation

    Plate_KEps_TL.py2D-Plane configuration
    Navier-Stokes
    KEps turbulence model
    Two layer
    Jameson fluxes
    Scalar Dissipation
    IRS
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (k,\epsilon ) + two layer modelisation
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~Issued from 50 iterations with laminar assumption
  • (and setting \mu_t ~=~ 100~\mu).
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 6000 iterations, CFL=5.
  • Plate-KEps-TL/Plate-KEPS-TL_1.jpeg
    Plate-KEps-TL/Plate-KEPS-TL_2.jpeg
    Plate-KEps-TL/Plate-KEPS-TL_3.jpeg
    Plate-KEps-TL/Plate-KEPS-TL_4.jpeg
    Plate-KEps-TL/Plate-KEPS-TL_5.jpeg
    Plate-KEps-TL/Plate-KEPS-TL_6.jpeg
    Plate-KEps-TL/Plate-KEPS-TL_7.jpeg
    Plate-KEps-TL/Plate-KEPS-TL_8.jpeg
    Plate-KEps-TL/Plate-KEPS-TL_9.jpeg
    Plate-KEps-TL/Plate-KEPS-TL_10.jpeg
    Plate-KEps-TL/zresidu.jpeg

    Plate-KL-G

    (Back to top of page)

    Flat Plate Turbulent KL

    Plate_KL_G.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
    Parallel
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Meshs:~ 23 \times 81 \times 2 and 23 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca' for mean flow.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform state.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Multigrid convergence acceleration method.
  • Implicit residual smoothing.
  • Local time step.
  • Parallel mode, 2 processors.
  • 2500 iterations, CFL=6.
  • Plate-KL-G/Plate-KL-G_1.jpeg
    Plate-KL-G/Plate-KL-G_2.jpeg
    Plate-KL-G/Plate-KL-G_3.jpeg
    Plate-KL-G/Plate-KL-G_4.jpeg
    Plate-KL-G/Plate-KL-G_5.jpeg
    Plate-KL-G/Plate-KL-G_6.jpeg
    Plate-KL-G/Plate-KL-G_7.jpeg
    Plate-KL-G/Plate-KL-G_8.jpeg
    Plate-KL-G/zresidu.jpeg

    Plate-KL-I

    (Back to top of page)

    Flat Plate Turbulent: KL, Scalar LDU

    plate_kl_i.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform state.
  • Time integration:~ backwardeuler.
  • Implicit scalar LU.
  • Local time step.
  • 3000 iterations, CFL=10.
  • Plate-KL-I/Plate-KL-I_2.jpeg
    Plate-KL-I/Plate-KL-I_3.jpeg
    Plate-KL-I/Plate-KL-I_5.jpeg
    Plate-KL-I/Plate-KL-I_1.jpeg
    Plate-KL-I/Plate-KL-I_4.jpeg
    Plate-KL-I/zresidu.jpeg

    Plate-KL-MG

    (Back to top of page)

    Flat Plate Turbulent: KL, MultiGrid

    flatPlateKL0_MG.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca' for mean flow.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform state.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Multigrid convergence acceleration method (V cycle)
  • Implicit residual smoothing.
  • Local time step.
  • 2500 iterations, CFL=6.
  • Plate-KL-MG/Plate-KL-MG_4.jpeg
    Plate-KL-MG/Plate-KL-MG_5.jpeg
    Plate-KL-MG/Plate-KL-MG_2.jpeg
    Plate-KL-MG/Plate-KL-MG_3.jpeg
    Plate-KL-MG/Plate-KL-MG_1.jpeg
    Plate-KL-MG/Plate-KL-MG_6.jpeg
    Plate-KL-MG/zresidu.jpeg

    Plate-KL-Wl

    (Back to top of page)

    Flat Plate Turbulent: KL Wall law

    Plate_KL_Wl.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Wall law
    Prescribed transition
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Wall law.
  • Intermittency file.
  • Mesh:~ 45 \times 50 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform state.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=6
  • Plate-KL-Wl/Plate-KL-Wl_4.jpeg
    Plate-KL-Wl/Plate-KL-Wl_5.jpeg
    Plate-KL-Wl/Plate-KL-Wl_2.jpeg
    Plate-KL-Wl/Plate-KL-Wl_3.jpeg
    Plate-KL-Wl/Plate-KL-Wl_1.jpeg
    Plate-KL-Wl/Plate-KL-Wl_6.jpeg
    Plate-KL-Wl/zresidu.jpeg

    Plate-KL-orthd

    (Back to top of page)

    Flat Plate Turbulent: KL, MultiGrid, orth dist

    Plate_KL_orthd.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 45 \times 81 \times 2 .
  • walldistcompute = 'mininterf\_ortho'.
  • Jameson centered fluxes with artificial dissipation 'dismrt' for mean flow.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform state.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Multigrid convergence acceleration method (V cycle)
  • Implicit residual smoothing.
  • Local time step.
  • 2000 iterations, CFL=6.
  • Plate-KL-orthd/cf.jpeg
    Plate-KL-orthd/theta.jpeg
    Plate-KL-orthd/zresidu.jpeg

    Plate-KO

    (Back to top of page)

    Flat Plate Turbulent: KO

    flatPlateKO.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (k,\omega ).
  • Cut-off: 1.e-08 on k and 10. on \omega .
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca' for mean flow.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform state.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 8000 iterations, CFL=4.
  • Plate-KO/Plate-KO_6.jpeg
    Plate-KO/Plate-KO_4.jpeg
    Plate-KO/Plate-KO_3.jpeg
    Plate-KO/Plate-KO_1.jpeg
    Plate-KO/Plate-KO_2.jpeg
    Plate-KO/Plate-KO_5.jpeg
    Plate-KO/zresidu.jpeg

    Plate-KO-Wl

    (Back to top of page)

    Flat Plate Turbulent: KO - Wall law

    Plate_KO_Wl.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Wall law
    Prescribed transition
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (k,\omega) with forced transition.
  • Wall law.
  • Transition : from file.
  • Cut-off : 1.e-08 on k and 10. on \omega.
  • Mesh : 45 \times 50 \times 2.
  • Flat plane cell thickness : from 2.e-4 to 9.e-4.
  • Jameson centered fluxes with artificial dissipation `dissca' for mean flow.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions : uniform state.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 2000 iterations, CFL=6.
  • Plate-KO-Wl/Plate-KO-Wl_1.jpeg
    Plate-KO-Wl/Plate-KO-Wl_2.jpeg
    Plate-KO-Wl/Plate-KO-Wl_3.jpeg
    Plate-KO-Wl/Plate-KO-Wl_4.jpeg
    Plate-KO-Wl/Plate-KO-Wl_5.jpeg
    Plate-KO-Wl/Plate-KO-Wl_6.jpeg
    Plate-KO-Wl/Plate-KO-Wl_7.jpeg
    Plate-KO-Wl/Plate-KO-Wl_8.jpeg
    Plate-KO-Wl/zresidu.jpeg

    Plate-Keps-v2f

    (Back to top of page)

    Flat Plate Turbulent k-eps-v2f, Intermittency

    Plate_Keps_v2f.py2D-Plane configuration
    k-eps-v2f turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
    Low speed preconditionning
  • 2D Flat Plate
  • Steady turbulent viscous flow.
  • Turbulent model: 4 transport equations (k-eps-v2f).
  • Mesh:~ 145 \times 65 \times 1 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps.
  • Implicit residual smoothing.
  • Local time step.
  • Low speed preconditioning.
  • 48000 iterations, CFL=7.
  • Plate-Keps-v2f/rok2.jpeg
    Plate-Keps-v2f/uplus.jpeg
    Plate-Keps-v2f/zresidu.jpeg

    Plate-Knut-Spal

    (Back to top of page)

    Flat Plate Turbulent Knut-Spalart

    Plate_Knut_Spal.py2D-Plane configuration
    Knut-Spalart turbulence model
    Backward-Euler
    Jameson fluxes
    LU
    Multi-Grid
  • Flat Plate M_0=0.7, R_L=4\,10^{6}, T_i=300K
  • Steady turbulent viscous flow
  • Turbulence model~: k-\tilde{\nu} transport equation model.
  • Mesh : 45x81x2.
  • Calculation of wall distances : walldistcompute = 'mininterf'
  • Jameson centered flux with artificial dissipation 'dissca' for mean flow
  • Jameson centered flux with Roe correction for transport equations.
  • Initial conditions : uniform state.
  • Time integration : backward Euler.
  • Multigrid convergence method (V cycle with one coarse grid)
  • Implicit LU relaxation 'lurelaxsca'.
  • Local time step
  • 1000 iterations, CFL=100
  • Plate-Knut-Spal/profK.jpeg
    Plate-Knut-Spal/rhoK.jpeg
    Plate-Knut-Spal/zresidu.jpeg

    Plate-Michel-1

    (Back to top of page)

    Flat Plate Turbulent: Michel

    flatPlateMichel_1.py2D-Plane configuration
    Navier-Stokes
    Michel turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • Flat Plate
  • Steady turbulent viscous flow.
  • Algebraic turbulence model: Michel et al. (tmic\_cfg=1)
  • Value of vorticity ratio = 0.001
  • corresponding to a rather satisfactory
  • boundary layer thickness evaluation in turbulence model.
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Initial conditions:~Issued from a CANARI (k,l) calculation.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 6000 iterations, CFL=6.
  • Plate-Michel-1/Plate-Michel_2.jpeg
    Plate-Michel-1/Plate-Michel_3.jpeg
    Plate-Michel-1/Plate-Michel_4.jpeg
    Plate-Michel-1/Plate-Michel_1.jpeg
    Plate-Michel-1/zresidu.jpeg

    Plate-Michel-3

    (Back to top of page)

    Flat Plate Turbulent: Michel

    Plate_Michel_3.py2D-Plane configuration
    Moving frame
    Navier-Stokes
    Michel turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • Flat Plate with translation motion in the flow direction.
  • Steady turbulent viscous flow.
  • Absolute velocity formulation.
  • Algebraic turbulence model: Michel et al. (tmic\_cfg=1).
  • Wall law.
  • Mesh:~ 45 \times 28 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dismrt'.
  • Initial conditions:~Uniform state.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 5000 iterations, CFL=8.
  • Plate-Michel-3/Plate-Michel_2.jpeg
    Plate-Michel-3/Plate-Michel_3.jpeg
    Plate-Michel-3/Plate-Michel_4.jpeg
    Plate-Michel-3/Plate-Michel_1.jpeg
    Plate-Michel-3/zresidu.jpeg

    Plate-Rough-Spal

    (Back to top of page)

    Flat Plate with rough wall (Acharia experiment)

    Plate_Rough_Spal.py2D-Plane configuration
    Spalart-Allmaras turbulence model
    Backward-Euler
    Jameson fluxes
    Matrix Dissipation
    LU
    Low speed preconditionning
  • Flat Plate with rough wall (Acharia experiment)
  • M_0=0.2, R_L=3.76\,10^{6}, T_i=300K
  • Steady turbulent viscous flow
  • Turbulence model~: Spalart-Allmaras model, activation of roughness effect
  • Mesh : 45x81x2.
  • walldistcompute = 'mininterf'
  • Jameson centered flux with artificial dissipation 'dissca' for mean flow
  • Jameson centered flux with Roe correction for transport equations.
  • Initial conditions : uniform state.
  • Time integration : backward Euler.
  • Convergence acceleration : low velocity preconditioning, mono-grid.
  • Implicit LU relaxation 'lussorsca'.
  • Local time step
  • 6000 iterations, CFL=100
  • Plate-Rough-Spal/hi.jpeg
    Plate-Rough-Spal/cf.jpeg
    Plate-Rough-Spal/zresidu.jpeg

    Plate-SA-HF1

    (Back to top of page)

    Flat Plate Turbulent: Spalart + wall heat flux

    fp_SA_WallHeatFlux_1.py2D-Plane configuration
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • Fixed flat plate
  • Steady turbulent flow.
  • Turbulence model: 1 transport equation (Spalart-Allmaras).
  • Wall heat flux boundary condition :
  • At computation convergence, wall temperature must converge towards Tsta = 0.7
  • Mesh:~ 45 \times 41 \times 2 .
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction.
  • Jameson centered fluxes with Roe correction for transport equation.
  • Time integration:~ Runge-Kutta 4 steps.
  • Implicit residual smoothing.
  • Local time step.
  • 8000 iterations, CFL=8.
  • Plate-SA-HF1/Plate-SA-HF1.jpeg
    Plate-SA-HF1/Plate-SA-HF1_1.jpeg
    Plate-SA-HF1/zresidu.jpeg

    Plate-SA-HF2

    (Back to top of page)

    Flat Plate Turbulent: Spalart + wall heat flux + motion

    fp_SA_WallHeatFlux_2.py2D-Plane configuration
    Moving frame
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • Flat plate animated by a translation move in the flow direction (translation velocity = 100 m/s).
  • Steady turbulent flow.
  • Turbulence model: 1 transport equation (Spalart-Allmaras).
  • Wall heat flux boundary condition :
  • At computation convergence, wall temperature must converge towards Tsta = 0.7
  • Mesh:~ 45 \times 41 \times 2 .
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction.
  • Jameson centered fluxes with Roe correction for transport equation.
  • Time integration:~ Runge-Kutta 4 steps.
  • Implicit residual smoothing.
  • Local time step.
  • 7000 iterations, CFL=8.
  • Plate-SA-HF2/Plate-SA-HF1.jpeg
    Plate-SA-HF2/Plate-SA-HF1_1.jpeg
    Plate-SA-HF2/zresidu.jpeg

    Plate-SA-Isoth1

    (Back to top of page)

    Flat Plate Turbulent: Spalart + wall isoth

    fp_SA_WallIsoth_1.py2D-Plane configuration
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • Fixed flat plate
  • Steady turbulent flow.
  • Turbulence model: 1 transport equation (Spalart-Allmaras).
  • Isotherm Wall boundary condition; wall temperature Tsta = 0.7
  • Mesh:~ 45 \times 41 \times 2 .
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction.
  • Jameson centered fluxes with Roe correction for transport equation.
  • Time integration:~ Runge-Kutta 4 steps.
  • Implicit residual smoothing.
  • Local time step.
  • 8000 iterations, CFL=8.
  • Plate-SA-Isoth1/Plate-SA-Isoth1.jpeg
    Plate-SA-Isoth1/Plate-SA-Isoth1_1.jpeg
    Plate-SA-Isoth1/zresidu.jpeg

    Plate-SA-Isoth2

    (Back to top of page)

    Flat Plate Turbulent: Spalart + wall isoth + motion

    Plate_SA_Isoth2.py2D-Plane configuration
    Moving frame
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • Flat plate animated by a translation motion in the flow direction (relative frame)
  • Steady turbulent flow.
  • Turbulence model: 1 transport equation (Spalart-Allmaras).
  • Isotherm Wall boundary condition; wall temperature Tsta = 0.7
  • Mesh:~ 45 \times 41 \times 2 .
  • Jameson centered fluxes with scalar artificial dissipation and Martinelli correction.
  • Jameson centered fluxes with Roe correction for transport equation.
  • Time integration:~ Runge-Kutta 4 steps.
  • Implicit residual smoothing.
  • Local time step.
  • 7000 iterations, CFL=8.
  • Plate-SA-Isoth2/zresidu.jpeg

    Plate-Spal

    (Back to top of page)

    Flat Plate Turbulent: Spalart

    flatPlateSpalart.py2D-Plane configuration
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulence model: 1 transport equation (Spalart-Allmaras).
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Jameson centered fluxes with Roe correction for transport equation.
  • Initial conditions:~ ~Issued from 50 iterations with laminar assumption
  • (and setting \mu_t ~=~ \mu).
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 6000 iterations, CFL=6.
  • Plate-Spal/Plate-Spalart_2.jpeg
    Plate-Spal/Plate-Spalart_1.jpeg
    Plate-Spal/Plate-Spalart_3.jpeg
    Plate-Spal/Plate-Spalart_4.jpeg
    Plate-Spal/Plate-Spalart_5.jpeg
    Plate-Spal/zresidu.jpeg

    Plate-Spal-LU

    (Back to top of page)

    Flat Plate Turbulent: Spalart + LUrelaxsca

    flatPlateSpalartLU.py2D-Plane configuration
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    LU
  • Flat Plate
  • Steady turbulent viscous flow.
  • Turbulence model: 1 transport equation (Spalart-Allmaras).
  • Mesh:~ 45 \times 81 \times 2 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Jameson centered fluxes with Roe correction for transport equation.
  • Initial conditions:~ ~Issued from 50 iterations with laminar assumption
  • (and setting \mu_t ~=~ \mu).
  • Time integration:~ backward Euler
  • Implicit scalar LUrelax.
  • Local time step.
  • 6000 iterations, CFL=6.
  • Plate-Spal-LU/Plate-Spalart_2.jpeg
    Plate-Spal-LU/Plate-Spalart_1.jpeg
    Plate-Spal-LU/Plate-Spalart_3.jpeg
    Plate-Spal-LU/Plate-Spalart_4.jpeg
    Plate-Spal-LU/Plate-Spalart_5.jpeg
    Plate-Spal-LU/Plate-Spalart_6.jpeg
    Plate-Spal-LU/zresidu.jpeg

    Propeller-Eul

    (Back to top of page)

    Propeller - Euler

    Propeller_Eul.py3D configuration
    Multi-Domain
    Euler
    Backward-Euler
    Jameson fluxes
    Matrix Dissipation
    LU
    Multi-Grid
    Parallel
  • 3D actuator disc.
  • Propeller simulation.
  • Jameson centered fluxes with artificial dissipation `dissca``.
  • Mesh: 4 blocks, 236520 nodes.
  • Time integration :~ Backward Euler.
  • Implicit LU.
  • CFL=10 (with linear evolution from CFL=1 during first 77 it.)
  • 250 iterations.
  • Parallel calculation on 2 processors.
  • Propeller-Eul/zresidu.jpeg

    R7A-RANS-Dts

    (Back to top of page)

    Rotor 7A 1.2-F1 deforming blade :ALE - Turbulent Michel - Dts

    R7A_RANS_Dts.py3D configuration
    Multi-Domain
    Moving frame
    ALE
    Navier-Stokes
    Michel turbulence model
    Backward-Euler
    Dual time step
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
    Unsteady
  • 7A Rotor, 4 blades, soft deformable blades, weak coupling HOST - elsA
  • Motion frame with ALE, absolute velocity formulation;
  • Rotationnal tip Mach number ---> M\_T = 0.646
  • Aspect ratio ---> AR =15.
  • Advance ratio ---> MU = 0.4
  • Rotation speed ---> OMGR = M\_T / AR
  • Rotation axis ---> OZ
  • Rotor shaft ---> ALP0 = 0.
  • Translation speed ---> (-MU*M\_T*cos(ALP0*pi/180.), 0., MU*M\_T*sin(ALP0*pi/180.))
  • Unsteady forward flight calculation, inviscid perfect gas flow with Michel model.
  • Jameson centered fluxes with artificial dissipation and Martinelli correction ``dismrt''.
  • Time integration:~ Backward-Euler.
  • Implicit phase Lu-Relax (2 sub-sycles)
  • Dual time stepping with maximum number of 150 dual iterations.
  • Multigrid convergence acceleration method (V cycle, one coarse grid)
  • Time step associated with a rotation of 0.1~deg
  • Initial conditions:~Issued from a first rotor revolution (360 iterations)
  • CFL=4, 360 iterations (second rotor revolution)
  • R7A-RANS-Dts/bladesecforcem2z.jpeg

    R7A-RANS-Gear

    (Back to top of page)

    Rotor 7A 1.2-F1 deforming blade :ALE - Turbulent Michel - Gear

    R7A_RANS_Gear.py3D configuration
    Multi-Domain
    Moving frame
    ALE
    Navier-Stokes
    Michel turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Unsteady
  • 7A Rotor, 4 blades, soft deformable blades, weak coupling HOST - elsA
  • Motion frame with ALE, absolute velocity formulation;
  • Rotationnal tip Mach number ---> M\_T = 0.646
  • Aspect ratio ---> AR =15.
  • Advance ratio ---> MU = 0.4
  • Rotation speed ---> OMGR = M\_T / AR
  • Rotation axis ---> OZ
  • Rotor shaft ---> ALP0 = 0.
  • Translation speed ---> (-MU*M\_T*cos(ALP0*pi/180.), 0., MU*M\_T*sin(ALP0*pi/180.))
  • Unsteady forward flight calculation, inviscid perfect gas flow with Michel model.
  • Jameson centered fluxes with artificial dissipation and Martinelli correction ``dismrt''.
  • Time integration:~ Backward-Euler.
  • Implicit phase Lu-Relax (2 sub-sycles)
  • Gear method with maximum number of 40 sub iterations.
  • Time step associated with a rotation of 0.1~deg
  • Initial conditions:~Issued from a first rotor revolution (360 iterations)
  • 360 iterations (second rotor revolution)
  • R7A-RANS-Gear/bladesectorquem2z.jpeg

    RAE-BLX-02

    (Back to top of page)

    Rae2822 Profile: Baldwin-Lomax,2 dom, Intermittency

    RAE_BLX_02.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    Baldwin-Lomax turbulence model
    Prescribed transition
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: Algebraic Baldwin-Lomax.
  • Mesh:~ 257 \times 129 \times 2 cut into 2 blocks :~
  • 129 \times 129 \times 2 and 129 \times 129 \times 2.
  • Wall distance is computed as mininterf.
  • Jameson centered fluxes with artificial dissipation ``dissca'' for mean flow.
  • Initial conditions:~ uniform state.
  • Time integration:~ backward Euler
  • Implicit scalar LU-SSOR.
  • Multigrid (W cycle)
  • Local time step.
  • 1000 iterations, CFL=1000.
  • RAE-BLX-02/RAE-BLX-02_1.jpeg
    RAE-BLX-02/zresidu.jpeg

    RAE-KL-02

    (Back to top of page)

    Rae2822 Profile: KL, 2 domains

    rae2822_KL_2dom.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 257 \times 65 \times 2 cut into 2 blocks :~
  • 129 \times 65 \times 2 and 129 \times 65 \times 2.
  • Wall distance is read in a file and corresponds to minimum value choice.
  • Jameson centered fluxes with artificial dissipation ``dissca'' for mean flow.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform state.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 6000 iterations, CFL=4.
  • RAE-KL-02/RAE-KL-02_1.jpeg
    RAE-KL-02/RAE-KL-02_2.jpeg
    RAE-KL-02/RAE-KL-02_3.jpeg
    RAE-KL-02/RAE-KL-02_4.jpeg
    RAE-KL-02/zresidu.jpeg

    RAE-KL-CRITLOC

    (Back to top of page)

    Rae2822 Profile: KL, Abu Ghannam \& Shaw local transition criteria

    RAE_KL_CRITLOC.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Transition criteria
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: (k-l) Smith with Abu Ghannam \& Shaw local transition criteria (T_u=0.1\%).
  • Transition criterion computed between x/c=0.03 and x/c=0.75 (wall interface numbers from 11 to 78 and 111 to 179), imposed laminar at the leading edge (from 79 to 110), turbulent elsewhere (trailing edge).
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dismrt''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from initial file corresponding to a 129x33 coarse mesh (2000 iter)
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid Acceleration V-cycle.
  • Local time step.
  • 2000 iterations, CFL=5.
  • RAE-KL-CRITLOC/RAE-KL-CRITLOC_1.jpeg
    RAE-KL-CRITLOC/RAE-KL-CRITLOC_2.jpeg
    RAE-KL-CRITLOC/RAE-KL-CRITLOC_4.jpeg
    RAE-KL-CRITLOC/zresidu.jpeg

    RAE-KL-CRITLOC-1S2

    (Back to top of page)

    Rae2822 Profile: KL,Abu Ghannam \& Shaw local transition criteria

    RAE_KL_CRITLOC_1S2.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Transition criteria
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • RAE2822 2D wing profile.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: k-l Smith with Abu Ghannam \& Shaw transition criteria (T_u=0.1\%).
  • Transition criteria computed between leading edge and x/c=0.75 (wall interface numbers from 11 to 83, imposed turbulent elswhere (trailing edge).
  • Mesh:~ 129 \times 33 \times 2 .
  • Jameson centered fluxes with artificial dissipation and Martinelli correction.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from uniform field.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 2000 iterations, CFL=4.

  • RAE-KL-VGRD-5PCOR

    (Back to top of page)

    Rae2822 Profile: KL, 1 domain

    RAE_KL_VGRD_5PCOR.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model~: 2 transport equations (k,\epsilon) (despite of the test case name).
  • Initial conditions~: from previous laminar iterations.
  • Mesh:~ 2 blocks including 207025 nodes per block.
  • Jameson centered fluxes with artificial dissipation ``dissca'':[~0.5~,~0.032~,~1.0~].
  • Velocity sensor for reduction of artificial viscosity in the boundary layer.
  • Calculation of the diffusive gradients : centered gradients with correction at the interfaces.
  • Harten correction coefficient = 0.1
  • Time integration :~Runge-Kutta 4 steps with freezing.
  • Implicit Residual Smoothing.
  • Local time step.
  • 2000 iterations, CFL=5.
  • RAE-KL-VGRD-5PCOR/RAE-KL_VGRD_1.jpeg
    RAE-KL-VGRD-5PCOR/zresidu.jpeg

    RAE-KO-AMR

    (Back to top of page)

    rae2822 - KOMEGA - Local Multigrid

    rae_ko_amr.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Local Multi-Grid (AMR)
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: (k-\omega).
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dissca''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform flow field.
  • Time integration:~ BackwardEuler.
  • Lussorsca implicit method.
  • Local time step.
  • 4500 iterations, CFL=5.
  • Local multigrid.
  • RAE-KO-AMR/RAE-KO-AMR-1.jpeg
    RAE-KO-AMR/RAE-KO-AMR-2.jpeg
    RAE-KO-AMR/zresidu.jpeg

    RAE-KO-CAVITY

    (Back to top of page)

    Rae2822 Profile: KO, Double BC Chimera

    RAE_KO_CAVITY.py2D-Plane configuration
    Multi-Domain
    Chimera
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
  • RAE2822 2D wing profile with a cavity on upper side.
  • Chimera context : Mask cart\_elts, depth = 2, interp = adt, explicit interpolation, doubly defined boundary condition.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k, \omega ) with forced transition.
  • Meshes:~ 213 \times 41 \times 2 and 149 \times 129 \times 2.
  • Jameson centered fluxes with artificial dissipation ``dissca''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from initial file.
  • Chimera data:~ from file.
  • Time integration:~ Backwardeuler.
  • Implicit LU-Relax scalar.
  • Local time step.
  • 10000 iterations, CFL=(1. -> 6.)
  • RAE-KO-CAVITY/RAE-KO-CAVITY_rok.jpeg
    RAE-KO-CAVITY/zresidu.jpeg

    RAE-KO-CHIM

    (Back to top of page)

    Rae2822 Profile : Chimera, IRS, KO, Intermittency

    rae_ko_chim.py2D-Plane configuration
    Multi-Domain
    Chimera
    KO turbulence model
    Prescribed transition
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • RAE2822 2D wing profile.
  • Chimera context : Masking by cartesian elements, depth = 1, interp = icg, explicit interpolation.
  • Multigrid - Extrapolation - 2 coarse grid - 1 ite on coarse grid - cell to cell - No mask on coarse grid.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k, \omega ) with forced transition.
  • Meshes:~ 213 \times 41 \times 2 and 149 \times 129 \times 2.
  • Jameson centered fluxes with artificial dissipation ``dissca''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from initial file.
  • Chimera data:~ from file.
  • Time integration:~ Backwardeuler.
  • Implicit LUrelax scalar.
  • Local time step.
  • 1800 iterations, CFL=500.
  • RAE-KO-CHIM/RAE-KO-CHIM_1.jpeg
    RAE-KO-CHIM/RAE-KO-CHIM_2.jpeg
    RAE-KO-CHIM/zresidu.jpeg

    RAE-KO-LU-SST

    (Back to top of page)

    rae2822 - KOMEGA with SST Correction

    RAE_KO_LU_SST.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: (k-\omega) Kok version model with SST correction.
  • No transition criterion, no prescribed intermittency file.
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dismrt''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from infinite state
  • Time integration:~ backward-Euler
  • Implicit phase: scalar LU-SSOR
  • Local time step.
  • 15000 iterations, CFL 500.
  • RAE-KO-LU-SST/isoM.jpeg
    RAE-KO-LU-SST/zresidu.jpeg

    RAE-KO-LU-SST-SCHEME

    (Back to top of page)

    rae2822 - KOMEGA with SST Correction

    RAE_KO_LU_SST_SCHEME.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    LU
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.754, \alpha~=~2.57\deg, Re=6.2e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: (k-\omega) Kok version model with SST correction.
  • No transition criterion, no prescribed intermittency file.
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dismrt''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from infinite state
  • Time integration:~ backward-Euler
  • Implicit phase: scalar LU-SSOR
  • Local time step.
  • 15000 iterations, CFL 6.
  • Configuration 1: ausmp scheme.
  • Configuration 2: jameson scheme.
  • Configuration 3: rbci scheme.
  • Configuration 4: rbco3 scheme.
  • RAE-KO-LU-SST-SCHEME/RAE-KO-SST_Cl.jpeg
    RAE-KO-LU-SST-SCHEME/RAE-KO-SST_flux_row.jpeg
    RAE-KO-LU-SST-SCHEME/RAE-KO-SST_H.jpeg
    RAE-KO-LU-SST-SCHEME/RAE-KO-SST_theta1.jpeg
    RAE-KO-LU-SST-SCHEME/RAE-KO-SST_residual.jpeg
    RAE-KO-LU-SST-SCHEME/RAE-KO-SST_Cd.jpeg

    RAE-KO-LU-SST-ausmp

    (Back to top of page)

    rae2822 - KOMEGA with SST Correction - ausmp scheme

    RAE_KO_LU_SST_ausmp.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    AUSMP scheme
    LU
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.754, \alpha~=~2.57\deg, Re=6.2e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: (k-\omega) Kok version model with SST correction.
  • No transition criterion, no prescribed intermittency file.
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dismrt''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from infinite state
  • Time integration:~ backward-Euler
  • Implicit phase: scalar LU-SSOR
  • Local time step.
  • 15000 iterations, CFL 6.

  • RAE-KO-LU-SST-jameson

    (Back to top of page)

    rae2822 - KOMEGA with SST Correction - Jameson scheme

    RAE_KO_LU_SST_jameson.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.754, \alpha~=~2.57\deg, Re=6.2e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: (k-\omega) Kok version model with SST correction.
  • No transition criterion, no prescribed intermittency file.
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dismrt''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from infinite state
  • Time integration:~ backward-Euler
  • Implicit phase: scalar LU-SSOR
  • Local time step.
  • 15000 iterations, CFL 6.

  • RAE-KO-LU-SST-rbci

    (Back to top of page)

    rae2822 - KOMEGA with SST Correction - rbci scheme

    RAE_KO_LU_SST_rbci.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    rbci scheme
    LU
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.754, \alpha~=~2.57\deg, Re=6.2e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: (k-\omega) Kok version model with SST correction.
  • No transition criterion, no prescribed intermittency file.
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dismrt''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from infinite state
  • Time integration:~ backward-Euler
  • Implicit phase: scalar LU-SSOR
  • Local time step.
  • 15000 iterations, CFL 6.

  • RAE-KO-LU-SST-rbco3

    (Back to top of page)

    rae2822 - KOMEGA with SST Correction - rbco3 scheme

    RAE_KO_LU_SST_rbco3.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    rbci scheme
    LU
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.754, \alpha~=~2.57\deg, Re=6.2e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: (k-\omega) Kok version model with SST correction.
  • No transition criterion, no prescribed intermittency file.
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dismrt''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from infinite state
  • Time integration:~ backward-Euler
  • Implicit phase: scalar LU-SSOR
  • Local time step.
  • 15000 iterations, CFL 6.

  • RAE-KO-SST

    (Back to top of page)

    rae2822 - KOMEGA with SST Correction

    RAE_KO_SST.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.754, \alpha~=~2.57\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: (k-\omega) Kok version model with SST correction.
  • No transition criterion, with prescribed intermittency file.
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dismrt''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform conditions at infinity.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 5000 iterations, CFL increase from to 2 to 6 during the first 300 iterations
  • RAE-KO-SST/RAE-KO-SST_1.jpeg
    RAE-KO-SST/RAE-KO-SST_2.jpeg
    RAE-KO-SST/RAE-KO-SST_3.jpeg
    RAE-KO-SST/RAE-KO-SST_4.jpeg
    RAE-KO-SST/RAE-KO-SST_5.jpeg
    RAE-KO-SST/zresidu.jpeg

    RAE-KO-TRA

    (Back to top of page)

    Rae2822 Profile: KO, Intermittency

    rae_ko_tra.py2D-Plane configuration
    Navier-Stokes
    KO turbulence model
    Prescribed transition
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k, \omega ) with forced transition.
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dissca''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from initial file.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid.
  • Local time step.
  • 4000 iterations, CFL=4.
  • RAE-KO-TRA/RAE-KO-TRA_1.jpeg
    RAE-KO-TRA/zresidu.jpeg

    RAE-KW-MG-MPI

    (Back to top of page)

    Rae2822 Profile: KOmega Parallel

    rae_kw_mg_2d_mpi.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
    Parallel
  • RAE2822 3D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,\omega).
  • Mesh:~90000 points into 8 blocks.
  • Jameson centered fluxes with artificial dissipation ``dissca'' for mean flow.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ uniform state.
  • Time integration:~ Backward-Euler.
  • Implicit :~Scalar LU-SSOR
  • Multigrid convergence acceleration.
  • Local time step.
  • Parallel mode, 2 processors.
  • 1000 iterations, CFL=10.
  • RAE-KW-MG-MPI/RAE-KW-NM.jpeg
    RAE-KW-MG-MPI/RAE-KW-NM-residual.jpeg

    RAE-SA-CRITNOLOC

    (Back to top of page)

    Rae2822 Profile: Spalart-Allmaras, non-local transition criterion

    RAE_SA_CRITNOLOC.py2D-Plane configuration
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Transition criteria
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: Spalart with non-local Arnal-Habiballah-Delcourt transition criteria (T_u=0.3\%).
  • Transition criterion computed between x/c=0.03 and x/c=0.75 (wall interface numbers from 11 to 78 and 111 to 179), imposed laminar at the leading edge (from 79 to 110), turbulent elsewhere (trailing edge).
  • Mesh:~ 257 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation ``dismrt''.
  • Jameson centered fluxes with Roe correction for transport equations.
  • Initial conditions:~ from initial file corresponding to a 129x33 coarse mesh.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid acceleration V-cycle.
  • Local time step.
  • 3000 iterations, CFL=5.
  • RAE-SA-CRITNOLOC/RAE-SA-CRITNOLOC_1.jpeg
    RAE-SA-CRITNOLOC/RAE-SA-CRITNOLOC_2.jpeg
    RAE-SA-CRITNOLOC/RAE-SA-CRITNOLOC_3.jpeg
    RAE-SA-CRITNOLOC/RAE-SA-CRITNOLOC_4.jpeg
    RAE-SA-CRITNOLOC/zresidu.jpeg

    RAE-SA-SSOR

    (Back to top of page)

    Rae2822 Profile: Spalart

    RAE_SA_SSOR.py2D-Plane configuration
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: Spalart-Allmaras
  • Mesh:~ 353 \times 65 \times 2 .
  • Jameson centered fluxes with artificial dissipation 'dissca'.
  • Centered scheme with artificial dissipation for turbulent system 'artviscspalart.
  • Initial conditions: infinite state.
  • Time integration:~ backward Euler
  • Implicit: LUSSOR scalar.
  • Multigrid vcycle (3 coarse grids).
  • Local time step.
  • 1000 iterations, CFL=1000.
  • RAE-SA-SSOR/RAE-SA-SSOR_1.jpeg
    RAE-SA-SSOR/RAE-SA-SSOR_2.jpeg
    RAE-SA-SSOR/zresidu.jpeg

    RAE-TUR-D0

    (Back to top of page)

    Rae2822 Profile: Distance to wall

    rae2822_2dom_dist0.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Turbulent viscous flow.
  • Mesh:~ 257 \times 65 \times 2 cut into 2 blocks :~
  • 129 \times 65 \times 2 and 129 \times 65 \times 2.
  • Calculation along mesh lines of the wall distance field.
  • (without flow calculation)
  • RAE-TUR-D0/RAE-dist0.jpeg

    RAE-TUR-D1

    (Back to top of page)

    Rae2822 Profile: Distance to wall

    rae2822_2dom_dist1.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
  • RAE2822 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.73, \alpha~=~2.79\deg, Re=6.5e6.
  • Turbulent viscous flow.
  • Mesh:~ 257 \times 129 \times 2 cut into 2 blocks :~
  • 129 \times 65 \times 2 and 129 \times 65 \times 2.
  • Calculation of the wall distance field : minimum value
  • (without flow calculation)
  • RAE-TUR-D1/RAE-dist1.jpeg

    ROTOR-01

    (Back to top of page)

    Rotor in hover 3D: Inviscid flow

    ROTOR_01.py3D configuration
    Moving frame
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • 3D rotor Caradonna et Tung .
  • Tip Mach number ---> M\_T = 0.794
  • Rotation speed ---> omega =.1323
  • Rotation axis ---> OZ
  • Translation speed ---> (0.,0.,0.)
  • Steady transonic inviscid perfect gas flow.
  • Absolute velocity formulation.
  • Mesh:~115 \times 32 \times 26.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Slip condition with multi-dimensional extrapolation.
  • 3000 iterations, CFL=2.
  • ROTOR-01/ROTOR-01_2.jpeg
    ROTOR-01/ROTOR-01_1.jpeg
    ROTOR-01/zresidu.jpeg

    ROTOR-7A-12F1

    (Back to top of page)

    Rotor 7A 1.2-F1 deforming blade :ALE - Euler

    ROTOR_7A_12F1.py3D configuration
    Multi-Domain
    Moving frame
    ALE
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Unsteady
  • 7A Rotor, soft blade, CHANCE test case 1.2-F1, 4 blades.
  • Unsteady forward flight calculation, inviscid perfect gas flow.
  • Rotationnal tip Mach number ---> M\_T = 0.646
  • Aspect ratio ---> AR =15.
  • Advance ratio ---> MU = 0.4
  • Rotation speed ---> OMGR = M\_T / AR
  • Rotation axis ---> OZ
  • Rotor shaft ---> ALP0 = 0.
  • Translation speed ---> (-MU*M\_T*cos(ALP0*pi/180.), 0., MU*M\_T*sin(ALP0*pi/180.))
  • Steady NS equations with Michel model
  • Motion frame with ALE, absolute velocity formulation.
  • CH Mesh:~141 \times 40 \times 26.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps without freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration method (W cycle)
  • Time step associated with a rotation of 0.1~deg
  • 3600 iterations.
  • ROTOR-7A-12F1/ROTOR-7A-12F1_1.jpeg
    ROTOR-7A-12F1/ROTOR-7A-12F1_2.jpeg
    ROTOR-7A-12F1/ROTOR-7A-12F1_3.jpeg

    ROTOR-7A-CHIM-01

    (Back to top of page)

    Standard Rotor 7A : Chimera

    rotor_7A_chim_01.py3D configuration
    Multi-Domain
    Chimera
    Moving frame
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Unsteady
  • 7A Helicopter rotor with complex motion resolved by a Chimera Technique, 4 blades.
  • Multi-domain with blanking and overlapping.
  • The computational domain is composed of five domains.
  • 1 domain for each blade ; the other domain : the background cartesian grid.
  • Each blade grid overlaps the cartesian grid, blade grids do not recover each other.
  • The cartesian grid is refined close to the blade.
  • Chimera context : Mask Parallelepiped, depth = 2, interp = icg, explicit interpolation.
  • extraction in absolute frame
  • Tip Mach number : 0.646.
  • Aspect ratio : 0.4.
  • Advance ratio : 1.5.
  • Unsteady transonic inviscid flow.
  • 7A-blade mesh :~141 \times 27 \times 18.
  • Cylinder mesh :~60 \times 60 \times 60.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration: Runge Kutta 4 steps
  • Implicit residual smoothing
  • Global time step : 0.003 s.
  • 2600 iterations.
  • Motion : constant translation (`xz' plane, incidence : 12.57{\deg}, norm : 0.2584~a_{\infty} ) and rotation (`z' axis, norm : 0.431~rad/s), composed with complex rotor motion.
  • Flap : [{\beta}]~=~[~-1.789~,~-3.758~,~0~,~-0.343~,~0.095~,~-0.024~,~-0.03~]
  • Lead-lag : [{\delta}]~=~[~-0.339~,~0.0188~,~-0.095~,~0.012~,~0.046~,~0.007~,~0.008~]
  • Pitch : [{\theta}]~=~[~13.614~,~1.509~,~-3.758~]
  • ROTOR-7A-CHIM-01/Cp.jpeg
    ROTOR-7A-CHIM-01/machr.jpeg
    ROTOR-7A-CHIM-01/zresidu.jpeg

    ROTOR-7A-KO

    (Back to top of page)

    Rotor 7A K-Omega:

    ROTOR_7A_KO.py3D configuration
    Moving frame
    Navier-Stokes
    KO turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
  • 7A helicopter rotor
  • CH mesh generated by PB for CHANCE : NS 7A 1.2-H1 (NS calculation)
  • Rotationnal tip Mach number ---> ~M\_T ~=~ 0.617
  • Collective pitch ---> ~\theta\_c ~=~ 5.97^o
  • Tip Rey ---> ~Re\_{TIP} ~=~ 1930000.
  • aspect ratio ---> ~AR~=~15.
  • Rotation speed ---> ~omega ~=~ M\_T / AR
  • Rotation axis ---> ~OX
  • Translation speed ---> ~(0.,~0.,~0.)
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k , \omega ) .
  • Absolute velocity formulation.
  • Mesh:~217 \times 61 \times 57.
  • Jameson centered fluxes with artificial dissipation `dismrt'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration method (W cycle)
  • Local time step.
  • Adiabatic wall
  • 1500 iterations, CFL=4.
  • ROTOR-7A-KO/ROTOR-7A_1.jpeg
    ROTOR-7A-KO/ROTOR-7A_2.jpeg
    ROTOR-7A-KO/ROTOR-7A_3.jpeg
    ROTOR-7A-KO/zresidu.jpeg

    ROTOR-7A-KO-MDPAR

    (Back to top of page)

    Rotor 7A K-Omega Parallel:

    ROTOR_7A_KO_MDPAR.py3D configuration
    Multi-Domain
    Moving frame
    Navier-Stokes
    KO turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
    Parallel
  • 7A helicopter rotor
  • CH mesh generated by PB for CHANCE : NS 7A 1.2-H1 (NS calculation)
  • Rotationnal tip Mach number ---> ~M\_T ~=~ 0.617
  • Collective pitch ---> ~\theta\_c ~=~ 5.97^o
  • Tip Rey ---> ~Re\_{TIP} ~=~ 1930000.
  • aspect ratio ---> ~AR~=~15.
  • Rotation speed ---> ~omega ~=~ M\_T / AR
  • Rotation axis ---> ~OX
  • Translation speed ---> ~(0.,~0.,~0.)
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k , \omega ) Wilcox, with Zheng limitor.
  • Absolute velocity formulation.
  • Mesh:~217 \times 61 \times 29.
  • Jameson centered fluxes with artificial dissipation `dismrt'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration method (W cycle)
  • Local time step.
  • Adiabatic wall
  • Parallel computation, 2 processors
  • 1500 iterations, CFL=4.
  • ROTOR-7A-KO-MDPAR/zresidu.jpeg
    ROTOR-7A-KO-MDPAR/ROTOR-7A_2.jpeg

    ROTOR-AIX-CHIM

    (Back to top of page)

    Rotor Chimere

    ROTOR_AIX_CHIM.py3D configuration
    Chimera
    Partially coincident match
    Moving frame
    KO turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • ROTOR Aix with blade tip groove resolved by a Chimera Technique.
  • Chimera context : depth = 1, interp = icg, explicit interpolation.
  • use of "doubly\_defined" boudary conditions.
  • Steady turbulent viscous flow.
  • Turbulent model : Spalart-Allmaras.
  • Mesh : H block domain with 13~\times~21~\times~99 points ;
  • O block domain with 197~\times~45~\times~99 points ;
  • H block domain with 49~\times~37~\times~99 points ;
  • O block domain in tip clearance with 197~\times~21~\times~23 points ;
  • H block domain in tip clearance with 75~\times~25~\times~23 points ;
  • H block domain for blade tip groove with 129~\times~51~\times~47 points ;
  • Jameson centered fluxes with artificial dissipation `dismrt' : [~0.5~,~0.032~,~1~].
  • Time integration: Runge-Kutta 4.
  • Implicit IRS.
  • 10000 iterations. Cfl = 3.0
  • ROTOR-AIX-CHIM/rotor_aix_chim_1.jpeg
    ROTOR-AIX-CHIM/rotor_aix_chim_2.jpeg
    ROTOR-AIX-CHIM/rotor_aix_chim_3.jpeg
    ROTOR-AIX-CHIM/zresidu.jpeg

    ROTOR-CHIMERE6

    (Back to top of page)

    Rotor Chimere

    rotor_chimere.py3D configuration
    Chimera
    Moving frame
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • ROTOR-7Awith motion resolved by a Chimera Technique.
  • Chimera context : Mask Parallelepiped, depth = 2, interp = icg, implicit interpolation OS.
  • Tip Mach number : 0.662.
  • Advanced ratio : 1.5.
  • steady transonic perfect gas flow.
  • Four 7A-blade meshes :~141 \times 27 \times 18.
  • Cylinder mesh :60 \times 60 \times 608.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration: Runge-Kutta 4 steps with freezing.
  • Implicit IRS.
  • 4000 iterations. Cfl = 3.0
  • ROTOR-CHIMERE6/ROTOR-CHIMERE6_relative_mach.jpeg
    ROTOR-CHIMERE6/ROTOR-CHIMERE6_vorticity.jpeg
    ROTOR-CHIMERE6/zresidu.jpeg

    ROTOR-Michel-01

    (Back to top of page)

    Rotor in hover 3D: Turbulent flow

    ROTOR_Michel_01.py3D configuration
    Moving frame
    Navier-Stokes
    Michel turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
  • 3D rotor Caradonna et Tung , 8 deg incidence
  • Tip Mach number ---> M\_T = 0.877
  • aspect ratio ---> AR =6.
  • Rotation speed ---> omega = M\_T / AR
  • Rotation axis ---> OX
  • Translation speed ---> (0.,0.,0.)
  • Steady NS equations with Michel model
  • Absolute velocity formulation.
  • Mesh:~121 \times 33 \times 33.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Adiabatic wall
  • 10000 iterations, CFL=4.
  • ROTOR-Michel-01/ROTOR-Michel-01_1.jpeg
    ROTOR-Michel-01/ROTOR-Michel-01_2.jpeg
    ROTOR-Michel-01/zresidu.jpeg

    ROTOR-NS-MGINTERP

    (Back to top of page)

    Rotor 7A - CHIMERE - K-OMEGA

    ROTOR_NS_MGINTERP.py3D configuration
    Multi-Domain
    Chimera
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • 7A Helicopter rotor.
  • Steady transonic turbulent viscous flow.
  • Tip Mach number : 0.617
  • Tip Reynolds number : 1.93~10^6
  • Aspect ratio : 15.
  • Turbulence model: 2 transport equations (k, \omega)
  • Chimera technique with blanking and overlapping.
  • Chimera context : Mask "cartesian elts", depth=1, interp=adt, explicit interpolation.
  • 7A-blade mesh : 257 x 49 x 33
  • Cylinder mesh : 73 x 61 x 225
  • Jameson centered fluxes with artificial dissipation `dismrt'.
  • Time integration :~BackwardEuler.
  • Implicit scalar LU-Relax.
  • Multigrid convergence acceleration method (1 coarse grid)
  • Multigrid : extrapolation boundary conditions for the Chimera boundary conditions.
  • Local time step.
  • 1500 iterations, CFL=100.
  • ROTOR-NS-MGINTERP/Cp.jpeg
    ROTOR-NS-MGINTERP/zresidu1.jpeg
    ROTOR-NS-MGINTERP/zresidu2.jpeg

    ROTOR-STAT

    (Back to top of page)

    x

    ROTOR_STAT.py3D configuration
    Multi-Domain
    KO turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
  • 7A helicopter rotor in steady flight.
  • CH mesh generated by PB for CHANCE : NS 7AD 1.2-H7 (NS calculation).
  • Stalled configuration (13 degrees).
  • Rotationnal tip Mach number ---> ~M\_T ~=~ 0.617
  • Tip Rey ---> ~Re\_{TIP} ~=~ 1930000.
  • Aspect ratio ---> ~AR~=~15.
  • Rotation speed ---> ~omega ~=~ M\_T / AR
  • Rotation axis ---> ~OX
  • Translation speed ---> ~(0.,~0.,~0.)
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k , \omega ).
  • Zheng limitor, SST correction.
  • Absolute velocity formulation.
  • Adiabatic wall.
  • Mesh:~217 \times 61 \times 57.
  • Jameson centered fluxes for mean flow
  • with artificial dissipation `dismrt': [0.5,~0.016,~1.,~0.33].
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction coefficient : 0.01
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration method (W cycle)
  • Local time step.
  • Initialization : file associated with 50 iterations in laminar (coeffmutinit = 10.)
  • 1500 iterations, CFL=4.
  • ROTOR-STAT/zb_cb_fm_1zone.jpeg
    ROTOR-STAT/zresidu.jpeg

    ROTOR37-KEPS

    (Back to top of page)

    Rotor 37: Turbulent flow

    ROTOR37_KEPS.py3D configuration
    Multi-Domain
    Moving frame
    Navier-Stokes
    KEps turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • NASA Rotor 37 - 3D.
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations (k,\epsilon ).
  • Mesh : O block domain with 201~\times~33~\times~97 points ;
  • H block domain with 201~\times~33~\times~97 points ;
  • O block domain in tip clearance with 201~\times~13~\times~17 points ;
  • H block domain in tip clearance with 89~\times~13~\times~17 points ;
  • Translation : no translation.
  • Rotation axis : Ox.
  • Rotation speed : {\Omega}~=~17188~tr/min.
  • Formulation : Relative conservative variables / Rotating Frame.
  • Jameson centered fluxes with artificial dissipation `dismrt' : [~0.5~,~0.032~,~1~].
  • Time integration : backward Euler.
  • Implicit scalar LU-SSOR : 2 relaxation sweeps.
  • Local time step.
  • Time step divided on boundaries.
  • Multigrid.
  • 3500 iterations, variable CFL= 1. to 40.
  • ROTOR37-KEPS/coupe_mach_R37.jpeg
    ROTOR37-KEPS/coupe_viscrapp_R37.jpeg
    ROTOR37-KEPS/debits_R37.jpeg
    ROTOR37-KEPS/zresidu.jpeg

    ROTOR37-MICHEL

    (Back to top of page)

    Rotor 37: Turbulent flow

    ROTOR37_MICHEL.py3D configuration
    Multi-Domain
    Moving frame
    Navier-Stokes
    Michel turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • NASA Rotor 37 - 3D.
  • Steady Navier-Stokes equations with Michel model.
  • Mesh : O block domain with 189~\times~35~\times~69 points ;
  • H block domain with 155~\times~21~\times~69 points ;
  • O block domain in tip clearance with 189~\times~15~\times~11 points ;
  • H block domain in tip clearance with 83~\times~13~\times~11 points ;
  • Translation : no translation.
  • Rotation axis : Ox.
  • Rotation speed : {\Omega}~=~17188~tr/min.
  • Formulation : Relative conservative variables / Rotating Frame.
  • Initial field : from previous 100 laminar iterations.
  • Jameson centered fluxes with artificial dissipation `dismrt' : [~0.5~,~0.032~,~1~].
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Time step divided on boundaries.
  • Mut limitor.
  • 5000 iterations, CFL=8.(blocks O and H), 6.(blocks Oj and Hj)
  • Flux extraction.
  • ROTOR37-MICHEL/r37mi_1.jpeg
    ROTOR37-MICHEL/r37mi_2.jpeg
    ROTOR37-MICHEL/r37mi_3.jpeg
    ROTOR37-MICHEL/r37mi_4.jpeg
    ROTOR37-MICHEL/zresidu.jpeg

    RodInCavity-A06

    (Back to top of page)

    2-D cavity with heated rod

    RodInCavity_A06.py2D-Plane configuration
    Multi-Domain
    Laminar
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Unsteady
    Low speed preconditionning
  • 2-D cavity with heated rod (both square, centered)
  • Unsteady laminar viscous flow (with existing steady state), with gravity terms.
  • Mesh:~ 8 domains with 201 \times 201 \times 2 mesh points total
  • Jameson centered fluxes with scalar artificial dissipation
  • Initial conditions:~Issued from unsteady solution at t=16.
  • Time integration:~ backward Euler.
  • Uniform time step = 0.05 .
  • low-speed preconditioning.
  • 2000 iterations in physical time step.
  • Final time ~:~100 s.
  • RodInCavity-A06/stream.jpeg
    RodInCavity-A06/psta.jpeg
    RodInCavity-A06/tsta.jpeg
    RodInCavity-A06/rovy.jpeg
    RodInCavity-A06/zresdu.jpeg

    S-tube-B-roe

    (Back to top of page)

    ShockTube 3D

    shockTube.py3D treatment
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    Explicit
    Unsteady
  • Shock tube.
  • Unsteady perfect gas flow.
  • Mesh:~ 50 \times 7 \times 7.
  • 3D computation.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps without freezing.
  • Explicit. Uniform time step.
  • 30 iterations.
  • S-tube-B-roe/S-tube-B-roe_1.jpeg

    S-tube-C

    (Back to top of page)

    ShockTube 1D

    shockTube1D.pyEuler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    Explicit
    Unsteady
  • Shock tube.
  • Unsteady perfect gas flow.
  • Mesh:~ 50 \times 2 \times 2.
  • 1D computation.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps without freezing.
  • Explicit. Uniform time step.
  • 30 iterations.
  • S-tube-C/S-tube-C_1.jpeg

    S-tube-p05

    (Back to top of page)

    ShockTube UpWind

    shockTubeUpw.py3D treatment
    Euler
    Backward-Euler
    Van Leer fluxes
    Explicit
    Unsteady
  • Shock tube.
  • Unsteady perfect gas flow.
  • Mesh:~ 50 \times 7 \times 7.
  • 3D computation.
  • Van Leer upwind fluxes.
  • Time integration:~ backward Euler.
  • Explicit. Uniform time step.
  • 30 iterations.
  • S-tube-p05/S-tube-p05_1.jpeg

    S3CH-02

    (Back to top of page)

    S3CH - MonoGrid

    elsa_fin.py3D configuration
    Multi-Domain
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • 3D wing-pylone-nacelle S3Ch configuration.
  • Steady transonic perfect gas flow.
  • Mesh:~440000 points into 70 blocks.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 2000 iterations, CFL=5.
  • S3CH-02/S3CH-02_1.jpeg
    S3CH-02/zresidu.jpeg

    S3CH-A-KO

    (Back to top of page)

    3D Wing Part

    S3CH_A_KO.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Matrix Dissipation
    LU
    Multi-Grid
  • S3Ch configuration :
  • Swept wing section between two walls + pylon and powered nacelle
  • M~=~0.82~\alpha~=~1.56~deg~Re_{AMC}~=~5.5~10^6
  • Mesh : 62 blocks, 2 129 000 nodes
  • Fan inlet massflow given.
  • Steady transonic turbulent flow.
  • Turbulence model : (k,\omega) Kok with Zheng limitor (kok\_diff\_cor=0)
  • Wall distance calculation along grid lines
  • Jameson centered fluxes (divergence form) for mean flow
  • with artificial dissipation "dismrt" : 0.5 0.016 1.0 0.5
  • Border treatment "current" for artificial viscosity
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction : 0.01
  • Gradients calculated on cell centers
  • Time integration : backward Euler
  • Implicit scalar LU-Relax : 4 relaxation sweeps, relaxscatype=viscous\_5p
  • Multigrid acceleration method on the mean equation sub-system :
  • 2 coarse grids, V-cycle, synchronous restriction,
  • arithmetic correction transfer on coarse grid,
  • correction transfer 'inv\_topo' from coarse to fine grid,
  • cell to node prolongation
  • artificial dissipation coefficients in coarse grids : 1.0 0.032
  • 2 sub-iterations for the turbulence sub-system
  • No filter to force field positivity.
  • Initialization : uniform flow
  • 1001 iterations, CFL=100.

  • S3CH-A-SA

    (Back to top of page)

    3D Wing Part

    S3CH_A_SA.py3D configuration
    Multi-Domain
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Backward-Euler
    Jameson fluxes
    Matrix Dissipation
    LU
    Multi-Grid
  • S3Ch configuration :
  • Swept wing section between two walls + pylon and powered nacelle
  • M~=~0.82~\alpha~=~1.56~deg~Re_{AMC}~=~5.5~10^6
  • Mesh : 62 blocks, 2 129 000 nodes
  • Fan inlet massflow given.
  • Steady transonic turbulent flow.
  • Turbulence model : (k,\omega) Kok with Zheng limitor (kok\_diff\_cor=0)
  • Wall distance calculation along grid lines
  • Jameson centered fluxes (divergence form) for mean flow
  • with artificial dissipation "dismrt" : 0.5 0.016 1.0 0.5
  • Border treatment "current" for artificial viscosity
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction : 0.01
  • Gradients calculated on cell centers
  • Time integration : backward Euler
  • Implicit scalar LU-Relax : 4 relaxation sweeps, relaxscatype=viscous\_5p
  • Multigrid acceleration method on the mean equation sub-system :
  • 2 coarse grids, V-cycle, synchronous restriction,
  • arithmetic correction transfer on coarse grid,
  • correction transfer 'inv\_topo' from coarse to fine grid,
  • cell to node prolongation
  • artificial dissipation coefficients in coarse grids : 1.0 0.032
  • 2 sub-iterations for the turbulence sub-system
  • No filter to force field positivity.
  • Initialization : uniform flow
  • 1001 iterations, CFL=100.

  • S3CH-MG-LUSSOR

    (Back to top of page)

    S3CH - MultiGrid - Lussor

    S3CH_MG_LUSSOR.py3D configuration
    Multi-Domain
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • 3D wing-pylone-nacelle S3Ch configuration.
  • Steady transonic perfect gas flow.
  • Mesh:~440000 points into 70 blocks.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Backward Euler
  • Implicit :~Scalar LU-SSOR
  • Multigrid convergence acceleration.
  • Local time step.
  • 300 iterations, CFL=100.
  • S3CH-MG-LUSSOR/S3CH-MG-LUSSOR_1.jpeg
    S3CH-MG-LUSSOR/zresidu.jpeg

    S3CH-MS-01

    (Back to top of page)

    3D Wing Part

    S3CH_MS_01.py3D configuration
    Multi-Domain
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • S3Ch configuration :
  • Swept wing section between two walls + pylon and powered nacelle
  • M~=~0.82~\alpha~=~1.56~deg~Re_{AMC}~=~5.5~10^6
  • Mesh : 62 blocks, 2 129 000 nodes
  • Fan inlet massflow given.
  • Steady transonic turbulent flow.
  • Turbulence model : (k,\omega) Kok with Zheng limitor (kok\_diff\_cor=0)
  • Wall distance calculation along grid lines
  • Jameson centered fluxes (divergence form) for mean flow
  • with artificial dissipation "dismrt" : 0.5 0.016 1.0 0.5
  • Border treatment "current" for artificial viscosity
  • Jameson centered fluxes with Roe correction for transport equations
  • Harten correction : 0.01
  • Gradients calculated on cell centers
  • Time integration : backward Euler
  • Implicit scalar LU-Relax : 4 relaxation sweeps, relaxscatype=viscous\_5p
  • Multigrid acceleration method on the mean equation sub-system :
  • 2 coarse grids, V-cycle, synchronous restriction,
  • arithmetic correction transfer on coarse grid,
  • correction transfer 'inv\_topo' from coarse to fine grid,
  • cell to node prolongation
  • artificial dissipation coefficients in coarse grids : 1.0 0.032
  • 2 sub-iterations for the turbulence sub-system
  • No filter to force field positivity.
  • Initialization : uniform flow
  • 1001 iterations, CFL=100.
  • S3CH-MS-01/Cp-36375.jpeg
    S3CH-MS-01/Cp-46000.jpeg
    S3CH-MS-01/Cp-54000.jpeg
    S3CH-MS-01/Cp-63750.jpeg
    S3CH-MS-01/skin_pressure.jpeg
    S3CH-MS-01/Cx.jpeg
    S3CH-MS-01/Cz.jpeg
    S3CH-MS-01/residuals-kok.jpeg
    S3CH-MS-01/residuals-kow.jpeg
    S3CH-MS-01/residuals-sa.jpeg

    S3CH-SSOR-MAT

    (Back to top of page)

    S3CH - MultiGrid - Lussor

    S3CH_SSOR_MAT.py3D configuration
    Multi-Domain
    Euler
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • 3D wing-pylone-nacelle S3Ch configuration.
  • Steady transonic perfect gas flow.
  • Mesh:~440000 points into 70 blocks.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Euler Backward
  • Implicit :~matricial LU-SSOR with implicitation of 4th-order dissipation
  • Multigrid convergence acceleration.
  • Local time step.
  • 300 iterations, CFL=100.
  • S3CH-SSOR-MAT/S3CH-SSOR-MAT_1.jpeg
    S3CH-SSOR-MAT/zresidu.jpeg

    SPOILER-CHIMERA

    (Back to top of page)

    3D Wing profile with spoiler resolved by a Chimera Technique

    SPOILER_CHIMERA.py3D configuration
    Multi-Domain
    Chimera
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
    Parallel
  • 3D Wing profile with spoiler resolved by a Chimera Technique.
  • Chimera context : depth = 1, interp = adt, explicit interpolation.
  • use of "double wall".
  • use of "xray" mask.
  • Parallel (MPI) computing.
  • Steady turbulent viscous flow.
  • Turbulent model : k-omega Kok.
  • Multi-domain with overlaping (21 blocks).
  • Jameson centered fluxes with artificial dissipation `dismrt' : [~0.5~,~0.032~,~1~].
  • Time integration: Backward Euler
  • Implicit scalar LUSSOR.
  • 1500 iterations. Cfl = 100.0
  • SPOILER-CHIMERA/spoiler-chimera-1.jpeg
    SPOILER-CHIMERA/spoiler-chimera-2.jpeg
    SPOILER-CHIMERA/spoiler-chimera-3.jpeg
    SPOILER-CHIMERA/zresidu.jpeg

    SQNZ-MDPAR-01

    (Back to top of page)

    SquaredNozzle MultiDomain Parallel

    eu8dompar.py3D configuration
    Multi-Domain
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    Explicit
    Parallel
  • 3D square nozzle (one quarter is computed).
  • Shockless choked steady perfect gas flow.
  • Mesh:~ 45 \times 17 \times 17 cut into 8 different-size blocks (4 blocks 21 \times 9 \times 9 and 4 blocks 25 \times 9 \times 9 ).
  • Parallel computation : 4 processors.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Explicit. Local time step.
  • 2000 iterations, CFL=2.
  • SQNZ-MDPAR-01/zresidu.jpeg
    SQNZ-MDPAR-01/SQNZ-MDPAR-01_1.jpeg

    SQNZ-MDPAR-03

    (Back to top of page)

    SquaredNozzle MultiDomain Parallel

    eu2domi_2node.py3D configuration
    Multi-Domain
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    Explicit
    Parallel
  • 3D square nozzle (one quarter is computed).
  • Shockless choked steady perfect gas flow.
  • Mesh:~ 45 \times 17 \times 17 cut into 2 blocks 23 \times17 \times 17 .
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Explicit.
  • Local time step.
  • Parallel mode calculation, 2 processors.
  • 1200 iterations, CFL=1.
  • SQNZ-MDPAR-03/zresidu.jpeg
    SQNZ-MDPAR-03/SQNZ-MDPAR-03_1.jpeg

    SQNZ-NS-06

    (Back to top of page)

    Squared Nozzle: Laminar, 3 domains

    SQNZ_NS_06.py3D configuration
    Multi-Domain
    Navier-Stokes
    Laminar
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
  • 3D square nozzle (one quarter is computed).
  • Shockless choked laminar viscous steady flow.
  • Mesh:~ 45 \times 17 \times 17 cut into 3 blocks 45 \times 7 \times 17, 45 \times 5 \times 17 and 45 \times 7 \times 17.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Adiabatic wall boundary condition.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration (only 2 cells on the coarser grid of one block).
  • Local time step.
  • 2000 iterations, CFL=4.
  • SQNZ-NS-06/SQNZ-NS-06_1.jpeg
    SQNZ-NS-06/SQNZ-NS-06_2.jpeg
    SQNZ-NS-06/zresidu.jpeg

    SQNZ-OptAdj

    (Back to top of page)

    Squared Nozzle - Euler - Shape Optimization (adjoint gradient computation)

    SQNZ_OptAdj.py3D configuration
    Shape optimization adjoint equation
    Euler
    Backward-Euler
    Roe fluxes
    LU
  • Brochet - Nozzle
  • Shockless inviscid flow in a 3D choked squared nozzle
  • Euler equations, gradient computation by adjoint method, second order Roe upwind fluxes.
  • Tests: Wall slip, subsonic inlet and subsonic outlet.
  • boundary type `wallslip'
  • Inlet condition : boundary type `inlet'
  • Outlet condition : boundary type `outsup'
  • Symmetric condition : boundary type `sym'
  • Mesh:~ 45 \times 17 \times 17 .
  • Jameson centered scheme with artificial dissipation
  • Euler backward with local time stepping
  • Implicit LU
  • CFL =~ 10.
  • SQNZ-OptAdj/adj1-rho.jpeg

    SQNZ10

    (Back to top of page)

    Nozzle: NoMatch

    eu2dom_nm.py3D configuration
    Multi-Domain
    Non-coincident quasi-conservative match
    Euler
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
  • 3D nozzle choked (with shock) configuration.
  • Steady inviscid perfect gas flow.
  • Mesh:~5000 points into 2 blocks.
  • Non-coincident quasi-conservative match (also called "patch grid")
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration:~ Backward-Euler.
  • Implicit :~Scalar LU-SSOR
  • Local time step.
  • 300 iterations, CFL=1000.
  • SQNZ10/SQNZ10_1.jpeg
    SQNZ10/SQNZ10_2.jpeg
    SQNZ10/SQNZ10_3.jpeg

    StatorBlade-OptLin

    (Back to top of page)

    Stator vane 3D - Euler - Shape Optimization (linearized gradient computation)

    StatorBlade_OptLin.py3D configuration
    Shape optimization linearized equation
    Euler
    Backward-Euler
    Roe fluxes
    LU
  • Basic stator blade geometry (2 domains, coarse mesh) also called RED3D.
  • Euler equations, gradient computation by linearized method, second order Roe upwind fluxes.
  • Tests: Wall slip, Subsonic inlet and Subsonic outlet.
  • Time integration :~ Backward Euler.
  • Implicit LU
  • CFL =~ 10
  • StatorBlade-OptLin/zresidu1.jpeg
    StatorBlade-OptLin/zresidu2.jpeg

    Step-ASM-TL

    (Back to top of page)

    Step - 2D ASM two layer

    Step_ASM_TL.py2D-Plane configuration
    Multi-Domain
    Navier-Stokes
    ASM turbulence model
    Two layer
    Runge-Kutta
    Jameson fluxes
    IRS
    Multi-Grid
  • 2D back step (Driver \& Seegmiller)
  • Steady turbulent viscous flow.
  • Turbulent model: 2 transport equations ASM(SZL) + two layer modelisation.
  • Meshes: ~ 2 blocks (53 \times 41 \times 2, 159 \times 95 \times 2).
  • Initial field : 5 laminar iterations starting from uniform external state.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.016~,~1~].
  • Harten c{\oe}fficient for turbulent equations : 0.05.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 4980 iterations, variable CFL from 1. up to 6.
  • Step-ASM-TL/step_asmtl.jpeg
    Step-ASM-TL/cf_step_asmtl.jpeg
    Step-ASM-TL/zresidu.jpeg

    Tube-Collect-Spal

    (Back to top of page)

    Pipe - Collect and injrot boundary condition

    Tube_Collect_Spal.py3D configuration
    Moving frame
    Spalart-Allmaras turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • This test case computes the flow in a pipe ;
  • For validatation of the collect and injrot boundary conditions ;
  • A 'user' data frame is defined for each injection condition
  • All quantities are normalized by stagnation conditions.
  • Steady turbulent viscous flow.
  • Turbulence model: 1 transport equation (Spalart-Allmaras).
  • Mesh:~ 61 \times 29 \times 73 ;
  • Jameson centered fluxes with artificial dissipation `dismrt';
  • Time integration : Runge-Kutta 4 steps;
  • Implicit residual smoothing ;
  • 1000 iterations, CFL=15.
  • Tube-Collect-Spal/tuyau.jpeg
    Tube-Collect-Spal/zresidu.jpeg

    VEGA-2HOH

    (Back to top of page)

    S/R MultiStage - 3D turbulent Michel

    vega_2hoh.py3D configuration
    Multi-Domain
    Turbomachinery multi-stage match
    Navier-Stokes
    Michel turbulence model
    Runge-Kutta
    Jameson fluxes
    IRS
  • VEGA2 3D-annular stator-rotor configuration.
  • Steady turbulent viscous flow.
  • Turbulence model: Michel.
  • Mesh:~ 6 blocks (Total : 473 888 cells) with (HOH)-(HOH) topology.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Initial conditions:~ 100 iterations in laminar from 1-D initialization.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=4.
  • VEGA-2HOH/vega_2hoh_1.jpeg
    VEGA-2HOH/vega_2hoh_2.jpeg
    VEGA-2HOH/zresidu.jpeg
    VEGA-2HOH/vega_2hoh_3.jpeg
    VEGA-2HOH/vega_2hoh_4.jpeg

    VEGA-2HOH-02

    (Back to top of page)

    S/R Multistage with Blade Reduction - 3D Laminar

    VEGA_2HOH_02.py3D configuration
    Multi-Domain
    Turbomachinery multi-stage match
    Moving frame
    Laminar
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Unsteady
  • VEGA2 3D-annular stator-rotor configuration with only 7 radial planes
  • Unsteady laminar viscous flow with stage reduction method.
  • Mesh:~ 8 blocks (Total : 127 968 cells) with (OHHH)-(OHHH) topology.
  • Jameson centered fluxes with artificial dissipation `dismrt'.
  • Initial conditions:~ 1000 iterations of a laminar steady computation
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Global time step.
  • 5500 iterations (to perform 5 unsteady phenomena period)
  • VEGA-2HOH-02/vega_2hoh_02.jpeg

    VEGA2-STAGE-MXPL

    (Back to top of page)

    Steady - Stage-MXPL

    VEGA2_STAGE_MXPL.py3D configuration
    Multi-Domain
    Turbomachinery multi-stage match
    Moving frame
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Roe fluxes
  • VEGA2 stator-rotor : light configuration at mid-span.
  • Steady transonic turbulent viscous flow.
  • Turbulence model :~ 2-transport equations model, Smith kl model.
  • Moving Frame :~ No translation - Rotation axis Ox
  • Formulation :~ relative velocity / rotating frame.
  • Mesh :~ 8 blocks (Total : 127 968 cells) with (OHHH)-(OHHH) topology, 7 radial planes at mid-span.
  • Jameson centered fluxes with artificial dissipation `dissca' for mean flow.
  • Roe scheme for transport equations.
  • Harten correction :~ 0.01
  • Time integration :~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Initial conditions :~ 100 iterations in laminar from 1-D initialization.
  • Adiabatic wall.
  • Mixing plane condition at the interface stator-rotor :
  • mxpl\_avermean=riemann, mxpl\_num=characteristic, mxpl\_avertur=conservative.
  • 700 iterations, CFL=5.
  • VEGA2-STAGE-MXPL/res_dep_pressure_nocoinc_kl.jpeg

    VEGA2-STAGE-MXPL-MG

    (Back to top of page)

    Multistage - Multigrid

    VEGA2_STAGE_MXPL_MG.py3D configuration
    Turbomachinery multi-stage match
    Moving frame
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • VEGA2 stator-rotor : light configuration at mid-span.
  • Steady transonic turbulent viscous flow.
  • Turbulence model :~ komega\_wilcox.
  • Moving Frame :~ No translation - Rotation axis Ox
  • Formulation :~ relative velocity / rotating frame.
  • Mesh :~ 8 blocks (Total : 127 968 cells) with (OHHH)-(OHHH) topology, 7 radial planes at mid-span.
  • Jameson centered fluxes with artificial dissipation `dissca' for mean flow.
  • Roe scheme for transport equations.
  • Harten correction :~ 0.01
  • Time integration :~ backward Euler.
  • Multigrid convergence acceleration method (one coarse grid).
  • Implicit scalar LU-Relax: relaxscatype=viscous\_3p.
  • Local time step.
  • Initial conditions :~ 100 iterations in laminar from 1-D initialization.
  • Adiabatic wall.
  • Mixing plane condition at the interface stator-rotor :
  • mxpl\_avermean=riemann, mxpl\_num=characteristic, mxpl\_avertur=conservative.
  • Non-coincident radial match along lines.
  • 5000 iterations, CFL=20.
  • VEGA2-STAGE-MXPL-MG/res_deb_p_ko_wilcox.jpeg

    VEGA2-STAGE-RED

    (Back to top of page)

    Unsteady - Stage-Red

    VEGA2_STAGE_RED.py3D configuration
    Multi-Domain
    Turbomachinery multi-stage match
    Moving frame
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Backward-Euler
    Jameson fluxes
    Roe fluxes
    LU
    Unsteady
  • VEGA2 stator-rotor : light configuration at mid-span.
  • Unsteady transonic turbulent viscous flow on 10 unsteady periods.
  • Rerun of former unsteady computation performed on 20 periods.
  • Turbulence model :~ 1-transport equation model, Spalart-Allmaras model.
  • Moving Frame :~ No translation - Rotation axis Ox
  • Formulation :~ relative velocity / rotating frame.
  • Mesh :~12 blocks (Total : 188 256 cells) with (OHHH)-2(OHHH) topology, 7 radial planes at mid-span.
  • Jameson centered fluxes with artificial dissipation `dissca' for mean flow.
  • Roe scheme for transport equations.
  • Harten correction :~ 0.01
  • Time integration :~ backward Euler
  • Scalar LU-Relax
  • Global time step.
  • Initial conditions :~ unsteady computation with reduced blade count technique (20 periods)
  • Adiabatic wall.
  • periodicity condition on azimutal boundaries.
  • Reduced blade count technique on stage interface.
  • VEGA2-STAGE-RED/vega2_7c_debits.jpeg
    VEGA2-STAGE-RED/vega2_7c_ps_entr_dilat.jpeg

    Wing-Body-F4-Lin

    (Back to top of page)

    F4 Wing with body- 3D Euler - Shape Optimization

    f4_va_lin_2r_nrg.py3D configuration
    Multi-Domain
    Shape optimization linearized equation
    Euler
    Backward-Euler
    Roe fluxes
    LU
  • WingF4 3D. M_{\inf}~=~0.8~,~\alpha~=~0.93~.
  • Mesh: 153~\times~25~\times~41.
  • Steady transonic inviscid flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=4.
  • Second order Roe Upwind fluxes (van Albada limiter).
  • Time integration: backward Euler.
  • Gradient computation: linearized method.
  • One shape parameter: angular twist.
  • Calculation of CL, CD_{p}, CD_{w} and CD_{i} gradients.
  • Wing-Body-F4-Lin/drhoda1.jpeg
    Wing-Body-F4-Lin/zresidu1.jpeg

    WingDefRoeAdj

    (Back to top of page)

    Wing - turbulent SA - parallel - Adjoint method

    # Error: No description for test WingDefRoeAdj.py
    WingDefRoeAdj.py3D configuration
    Multi-Domain
    Shape optimization adjoint equation
    Spalart-Allmaras turbulence model
    Backward-Euler
    Multi-Grid
    Parallel
  • No description
  • WingDefRoeAdj/results.jpeg
    WingDefRoeAdj/zresidus.jpeg

    WingF4-KL

    (Back to top of page)

    F4 Wing - 3D NS turbulent KL

    WingF4_KL.py3D configuration
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • F4 Wing - 3D.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 257 \times 49 \times 89 .
  • Initial conditions:~solution obtained after 13000 iterations
  • with same artificial dissipation coefficients and same CFL.
  • Jameson centered fluxes
  • with artificial dissipation dismrt : ~0.5~,~0.016~,~1.0~,~0.5~.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 10000 iterations, CFL=1.
  • WingF4-KL/WingF4-KL_1.jpeg
    WingF4-KL/WingF4-KL_2.jpeg
    WingF4-KL/zresidu.jpeg

    WingM6-Blx-OptLin

    (Back to top of page)

    M6 Wing - 3D NS turbulent Blx - Shape optimization

    wingm6_BL2_optlin.py3D configuration
    Shape optimization linearized equation
    Navier-Stokes
    Baldwin-Lomax turbulence model
    Backward-Euler
    Roe fluxes
    LU
  • WingM6 3D. M_{\inf}~=~0.83~,~\alpha~=~3.06~, ~Re_{\inf}~=~14.61~10^6.
  • Mesh: 193~\times~49~\times~65.
  • Steady transonic turbulent flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=5.
  • Turbulence model: Baldwin-Lomax
  • Second order Roe Upwind flux.
  • Time integration: backward Euler.
  • Gradient computation: linearized method.
  • One shape parameter: angular twist.
  • Calculation of CL, CD_{nf} and CD_{ff} gradients.
  • WingM6-Blx-OptLin/drhoda1.jpeg
    WingM6-Blx-OptLin/zresidu1.jpeg

    WingM6-KL

    (Back to top of page)

    M6 Wing - 3D NS turbulent KL

    WingM6_KL.py3D configuration
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • M6 Wing - 3D.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 193 \times 49 \times 65 .
  • Uniform Initial conditions.
  • Jameson centered fluxes
  • with artificial dissipation dissca : ~0.5~,~0.032~,~1.0~.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=2.
  • WingM6-KL/psta.jpeg
    WingM6-KL/zresidu.jpeg

    WingM6-KO-SST-SCHEME

    (Back to top of page)

    M6 Wing - 3D NS turbulent Blx

    WingM6_KO_SST_SCHEME.py3D configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • M6 Wing - 3D.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 193 \times 49 \times 65 .
  • Uniform Initial conditions.
  • Jameson centered fluxes
  • with artificial dissipation dissca : ~0.5~,~0.032~,~1.0~.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=2.
  • Configuration 1: ausmp scheme.
  • Configuration 2: jameson scheme.
  • Configuration 3: rbco2 scheme.
  • Configuration 4: rbco3 scheme.
  • WingM6-KO-SST-SCHEME/WingM6-Cp.jpeg
    WingM6-KO-SST-SCHEME/WingM6_residual_ro.jpeg
    WingM6-KO-SST-SCHEME/WingM6_residual_rok.jpeg

    WingM6-KO-SST-ausmp

    (Back to top of page)

    M6 Wing - 3D NS turbulent Blx - AUSMP scheme

    WingM6_KO_SST_ausmp.py3D configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    AUSMP scheme
    LU
    Multi-Grid
  • M6 Wing - 3D.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 193 \times 49 \times 65 .
  • Uniform Initial conditions.
  • Jameson centered fluxes
  • with artificial dissipation dissca : ~0.5~,~0.032~,~1.0~.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=2.

  • WingM6-KO-SST-jameson

    (Back to top of page)

    M6 Wing - 3D NS turbulent Blx - Jameson scheme

    WingM6_KO_SST_jameson.py3D configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • M6 Wing - 3D.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 193 \times 49 \times 65 .
  • Uniform Initial conditions.
  • Jameson centered fluxes
  • with artificial dissipation dissca : ~0.5~,~0.032~,~1.0~.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=2.

  • WingM6-KO-SST-rbci

    (Back to top of page)

    M6 Wing - 3D NS turbulent Blx - rbci scheme

    WingM6_KO_SST_rbci.py3D configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    rbci scheme
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • M6 Wing - 3D.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 193 \times 49 \times 65 .
  • Uniform Initial conditions.
  • Jameson centered fluxes
  • with artificial dissipation dissca : ~0.5~,~0.032~,~1.0~.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=2.

  • WingM6-KO-SST-rbco2

    (Back to top of page)

    M6 Wing - 3D NS turbulent Blx - rbco2 scheme

    WingM6_KO_SST_rbco2.py3D configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    rbc scheme
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • M6 Wing - 3D.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 193 \times 49 \times 65 .
  • Uniform Initial conditions.
  • Jameson centered fluxes
  • with artificial dissipation dissca : ~0.5~,~0.032~,~1.0~.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=2.

  • WingM6-KO-SST-rbco3

    (Back to top of page)

    M6 Wing - 3D NS turbulent Blx - rbco3 scheme

    WingM6_KO_SST_rbco3.py3D configuration
    Navier-Stokes
    KO turbulence model
    Backward-Euler
    rbc scheme
    Scalar Dissipation with Martinelli correction
    LU
    Multi-Grid
  • M6 Wing - 3D.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 193 \times 49 \times 65 .
  • Uniform Initial conditions.
  • Jameson centered fluxes
  • with artificial dissipation dissca : ~0.5~,~0.032~,~1.0~.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 3000 iterations, CFL=2.

  • WingM6-KOucpd-Adj

    (Back to top of page)

    M6 Wing - 3D NS turbulent KO uncoupled - Shape optimization

    wingm6_KO_optlin_bas.py3D configuration
    Shape optimization adjoint equation
    Navier-Stokes
    Baldwin-Lomax turbulence model
    Backward-Euler
    Roe fluxes
    LU
  • WingM6 3D. M_{\inf}~=~0.83~,~\alpha~=~3.06~, ~Re_{\inf}~=~14.61~10^6.
  • Mesh: 193~\times~49~\times~65.
  • Steady transonic turbulent flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=0.00000001
  • Turbulence model: 2 transport equations (k-\omega Wilcox).
  • Second order Roe Upwind flux (van Albada limiter).
  • Time integration: backward Euler.
  • Explicit phase.
  • Gradient computation: adjoint method.
  • Calculation of CL, CD_{nf} and CD_{ff} gradients.
  • Shape parameter: angular twist.
  • WingM6-KOucpd-Adj/adj-rho.jpeg
    WingM6-KOucpd-Adj/zresidu1.jpeg
    WingM6-KOucpd-Adj/zresidu2.jpeg

    WingM6-Michel-Lin

    (Back to top of page)

    M6 Wing 1972 - 3D config. - Linearization of Michel \& al. turbulent model

    WingM6_Michel_Lin.py3D configuration
    Shape optimization linearized equation
    Michel turbulence model
    Backward-Euler
    Roe fluxes
    LU
  • M6 Wing 1972 - 3D config.
  • Minf=0.836, Reinf=1.47E06, attack angle = 3.06
  • Steady transonic turbulent viscous flow.
  • Turbulence model: Michel \& al.
  • Mesh:~ 193 \times 49 \times 65 .
  • Initial converged field.
  • Implicit residual smoothing.
  • Local time step.
  • Gradient computation: linearized method.
  • Linearization of Michel \& al. turbulent model.
  • One Shape parameter : angular twist.
  • Calculation of CL, CDnf and CDff gradients.
  • WingM6-Michel-Lin/WingM6_Michel_Lin_NewtonResiduals.jpeg
    WingM6-Michel-Lin/WingM6_Michel_Lin_ConsResiduals.jpeg
    WingM6-Michel-Lin/WingM6_Michel_Lin_Sensibilities1.jpeg
    WingM6-Michel-Lin/WingM6_Michel_Lin_Sensibilities2.jpeg
    WingM6-Michel-Lin/WingM6_Michel_Lin_Sensibilities3.jpeg

    WingM6-SA-OptAdj-MPI

    (Back to top of page)

    M6 Wing - 3D NS turbulent SA - parallel - Adjoint methode

    WingM6_SA_OptAdj_MPI.py3D configuration
    Multi-Domain
    Shape optimization adjoint equation
    Navier-Stokes
    Spalart-Allmaras turbulence model
    Backward-Euler
    Roe fluxes
    LU
    Parallel
  • WingM6 3D. M_{\inf}~=~0.84~,~\alpha~=~3.00~, ~Re_{\inf}~=~1.46~10^7.
  • Mesh: multiblocks, 620042 nodes.
  • Steady transonic turbulent flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 4000 iterations)
  • 10 iterations, CFL=100.0
  • Turbulence model: 1 transport equation (Spalart Allmaras).
  • Second order Roe Upwind flux (van Albada limiter).
  • Time integration: backward Euler.
  • Scalar lussor implicit phase.
  • Gradient computation: adjoint method.
  • Calculation of CL, CD_{nf} and CD_{ff} gradients.
  • Shape parameter: angular twist.
  • Ordoning list of blocks corresponding to order 1 handling
  • WingM6-SA-OptAdj-MPI/adj1rho.jpeg
    WingM6-SA-OptAdj-MPI/zresidu1.jpeg
    WingM6-SA-OptAdj-MPI/zresidu2.jpeg

    naca-KL-LS

    (Back to top of page)

    NACA0012: Preconditionning Low Speed Turbulent Multigrid

    naca_KL_LS.py2D-Plane configuration
    Navier-Stokes
    KL turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
    Multi-Grid
    Low speed preconditionning
  • NACA0012 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.1, \alpha~=~10\deg.
  • Steady transonic turbulent viscous flow.
  • Turbulence model: 2 transport equations (k,l).
  • Mesh:~ 257 \times 65 \times 2 .
  • Initial field : laminar computation (20 iterations)
  • Jameson centered fluxes with artificial dissipation `dismrt' : [~0.0~,~0.032~,~1~,~0.5~].
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Multigrid convergence acceleration method, 1 coarse grid, V cycle.
  • Local time step.
  • Low speed preconditionning (Weiss et Smith)
  • 2980 iterations, CFL=5.
  • naca-KL-LS/naca-KL-LS_1.jpeg
    naca-KL-LS/zresidu.jpeg

    naca-LMG-nm

    (Back to top of page)

    NACA: AMR and nomatch

    # Error: No description for test naca_LMG_nm.py
    naca_LMG_nm.py2D-Plane configuration
    Multi-Domain
    Non-coincident quasi-conservative match
    Euler
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Local Multi-Grid (AMR)
  • No description

  • naca-ale

    (Back to top of page)

    NACA0064 : deformation ALE

    naca_ale.py2D-Plane configuration
    ALE
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Unsteady
  • 2D NACA0064 Oscillating Profile
  • Normalization : density and sound velocity for conditions at infinity, chord length
  • Infinite Mach number ---> ~M~=~0.796
  • Frequency ---> ~k~=~0.202
  • Rotation speed ---> ~\omega~=~2.*k*Vinf~ =~0.321584
  • Rotation axis ---> OY
  • Translation speed (along OX) = Flow velocity at infinity
  • Mean angle and harmonics of motion :
  • alp0~=~0.
  • alp1s~=~-1.01 degre
  • alp1c~=~alp2c~=~alp2s~=~0.
  • Wing motion ---> alp(t)~=~alp0 + alp1s*sin(\omega*t)
  • Unsteady inviscid perfect gas flow.
  • Absolute frame, Motion with ALE.
  • Mesh:~257 \times 33 \times 2.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~1~,~0.032~,~1~].
  • Time integration:~ Runge-Kutta 4 steps without freezing.
  • Implicit residual smoothing.
  • Time step = 0.02
  • Slip condition .
  • 4000 iterations.
  • naca-ale/naca-ale_1.jpeg
    naca-ale/zresidu.jpeg

    naca-rigid

    (Back to top of page)

    NACA0064: Rigid motion

    naca_rigid.py2D-Plane configuration
    Moving frame
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Unsteady
  • 2D NACA0064 Oscillating Profile
  • Normalization : density and sound velocity for conditions at infinity, chord length
  • Infinite Mach number ---> ~M~=~0.796
  • Frequency ---> ~k~=~0.202
  • Rotation speed ---> ~\omega~=~2.*k*Vinf~ =~0.321584
  • Rotation axis ---> OY
  • Translation speed (along OX) = Flow velocity at infinity
  • Mean angle and harmonics of motion :
  • alp0~=~0.
  • alp1s~=~-1.01 degre
  • alp1c~=~alp2c~=~alp2s~=~0.
  • Wing motion ---> alp(t)~=~alp0 + alp1s*sin(\omega*t)
  • Unsteady inviscid perfect gas flow.
  • Rotating frame, Absolute velocity formulation.
  • Mesh:~257 \times 33 \times 2.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.032~,~1~].
  • Time integration:~ Runge-Kutta 4 steps without freezing.
  • Implicit residual smoothing.
  • Time step = 0.01
  • Slip condition .
  • 8000 iterations.
  • naca-rigid/naca-rigid_1.jpeg
    naca-rigid/zresidu.jpeg

    naca-rigid-BLX-dts

    (Back to top of page)

    NACA0064: Rigid motion

    naca_rigid_BLX_dts.py2D-Plane configuration
    Moving frame
    Navier-Stokes
    Baldwin-Lomax turbulence model
    Backward-Euler
    Dual time step
    Jameson fluxes
    Scalar Dissipation
    LU
    Unsteady
  • 2D NACA0064 Oscillating Profile
  • Normalization : density and sound velocity for conditions at infinity, chord length
  • Infinite Mach number ---> ~M~=~0.796
  • Frequency ---> ~k~=~0.202
  • Rotation speed ---> ~\omega~=~2.*k*Vinf~ =~0.321584
  • Rotation axis ---> OY
  • Translation speed (along OX) = Flow velocity at infinity
  • Mean angle and harmonics of motion :
  • alp0~=~0.
  • alp1s~=~-1.01 degre
  • alp1c~=~alp2c~=~alp2s~=~0.
  • Wing motion ---> alp(t)~=~alp0 + alp1s*sin(\omega*t)
  • Unsteady viscous perfect gas flow.
  • Rotating frame, Absolute velocity formulation.
  • Mesh:~453 \times 70 \times 2.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.032~,~1~].
  • Time integration: backwardeuler.
  • Lussormat.
  • Time Step = 0.25
  • Wall condition .
  • 120 iterations.
  • 150 iterations max each External Loop.
  • naca-rigid-BLX-dts/naca-rigid-BLX-dts.jpeg
    naca-rigid-BLX-dts/zresidu.jpeg

    naca-sliding

    (Back to top of page)

    NACA0064: Rigid motion Sliding meshes

    elsa_dts_configvol.py2D-Plane configuration
    Moving frame
    Euler
    Backward-Euler
    Dual time step
    Jameson fluxes
    Scalar Dissipation
    LU
  • 2D NACA0012 Oscillating Profile with sliding meshes
  • Normalization : density and sound velocity for conditions at infinity, chord length
  • Infinite Mach number ---> ~M~=~0.755
  • Frequency ---> ~k~=~0.0814
  • Rotation speed ---> ~\omega~=~2.*k*Vinf~ =~0.122914
  • Rotation axis ---> OY
  • Translation speed (along OX) = Flow velocity at infinity
  • Mean angle and harmonics of motion :
  • alp0~=~0.
  • alp1s~=~2.51 degre
  • alp1c~=~alp2c~=~alp2s~=~0.
  • Wing motion ---> alp(t)~=~alp0 + alp1s*sin(\omega*t)
  • Inviscid perfect gas flow.
  • Absolute velocity in relative frame.
  • Four Meshes with 2 meshes for the interior O and 2 others for the exterior O
  • Interior meshes : ~97 \times 25 \times 2.
  • Exterior meshes : ~97 \times 33 \times 2.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.016~,~0.5~].
  • Time integration:~ Backward-Euler.
  • Implicit scalar LU-SSOR.
  • Multigrid convergence acceleration (2 coarse grids, 2 iterations on coarse grid).
  • Dual time stepping method with maximum number of dual time step iterations = 50.
  • and convergence test on density = 1.e-3
  • Time step = 1.278
  • Slip condition.
  • 200 iterations.
  • naca-sliding/naca-sliding.jpeg
    naca-sliding/zresidu.jpeg

    naca-sliding-MPI

    (Back to top of page)

    NACA0064: Rigid motion Sliding meshes

    elsa_dts_configvol_mpi.py2D-Plane configuration
    Moving frame
    Euler
    Backward-Euler
    Dual time step
    Jameson fluxes
    Scalar Dissipation
    LU
    Parallel
  • 2D NACA0012 Oscillating Profile with sliding meshes
  • Normalization : density and sound velocity for conditions at infinity, chord length
  • Infinite Mach number ---> ~M~=~0.755
  • Frequency ---> ~k~=~0.0814
  • Rotation speed ---> ~\omega~=~2.*k*Vinf~ =~0.122914
  • Rotation axis ---> OY
  • Translation speed (along OX) = Flow velocity at infinity
  • Mean angle and harmonics of motion :
  • alp0~=~0.
  • alp1s~=~2.51 degre
  • alp1c~=~alp2c~=~alp2s~=~0.
  • Wing motion ---> alp(t)~=~alp0 + alp1s*sin(\omega*t)
  • Inviscid perfect gas flow.
  • Absolute velocity in relative frame.
  • Four Meshes with 2 meshes for the interior O and 2 others for the exterior O
  • Interior meshes : ~97 \times 25 \times 2.
  • Exterior meshes : ~97 \times 33 \times 2.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.016~,~0.5~].
  • Time integration:~ Backward-Euler.
  • Implicit scalar LU-SSOR.
  • Multigrid convergence acceleration (2 coarse grids, 2 iterations on coarse grid).
  • Dual time stepping method with maximum number of dual time step iterations = 50.
  • and convergence test on density = 1.e-3
  • Time step = 1.278
  • Slip condition.
  • Parallel mode, 4 processors
  • 200 iterations.
  • naca-sliding-MPI/naca-sliding.jpeg

    naca-underwall

    (Back to top of page)

    NACA0012 under a wall : Chimera, Euler

    naca_underwall.py2D-Plane configuration
    Multi-Domain
    Chimera
    Euler
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
  • NACA0012 wing profile under a Wall.
  • Chimera context : depth = 2, explicit interpolation.
  • Infinite flow conditions : {M_\infty}~=~0.80, {p_\infty}~=~10.000~Pa, {\rho_\infty}~=~1.29~kg.m^{-3}.
  • Multi-domain with overlaping (Chimera).
  • Steady transonic perfect gas flow.
  • Mesh NACA0012 :~33 \times 193 \times 2.
  • Mesh Wall :~100 \times 88 \times 2.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Time integration: Backwardeuler.
  • Explicit.
  • Local time step.
  • 3000 iterations, CFL=100.
  • Configuration 1 : Cartesian elements and infinite plane Masks.
  • Configuration 2 : Parallelepiped and infinite plane Masks.
  • Configuration 3 : Implicit Hole Cutting.
  • Configuration 4 : Patch Assembly.
  • naca-underwall/chim_2d_01_blanking.jpeg
    naca-underwall/chim_2d_01_mach.jpeg
    naca-underwall/chim_2d_01_pinf.jpeg
    naca-underwall/zresidu.jpeg

    naca01-EXTRACT

    (Back to top of page)

    NACA0012

    naca01_EXTRACT.py2D-Plane configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • NACA0012 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.85, \alpha~=~1\deg.
  • Steady transonic perfect gas flow.
  • Mesh:~ 257 \times 33 \times 2 .
  • Initial field : far-field state.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.032~,~1~].
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 1500 iterations, CFL=15.
  • Flux extraction.
  • naca01-EXTRACT/naca01-EXTRACT_1.jpeg
    naca01-EXTRACT/naca01-EXTRACT_2.jpeg
    naca01-EXTRACT/naca01-EXTRACT_3.jpeg
    naca01-EXTRACT/zresidu.jpeg

    naca10

    (Back to top of page)

    NACA0012: Multigrid, Scalar Dissipation

    naca10.py2D-Plane configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
  • NACA0012 2D wing profile.
  • Steady transonic perfect gas flow.
  • Infinite flow : {M_\infty}~=~0.85, \alpha~=~1\deg.
  • Mesh:~257 \times 33 \times 2.
  • Initial field : far-field state.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.032~,~1~].
  • Slip boundary condition : extrap~=~0.,~prescor~=~0.
  • Time integration : backwardeuler
  • Implicit phase: Lurelax-sca
  • Multigrid convergence acceleration : V-cycle on 2 coarse grids,
  • arithmetic mean for prolongement operator, synchronous restriction.
  • Local time step.
  • 2000 iterations, CFL=1000.
  • naca10/isoM.jpeg
    naca10/zresidual.jpeg

    naca11

    (Back to top of page)

    NACA0012: Backward Euler, LDU, Multigrid, Scalar Dissipation

    naca11.py2D-Plane configuration
    Euler
    Backward-Euler
    Jameson fluxes
    Scalar Dissipation
    LU
    Multi-Grid
  • NACA0012 2D wing profile.
  • Steady transonic perfect gas flow.
  • Infinite flow : {M_\infty}~=~0.85, \alpha~=~1\deg.
  • Mesh:~257 \times 33 \times 2.
  • Initial field : far-field state.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.032~,~1~].
  • Slip boundary condition : extrap~=~0.,~prescor~=~0.
  • Time integration : Eulerbackward.
  • Implicit : scalar LU-Relax.
  • Multigrid convergence acceleration : V-cycle on 2 coarse grids,
  • arithmetic mean for prolongement operator, synchronous restriction.
  • Local time step.
  • 1000 iterations, CFL=5.
  • naca11/naca11_1.jpeg
    naca11/zresidu.jpeg

    naca6

    (Back to top of page)

    NACA0012: Matrix Viscosity

    naca6.py2D-Plane configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Matrix Dissipation
    IRS
  • NACA0012 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.85, \alpha~=~1\deg.
  • Steady transonic perfect gas flow.
  • Mesh:~ 257 \times 33 \times 2 .
  • Initial field : far-field state.
  • Jameson centered fluxes with artificial dissipation `dismat' : [~0.5~,~0.032~,~1~,~0.05~].
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 2500 iterations, CFL=15.
  • naca6/naca6_1.jpeg
    naca6/naca6_2.jpeg
    naca6/zresidu.jpeg

    naca64-Eul-Lin

    (Back to top of page)

    naca Euler shape optimization

    profil_roeva_optim_lin.py2D-Plane configuration
    Shape optimization linearized equation
    Euler
    Roe fluxes
    LU
  • NACA64A212 airfoil. M_{\inf}~=~0.71~,~\alpha~=~2.5~
  • Mesh: 257 \times 33.
  • Steady transonic inviscid flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=10.
  • Second order Roe Upwind flux.
  • Time integration: backward Euler.
  • Gradient computation: linearized method.
  • One shape parameter: linear combination of airfoils.
  • Calculation of CD_{w}, CD_{i}, CL and CD_{p} gradients.
  • naca64-Eul-Lin/drhoda1.jpeg
    naca64-Eul-Lin/zresidu1.jpeg

    naca64-Eul-Lur

    (Back to top of page)

    naca Euler Linearized - Aeroelasticity

    naca64_Eul_Lur.py2D-Plane configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • NACA64A010 - Aeroelastic simulation - Euler linearized
  • AGARD CT CASE NO. 6
  • Mach = 0.796 - Reynolds number= 1.3E07
  • Tangage Oscillating Profile
  • Frequency for forced motion = 34.4 Hz
  • Structural model: modal
  • Steady transonic perfect gas flow.
  • Implicit Residual Smoothing
  • Time integration:~Runge-Kutta 4
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.032~,~1~].
  • CFL = 4
  • 2000 iterations
  • naca64-Eul-Lur/cp.jpeg
    naca64-Eul-Lur/zresidu.jpeg

    naca64-KOcpld-Lin

    (Back to top of page)

    naca k-omega - coupled systems - shape optimization

    profilva_lin_cpld.py2D-Plane configuration
    Shape optimization linearized equation
    Navier-Stokes
    KO turbulence model
    Roe fluxes
    LU
  • NACA64A212 airfoil. M_{\inf}~=~0.71~,~\alpha~=~2.5~, ~Re_{\inf}~=~2~10^6~
  • Mesh: 257 \times 65.
  • Steady transonic turbulent flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=0.01
  • Turbulence model: 2 transport equations (k-\omega Wilcox).
  • Second order Roe Upwind flux.
  • Time integration: backward Euler.
  • Gradient computation: linearized method.
  • One shape parameter: linear combination of airfoils.
  • Calculation of CL, CD_{nf} and CD_{ff} gradients.
  • naca64-KOcpld-Lin/drhoda1.jpeg
    naca64-KOcpld-Lin/zresidu1.jpeg
    naca64-KOcpld-Lin/zresidu2.jpeg

    naca64-KOucpd-Adj

    (Back to top of page)

    naca k-omega shape optimization

    profilva_adj_nrg.py2D-Plane configuration
    Shape optimization adjoint equation
    Navier-Stokes
    KO turbulence model
    Roe fluxes
    LU
  • NACA64A212 airfoil. M_{\inf}~=~0.71~,~\alpha~=~2.5~, ~Re_{\inf}~=~2~10^6~
  • Mesh: 257~\times~65.
  • Steady transonic turbulent flow.
  • Initial conditions:~Issued from a first converged computation (convergence
  • obtained after 2000 iterations)
  • 10 iterations, CFL=5.
  • Turbulence model: 2 transport equations (k-\omega Wilcox).
  • Second order Roe Upwind flux.
  • Time integration: backward Euler.
  • Gradient computation: adjoint method.
  • Calculation of CL, CD_{nf} and CD_{ff} gradients.
  • One shape parameter: linear combination of airfoils.
  • naca64-KOucpd-Adj/adj1-rho.jpeg
    naca64-KOucpd-Adj/zresidu1.jpeg
    naca64-KOucpd-Adj/zresidu2.jpeg

    naca7-LS

    (Back to top of page)

    NACA0012: Preconditionning Low Speed Multigrid

    naca7_LS.py2D-Plane configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
    Multi-Grid
    Low speed preconditionning
  • NACA0012 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.01, \alpha~=~1\deg.
  • Steady transonic perfect gas flow.
  • Mesh:~ 257 \times 33 \times 2 .
  • Initial field : far-field state.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~0.5~,~0.032~,~1~].
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • Low speed preconditionning
  • 500 iterations, CFL=15.
  • naca7-LS/naca7-LS_1.jpeg
    naca7-LS/zresidu.jpeg

    naca7-MART

    (Back to top of page)

    NACA0012: Scalar Viscosity, Martinelli

    naca7_MART.py2D-Plane configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation with Martinelli correction
    IRS
  • NACA0012 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.85, \alpha~=~1\deg.
  • Steady transonic perfect gas flow.
  • Mesh:~ 257 \times 33 \times 2 .
  • Initial field : far-field state.
  • Jameson centered fluxes with artificial dissipation `dismrt' : [~0.5~,~0.032~,~1~,~0.5~]..
  • Martinelli correction (0.5).
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 2000 iterations, CFL=10.
  • naca7-MART/naca7-MART_1.jpeg
    naca7-MART/zresidu.jpeg

    naca8

    (Back to top of page)

    NACA0012: Scalar Viscosity

    naca8.py2D-Plane configuration
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • NACA0012 2D wing profile.
  • Steady transonic perfect gas flow.
  • Infinite flow : {M_\infty}~=~0.85, \alpha~=~1\deg.
  • Mesh:~257 \times 33 \times 2.
  • Initial field : far-field state.
  • Jameson centered fluxes with artificial dissipation `dissca' : [~1~,~0.064~,~1~]..
  • Multi-dimensional extrapolation slip boundary condition.
  • Time integration : Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 2000 iterations, CFL=15.
  • naca8/naca8_1.jpeg
    naca8/zresidu.jpeg

    naca9

    (Back to top of page)

    NACA0012: Coarse-Fine Matching

    naca2d.py2D-Plane configuration
    Multi-Domain
    Partially coincident match
    Euler
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • NACA0012 2D wing profile.
  • Steady transonic perfect gas flow.
  • Mesh:~ 257 \times 33 \times 2 cut into 2 blocks 65 \times 33 \times 2 and
  • 129 \times 33 \times 2 with fine-coarse matching.
  • Jameson centered fluxes with artificial dissipation `dissca', "av\_type" = 1.
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 2000 iterations, CFL=15.
  • naca9/naca9_1.jpeg
    naca9/zresidu.jpeg

    nacaUp2

    (Back to top of page)

    NACA0012: Roe fluxes

    nacaUp2.py2D-Plane configuration
    Euler
    Backward-Euler
    Roe fluxes
    LU
  • NACA0012 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.85, \alpha~=~1\deg.
  • Steady transonic perfect gas flow.
  • Mesh:~ 257 \times 33 \times 2 .
  • Initial field : far-field state.
  • Second order Roe upwind fluxes (van Leer limiter).
  • Time integration : backward Euler.
  • Implicit : matricial LU-Relax.
  • Local time step.
  • 3000 iterations, CFL=20.
  • nacaUp2/nacaUp2_1.jpeg
    nacaUp2/zresidu.jpeg

    nacaUp3

    (Back to top of page)

    NACA0012: Direct Coquel fluxes

    nacaUp3.py2D-Plane configuration
    Euler
    Backward-Euler
    Coquel fluxes
    LU
  • NACA0012 2D wing profile.
  • Infinite flow : {M_\infty}~=~0.85, \alpha~=~1\deg.
  • Steady transonic perfect gas flow.
  • Mesh:~ 257 \times 33 \times 2 .
  • Initial field : far-field state.
  • Direct Coquel upwind fluxes (van Leer limiter).
  • Time integration : backward Euler.
  • Implicit : matricial LU-Relax.
  • Local time step.
  • 4000 iterations, CFL=50.
  • nacaUp3/nacaUp3_1.jpeg
    nacaUp3/zresidu.jpeg

    turbine-Michel

    (Back to top of page)

    Turbine stator Turbulent Michel

    vega.py3D configuration
    Multi-Domain
    Partially coincident match
    Navier-Stokes
    Michel turbulence model
    Runge-Kutta
    Jameson fluxes
    Scalar Dissipation
    IRS
  • 3D annular turbine Stator.
  • Steady turbulent viscous flow.
  • Turbulence model:~algebraic Michel et al. model.
  • Value of vorticity ratio = 0.03
  • for boundary layer thickness evaluation in turbulence model.
  • Mesh: 2 blocks : 161 \times 21 \times 51 and 129 \times 25 \times 51.
  • Jameson centered fluxes with artificial dissipation `dissca'.
  • Initial conditions: Result of 30 preliminary iterations (CFL=1.)
  • done with elsA from a classical inviscid 1-D
  • (in each blade-to-blade mesh section) initialization
  • Time integration:~ Runge-Kutta 4 steps with freezing.
  • Implicit residual smoothing.
  • Local time step.
  • 2000 iterations, CFL=5.
  • turbine-Michel/vega_1.jpeg
    turbine-Michel/vega_2.jpeg
    turbine-Michel/vega_3.jpeg


    (updated $Date: 2016/04/28 13:06:54 $)Home Site map Contacts