Difference between revisions of "AC 610 Best Practice Advice"
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Latest revision as of 18:43, 11 February 2017
Contents
 1 Axial compressor cascade
 2 Best Practice Advice
Axial compressor cascade
Application Challenge 610 © copyright ERCOFTAC 2004
Best Practice Advice
Best Practice Advice for the AC
Key Fluid Physics
Description of Application Challenge
 ECAV2V2 high subsonic compressor cascade
 Wind tunnel measurements at DFVLR Braunschweig
 AGARD WG18 test case
 Inlet Mach numbers 0.30.9
 Flow turning 50^{o}
 High incidence/stall – choke
 Variation of streamtube
DOAPs
 Exit Mach number, M_{2}
 Exit flow angle, α_{2}
 Pressure Loss, ζ
 Blade surface pressure distributions, Cp
 Pressure loss across wake, ω
Boundary layer velocity profiles on suction surface
Flow Physics
 Stagnation point at leading edge
 Initial laminar region is followed by transition
 Turbulent boundary layer thickens and eventually separates
 High turning produces strong adverse pressure gradient
 Local supersonic regions near blade surface
Underlying Flow Regimes
 Stagnation point flow (312)
 Laminarturbulent boundary layer transition (304)
 Bypass transition on a flat plate (319)
 2D boundary layers in adverse pressure gradients (303)
 The main focus of the UFR Best Practice Advice is on turbulence modeling. Therefore the majority of the discussion regarding the best practice advice and its consistency with the UFRs is contained in the section on physical modeling.
2. Application Uncertainities
Turbulent length scale at inlet
 Turbulent length scale at inlet is unknown so comparison of varying turbulent length scale at inlet was carried out (coarse mesh, ke RNG)
 As length scale is increased:
– Higher loss and thicker wake
– Fuller velocity profiles
 Effect of length scale quantified. 5% of pitch chosen for all simulations
 UFR 319 indicates the importance of initial and freestream conditions for turbulent dissipation for prediction of bypass transition.
















Axial variation of streamtube thickness
 Data only provides an overall value of streamtube contraction
 Two possible axial variations of streamtube were investigated:
– a) Linear variation between the inlet and exit measuring planes
– b) Constant values upstream and downstream and a linear variation between leading and trailing edges
 Option a) is more accurate and was used for all simulations
Computational Domain and Boundary Conditions
Computational domain
 One blade pitch with blade located centrally
 Axial extent 0.8 to 1.8 axial chords from leading edge
 Pseudo2D with prescribed variation of streamtube
 Sensitivity of results to streamtube variation has been investigated
Boundary Conditions
 Inflow boundary
– fixed stagnation pressure
– Specified flow angle, total temperature
– Turbulence intensity: 5%, length scale: 5% pitch
 Outflow boundary
– Fixed static pressure adjusted to give correct inlet Mach number
 Noslip wall boundaries on blade surface
 Cyclic (periodic) boundaries pitchwise
 Symmetry planes on endwalls
Discretisation and Grid Resolution
 2^{nd} order discretisation (MARS) on momentum, enthalpy and turbulence
 Full central differencing used for density interpolation to cell faces
 Grid independence investigations:
– O grid around blade, H grid upstream and downstream
– 3 levels of general refinement
– Hybrid wall functions
– Additional refinement next to blade surface (Low Re, y^{+} ~ 1)
 Final low – Re mesh of 326 by 80 cells, with approx 25 cells in boundary layer (mesh 2).
 Near wall y^{+} consistent with advice given in UFR 303 and 304. Use of hybrid wall functions allows mesh refinement studies to cover entire domain, this is also recommended in UFR 303.








































Physical Modelling
 Low Re number implementations recommended. Although hybrid wall functions were employed, improved prediction of near wall gradients can be achieved with a true lowRe mesh (y^{+} =1)
 Ke, Cubic ke, SpalartAllmaras, v2f used
 Reasonable prediction of DOAPs can be achieved with ke, but improved loss prediction and capture of detailed flow features with more advanced models.
 UFRs 319 and 304 show that for 2eq models, a lowReynolds number implementation is required to have any chance of predicting transition (although their success may be coincidental). No specific transition models were incorporated in this study. UFR 304 states that linear eddy viscosity models usually need highly empirical transition correlations to be accurate.
 Most accurate boundary layer profiles obtained with cubic ke. UFR 312 shows that v2f has been shown to give comparable results to KatoLaunder formulation and time scale bounded model for stagnation point flows. As boundary layer growth starts at the stagnation point (leading edge) v2f is more likely to accurately predict boundary layer development.
 General high overall loss despite underprediction of exit flow angle is thought to be due to excessive turbulence in the freestream. This is strongly affected by inlet turbulent length scale. v2f gives lowest overall loss and most accurate loss levels from the suction surface towards the midblade passage.
























Recommendations for Future Work
 Modelling of the complete range of operating points available in the test data with this range of turbulence models.
 Comparison of KatoLaunder and time scale bounded models with v2f and cubic kε for boundary layer development
 Running a wider range of turbulence models with different turbulent length scales at inlet.
© copyright ERCOFTAC 2004
Contributors: Michael Dickens; Alex Read  Computational Dynamics Ltd