1 / 40

Materials Performance Centre Seminars, 12/09/2006

Materials Performance Centre Seminars, 12/09/2006. Application of Large Eddy Simulation to thermal-hydraulics in the Nuclear Power Generation Industry. Dominique.Laurence@manchester.ac.uk School of Mech, Aero & Civil Eng. Fluids AIG / CFD group Dominique.Laurence@edf.fr EDF R&D Chatou.

alvis
Download Presentation

Materials Performance Centre Seminars, 12/09/2006

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Materials Performance Centre Seminars,12/09/2006 • Application of Large Eddy Simulation • to thermal-hydraulics • in the Nuclear Power Generation Industry. • Dominique.Laurence@manchester.ac.uk • School of Mech, Aero & Civil Eng. • Fluids AIG / CFD group • Dominique.Laurence@edf.fr • EDF R&D Chatou The University of Manchester Contributions: Y. Addad, I. Afgan, S. Benhamadouche, S. Berrouk, N Jarrin C. Moulinec, T. Pasutto, 1

  2. Turbulence, Reynold Number Re = UD/visc. Low speed jet Osborne Reynolds 1868, became a professor of engineering at Owens College (now University of Manchester) Higher speed jet Reynolds tank, G. Begg building 2

  3. Kolmogorov Energy Cascade Андре́й Никола́евич Колмого́ров Moscow State Uni. 1939 3

  4. Direct Numerical Simulation (DNS) • Solve the standard (Navier Stokes) flow equation on a very fine mesh • All scales are resolved on that mesh (down to Kolmogorov scale) • No model needed • Results considered as valid as experimental data • Enormous computer resources, for even modest speed-domain size (Reynolds number) Nx=6144, Ny=633, Nz=4608 points = 17,921,212,416 cells 6 Million processor hours on 2048 processors, Barcelona Supercomputing Center Sergio Hoyas and Javier Jimenez, (2006) "Scaling of velocity fluctuations in turbulent channels up to Re_tau = 2000", Phys. of Fluids, vol 18, 4

  5. Luckily, only Large Scales matter(most of the time) • Large Scales & Human activity • Drag, mixing, heat transfer, • Large Scales dictate flow physics • Generated by/scale with obstacle • Impose dissipation rate • Exceptions: noise, combustion, Weather forecast (we are the small scales !) 5

  6. Large Eddy Simulation = Filtering Time Filter Space Filter CFD codes naturally induce filter D = 2 dx 6

  7. DHIT: Decay of Hom. Iso. Turb. • MANDATORY test case for first time LES ! • Reveals numerical dissipation, stability, 7

  8. 3 Levels of CFD approaches to turbulent flow • Direct Numerical Simulation (DNS) databases <=> Experiments • = “Costly”Fluid Dyn., exceptional, limited to zoom effect, • - 100% accurate, back to 1st principles, NO modelling hypothesis • Large Eddy Simulation (LES) • = “Colourful”Fluid Dyn., much detail, fluctuations, spectra, • - Applicable Eng. problems, at some cost • - Almost as reliable as DNS, but know-how required, not well established • Reynolds Averaged (RANS) • = “Conventional”Fluid Dyn., used daily in Eng., only mean values (B&W) • - Economical, full reactor or sub-component design (parametric) possible • - Problem: wide range of models to choose from, • - needs improvement & validation for new range of applications • (high temperature, buoyancy, conjugate heat transfer, ) • Future : Coupling of RANS and LES, using DNS for insight & validation 8

  9. Industrial LES applications to reactor thermal hydraulics • LES is mostly about numerical methods • Grid able to capture most turbulent scales • Easier in Power Industry (confined, non-streamlined geometry) • Local/embedded grid refinement, polyhedral scales • Boundary conditions • Walls => quasi DNS (wall functions not ideal) • Some real periodic geometry. pb. in Power Gen (tube bundles) • Synthetic inlet turbulence • Target values • Order of Mag. (within 10%), not 0.01 on Cd • Thermal mixing & loading, spectra, vibrations…. • Need Fast Unstructured FV Solver • EDF code Saturne & Star-CD very similar • High Accuracy Numerical Scheme • No numerical dissipation ( Central differencing, Second order in time) • Avoid any mesh distortion 9

  10. LES at EDF: Thermal stresses in T junction - Experimental mock-up (both thermalhydraulics and thermal fatigue mechanical aspects) - models and numerical tools to gain a better understanding. Qhot Qcold Configuration studied : Thot = 168°C , Tcold = 41°C Flow rate = 1000 m3/h, ratio 20% Length of the numerical simulation : 11 seconds 10

  11. Fluid results Instantaneous fluid temperature field (Code_Saturne) (Peniguel et al. ASME-PVP Cleveland 2003) Shortcut to aaPVP_anim.mpg.lnk 11

  12. Solid and fluid meshes Solid mesh : 958 975 nodeswidth of the first solid element : 100 microns Fluid mesh: 401 472 cells 12

  13. Solid temperature fluctuations Instantaneous solid temperature field (Syrthes) (location C12) C12 Instantaneous fluid temperature Instantaneous solid temperature Time (s) 13

  14. Temperature spectrum • - On site meas • L.E.S. • Mock-up CEX1 Frequency (Hz) Location CEX1 14

  15. T Junction, stratified case • Fluid temperature and flow structure VH = 3,37 m/s TH = 204°C VC = 0,77 m/s TC = 41°C Temperature In the symmetry plane (case 1) C12 15 Temperature near the wall (case 1) Recirculation zone

  16. Analysis of the results • Attenuation of the fluctuations by • the wall thermal inertia ( Ring C12 – 50 °) 17

  17. Mesh too coarse for Re=1 Million • temperatures (ring C12) • fluid:probe located at 10° probe located at 50° • Solid: Exp LES 18 underestimation of the fluctations (especially at 10°)  limitation of the wall function approach ?

  18. FAATER exp. : Meshes • Fluid meshes • 1st mesh : ~ 500 000 hexaedric cells y+~ 300 • 2nd mesh : ~ 1 000 000 hexaedric cells y+~ 170 (first node at 0,38 mm from the wall) (1 000 000 cell mesh) 19

  19. Trust & Quality-CFD project: hot wall jet (Magnox case) Buoyancy: none medium high Velocity: high medium low Addad Y. , D. Laurence and S. Benhamadouche. The Negative Buoyant Wall Jet: LES Results, I.J. Heat and Fluid Flow, 25, 795-808, 2004 20

  20. Grid generation (buoyant case) IntegralLength scale from k-epsilon • Pre- k-eps simulation • cell Volume near jet inlet (V)1/3=0.002 • y+=1 • In mixing region (V)1/3=0.007 • NCELLS=770 000 • StarCD code 22

  21. Horizontal Velocity Comparison 23

  22. LES DB => Analytic Wall Function development 24 (from A. Gerasimov)

  23. Thermal hydraulics of reactors Mixed convection in co-axial pipes (Y. Addad PhD, M. Rabitt British Energy) Study the physics of the flow in the decay heat inlet pen Examine the LES solution of the code Star-CD for the natural/mixed convection cases. Validate further the analytical wall functions developed at UMIST by Gerasimov et al. 25

  24. Cold Inlet Pipe in vessel => stratification trap Streamlines coloured by temperature K-eps pre-study 26

  25. Coaxial heated cylinder study • LES validation and parametric test cases: • Case1-Natural convection in square cavity (Ra=1.58  109) • Case2-Natural convection in annular cavity (Ra=1.8109) • Case3- annular cavity single coaxial cylinder (Ra=2.381010) • Case4- annular cavity with 3 coaxial cylinders (Ra=2.381010) • Case5- Flow in actual penetration cavity (bulk Re=620,000). Bishop 88, McLeod 89 27

  26. Natural Convection in coaxial cylinders CASE-3: Ra=2.3810E+10 Case 2: Ra=1.810E+9 SGS visc/Molecular visc.<1 CASE-4: Ra=2.3810E+10 28

  27. 3 Cylinders 30

  28. Flow through in-line tube bundles Objectives: Flow induced vibrations in heat exchangers (Lift & Drag coef.) Staggered: studied 10 years ago Current: in line Large heat exchanger => Homogeneous conditions => Periodic subset considered Mean pressure gradient Direction is in-line Re=45 000, P/D= 1.5 STAR CCM grid 31

  29. In-line tube bundle • - Fully symmetric conditions, • but non-symmetric solutions • - Coanda effect ? • Star-CCM LES launched • to confirm EDF finding • (Benhamadouche et al. NURETH 11, Avignon 2005) Time averaged velocity field => 32 I.Afgan@postgrad.manchester.ac.uk, with STAR-CCM

  30. In-line tube bundle P/D=1.5 mean pressure STAR CCM Mean velocity (Afgan) EDF Code-Saturne Mean velocity (Benhamadouche) 33

  31. LES in a 180° U-Bend Pipe -Vortex Method for Inlet -Polyhedral Cells (670,000) -Re=57,400 -Y+=2 (Prisms) -L1=3D; L2=5D - Smagorinsky Model, Van Driest Damping 34

  32. U-Bend Pipe Cross Sections: Mean flow • 45 degrees 135 degrees 177 degrees 90 degrees 36

  33. Research: Reconstructing fluctuations Real Eddies in Channel flow Cost = 5 days computing Synthetic Eddies in Channel flow Cost = 5 seconds computing Matches all rms values and given spectrum KNOO project: Develop similar technique to reconstruct temperature fluctuations at solid wall Link with materials ageing research 37

  34. Research: Mesh strategy for LES a) Possible FV near-wall refinements: a) dichotomy, b) non-conforming, c) & d) polyhedral & zoom. • Non dissipative Finite Volume Methods • Optimal meshing strategy for LES • Quality criteria for LES • General but essential issue. Collaboration with: • - CD – Adapaco (STAR-CD code) • - EDF R&D (Saturne code) • - Health & Safety Labs, CFD for Nuclear Reactor licensing ? 38

  35. Research: RANS – LES coupling U Under-resolved LES RANS – LES coupling Wall distance LES RANS LES: ~ 0.1 Million cells J. Uribe, Manchester 39

  36. Conclusions – Industrial LES • LES of Industrial flow • Much more information:Thermal stresses, fatigue, Acoustics, FIV (vibrations) • Cost-wise accessible when limited to subdomain • (synthetic turbulence for inlet) • Complex geometry possibly easier than smooth channel flow (academic overkill ?) • Flexible flexibility with professional/commercial software: • Opens new range of applications for LES • Medium Re number : DNS near wall resolution possible • Greater breakthrough than elaborate SGS models? • Further developments: • More meshing control (total cell size control from pre-simulation) • High Re : RANS –LES coupling, embedded LES • Cross-discipline research: Fluids / Structure-Mech/ Materials ? • Cracks, Thermal stripping, ageing, corrosion … 40

More Related