materials performance centre seminars, 12/09/2006

1

EDFElectricitéde France

Materials Performance Centre Seminars, 12/09/2006

Application of Large Eddy Simulation

to thermal-hydraulics

in the Nuclear Power Generation Industry.

[email protected] of Mech, Aero & Civil Eng.

Fluids AIG / CFD group

[email protected] R&D Chatou

Contributions: Y. Addad, I. Afgan, S. Benhamadouche, S. Berrouk, N Jarrin C. Moulinec, T. Pasutto,

The

Uni

vers

ity

of M

anch

este

r

2


Osborne Reynolds 1868, became a professor of engineering at Owens College (now University of Manchester)

Reynolds tank, G. Begg building

Low speed jet

Higher speed jet

Turbulence, Reynold Number Re = UD/visc.

3


Kolmogorov Energy Cascade

2 212

12

Assume : ( ) sin( ) 2 /

. sin( )cos( ) sin(2 )

thus energy transfer from 2 / to 2 2 /( )

i i i i

i i i i i i i

i i i i

u x u k x k L

duu u k k x k x u k k xdx

k L k L

Андре́5й Никола́5е́вич Колмого5ров

Moscow State Uni. 1939

4


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)

Sergio Hoyas and Javier Jimenez, (2006) "Scaling of velocity fluctuations in turbulent channels up to Re_tau = 2000", Phys. of Fluids, vol 18,

Direct Numerical Simulation (DNS)

Nx=6144, Ny=633, Nz=4608 points = 17,921,212,416 cells

6 Million processor hours on 2048 processors,

Barcelona Supercomputing Center

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 !)

6


Large Eddy Simulation = Filtering

1( , ) ( , ') '

2

t T

t Tu x t u x t t dt

T

drrxGtrutxuV

)(),(),(

CFD codes naturally induce filter = 2 dx

Space Filter

Time Filter

7


DHIT: Decay of Hom. Iso. Turb.

MANDATORY test case for first time LES !

Reveals numerical dissipation, stability,

G rid

S ta tio n4 2

S ta tio n9 8

U = 1 0 m s0

-1

8


• 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

3 Levels of CFD approaches to turbulent flow

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

10


LES at EDF: Thermal stresses in T junction

Configuration studied : Thot = 168°C , Tcold = 41°CFlow rate = 1000 m3/h, ratio 20%

- Experimental mock-up (both thermalhydraulics and thermal fatigue mechanical aspects)

- models and numerical tools to gain a better understanding.

Length of the numerical simulation : 11 seconds

QhotQcold

11

EDFElectricitéde FranceFluid results

Instantaneous fluid temperature field (Code_Saturne)

(Peniguel et al. ASME-PVP Cleveland 2003)Shortcut to aaPVP_anim.mpg.lnk

12


Solid and fluid meshes

Solid mesh : 958 975 nodeswidth of the first solid element : 100 microns

Fluid mesh: 401 472 cells

13

EDFElectricitéde FranceSolid temperature fluctuations

Instantaneous fluid temperature Instantaneous solid temperature

Time (s)

Instantaneous solid temperature field (Syrthes)(location C12)

C12

14

EDFElectricitéde FranceTemperature spectrum

Location CEX1

- On site meas

-L.E.S.

- Mock-up

CEX1

Frequency (Hz)

15


T Junction, stratified case

Fluid temperature and flow structure

Recirculation zone

C12

Temperature In the symmetry plane (case 1)

Temperature near the wall (case 1)

VH = 3,37 m/s

TH = 204°C

VC = 0,77 m/s

TC = 41°C

17


Analysis of the results

Attenuation of the fluctuations by the wall thermal inertia

( Ring C12 – 50 °)

18


Mesh too coarse for Re=1 Milliontemperatures (ring C12) fluid: probe located at 10° probe located at 50°

Solid:

underestimation of the fluctations (especially at 10°) limitation of the wall function approach ?

LES

Exp

19


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)

FAATER exp. : Meshes

20


Outflow region

Jet

x

y

Cold upflow

Trust & Quality-CFD project: hot wall jet (Magnox case)

Buoyancy: none medium highVelocity: high medium low

3-D view (STCL2). A: t1 = 2114 D j /V bjÝsÞ, B: t t2 = t1 + 18. 5D j /V bjÝsÞ.

Addad Y. , D. Laurence and S. Benhamadouche. The Negative Buoyant Wall Jet: LES Results, I.J. Heat and Fluid Flow, 25, 795-808, 2004

22


Grid generation (buoyant case)

● 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

IntegralLength scalefrom k-epsilon

23


Horizontal Velocity Comparison

24


LES DB => Analytic Wall Function development

(from A. Gerasimov)

25


Thermal hydraulics of reactors

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.

Mixed convection in co-axial pipes(Y. Addad PhD, M. Rabitt British Energy)

26


K-eps pre-study

Streamlines coloured by temperature

Cold Inlet Pipe in vessel => stratification trap

27


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=1.8109) Case3- annular cavity single coaxial cylinder (Ra=2.381010) Case4- annular cavity with 3 coaxial cylinders (Ra=2.381010) Case5- Flow in actual penetration cavity (bulk Re=620,000).

Bishop 88, McLeod 89

28


CASE-4: Ra=2.3810E+10

CASE-3: Ra=2.3810E+10

Natural Convection in coaxial cylinders

Case 2: Ra=1.810E+9SGS visc/Molecular visc.<1

30


3 Cylinders

31


Flow through in-line tube bundles

STAR CCM grid

Mean pressure

gradient

Direction is in-lin

e

Large heat exchanger=> Homogeneous conditions

=> Periodic subset considered

Re=45 000, P/D= 1.5

Objectives: Flow induced vibrations in heat exchangers (Lift & Drag coef.)

Staggered: studied 10 years agoCurrent: in line

32


In-line tube bundle

[email protected], with STAR-CCM

- 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 =>

33


In-line tube bundle P/D=1.5

-1.00

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

1.00

0 45 90 135 180 225 270 315 360

Azimuthal Angle

No

rma

lize

d P

res

su

re

SATURNE

STAR CCM

STAR CCMMean velocity

(Afgan)

EDF Code-SaturneMean velocity

(Benhamadouche)

mean pressure

34


-Vortex Method for Inlet

-Polyhedral Cells (670,000)

-Re=57,400

-Y+=2 (Prisms)

-L1=3D; L2=5D

- Smagorinsky Model, Van Driest Damping

LES in a 180° U-Bend Pipe

36


U-Bend Pipe Cross Sections: Mean flow

45 degrees

177 degrees

135 degrees

90 degrees

37


Research: Reconstructing fluctuations

Real Eddies in Channel flowCost = 5 days computing

Synthetic Eddies in Channel flowCost = 5 seconds computing

Matches all rms values andgiven spectrum

3-D view (STCL2). A: t1 = 2114 D j /V bjÝsÞ, B: t t2 = t1 + 18. 5D j /V bjÝsÞ.

KNOO project:Develop similar technique to

reconstruct temperature fluctuations at solid wall

Link with materials ageing research

38


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 ?

39


DNS at Re* N Cells

395 10 Million

640 28 Million

720 84 Million

2000 17,921 Million

RANS LES

Under-resolved LESRANS – LES coupling

U

Wall distance

J. Uribe, Manchester

Research: RANS – LES coupling

LES: ~ 0.1 Million cells

40


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 …

materials performance centre seminars, 12/09/2006

Documents

large scales matter

numerical methods

small scales

costly fluid dyn

conventional fluid dyn

colourful fluid dyn

turbulent flowindustrial

reactor thermal hydraulicsles