Review of Thermofluid / MHD activities for DCLL

Sergey Smolentsev & US TBM Thermofluid/MHD Group

2006 US-Japan Workshop on FUSION HIGH POWER DENSITY COMPONENTS and SYSTEMS

Santa Fe, New Mexico, USANov. 15-17, 2006

Outline

• Introduction. MHD phenomena in DCLL blankets

• Scaling analysis for DCLL DEMO and ITER TBM

• Particular MHD phenomena• MHD software development: HIMAG • Experiment

DCLL is current US blanket choice for DEMO and testing in ITER

DCLL DEMO

B-field

ITER TBM

•Blanket performance is strongly affected by MHD phenomena

•Studying MHD in DCLL conditions is one of the most important goals

FCI

He

PbLi

SiC/SiC FCI is the keyelement of DCLL

Thermofluid / MHD activities cover two major areas: (I) Design, (II) R&D Thermofluid / MHD issues of the DCLL blanket:

•Effectiveness of FCI as electric/thermal insulator•MHD pressure drop•Flow distribution and balancing•Heat transfer

• physical/mathematical model development• code development• numerical simulations• experiments

These issues are being addressed via:

Heat Transfer in DCLL blankets is strongly affected by fluid flow phenomena, where MHD

plays a major roleA. Formation of high-

velocity near-wall jets

B. 2-D MHD turbulence in flows with M-type velocity profile

C. Reduction of turbulence via Joule dissipation

D. Natural/mixed convection

E. Strong effects of MHD flows and FCI properties on heat transfer

-0.15 -0.1 -0.05 0 0.05 0.1 0.15Radia l d istance, m

400

800

1200

1600

Tem

pera

ture

, C

lam inar flow m odeltu rbulen t flow m odel

DEMO

E

g

DB

=500

=100

=5

A C

Key DCLL parameters (outboard)

Parameter DEMO ITER H-H ITER D-TSurface heat flux, Mw/m2 0.55 0.3 0.3

Neutron wall load, Mw/m2 3.08 - 0.78

PbLi In/Out T, C 500/700 470/~450 360/470

2a x 2b x L, m 0.22x0.22x2 0.066x0.12x1.6 0.066x0.12x1.6

PbLi velocity, m/s 0.06 0.1 0.1

Magnetic field, T 4 4 4

MHD / Heat Transfer phenomena in ITER can bequantitatively/qualitatively different from those in DEMO

Engineering scaling (poloidal flow)

PARAMETER ITER D-T DEMORe 30,500 61,000

Ha 6350 11,640

Ha/Re 0.208 0.190

N 1320 2217

Gr 7.22x109 3.52x1012

r 11.1 70.3

Gr/Re 2.36x105 5.76x107

Ha/Gr 8.80x10-7 3.31x10-9

a/b 0.55 1.0

L/a 50 18

Major differences between ITER and DEMO are expected for buoyancy-driven flows, which are much more intensive in DEMO conditions

Formation of near-wall jets and MHD pressure drop reduction by FCI

a b

a b

No pressure equalization openings

With a pressure equalization slot

DCLL unit-cell with FCI

0.01 0.1 1 10 100 1000SiC /S iC E lectric C onductivity, S /m

0

200

400

600

800

Pre

ssur

e dr

op re

duct

ion

fact

or No pressure equaliza tionopen ingsS lo t in the H artm ann wa llS lo t in the paralle l w all

MHD pressure drop reduction by FCI

DEMO (old)B=4 THa=16,000

Study of MHD buoyancy-driven flowsA. Numerical simulation of unsteady buoyancy-driven flows

B. Analytical solution for steady mixed convection

(a)

(b)

B

Poloidal distance

2

Re

baHa

Grr

Present computationsare limited to Gr~107.The near goal is toachieve Gr~109-1012.

Modeling of 2-D MHD turbulence•Two eddy-viscosity models (zero- and one-equation) have been developed and tested against experimental data (MATUR)•2-D DNS was performed for flows with internal shear layers to address the effect of bulk eddies on the boundary layer•One-equation model was used in heat transfer calculations for DCLL

2-D DNS

Transitions in MHD flows in a gradient magnetic field

BC: Flow will be unstable if the Hartmann number built through the magnetic field gradient > ~ 5

A. Linear stability analysis

l0 x

0

y

xU(y) (y)

Sketch of the problem. Formation of the double row of staggered vortices from the internal shear layers.

B. Nonlinear analysis

Heat transfer for 3 DCLL scenarios:DEMO, ITER H-H, ITER D-T

FSG

AP

FCI

Pb-L

i

100 S/m

20 S/m

FCI = 5 S/m

Temperature Profile for Model DEMO Case

kFCI = 2 W/m-K

Parametric analysis at: 0.01<<500, 2<k<20

• Preliminary identification of required SiC FCI properties:

~100 S/m, k~2 W/m-K• The most critical requirement is

that on T across the FCI. Near-wall jet allows for lower T

• Reduction of the jet effect via instabilities, turbulence, buoyancy-driven flows ?

• Narrow design window• Further MHD analysis is

necessary

MHD software development: HIMAG• The HyPerComp Incompressible

MHD Solver for Arbitrary Geometry (HIMAG) has been developed over the past several years by a US software company HyPerComp with some support from UCLA.

• At the beginning of the code design, the emphasis was on the accurate capture of a free surface in low to moderate Hartmann number flows.

• At present, efforts are directed to the code modification and benchmarking for higher Hartmann number flows in typical closed channel configurations relevant to the DCLL blanket.

y / a

U / U0

Rectangular duct, Ha=10,000

Circular pipe, Ha=1000

MTOR Laboratory at UCLA

JUPITER 2 MHD Heat Transfer Exp. in UCLA FLIHY Electrolyte Loop

BOB magnet

QTOR magnet and LM flow

loop

The manifold experiment

• (Exp. A) Non-conducting test-article • (Exp. B) Conducting test-article• (Exp. C) Manifold optimization • Parameters: L=1 m, B~2 T• Measurements: Pressure, electric potential, flow rate, velocity• Status: Vacuum testing

Goal: Manifold design that provides uniform flow distribution and minimizes the MHD pressure drop

Modeling the manifold experiment

X

0

50

100

150

200

Y

-40-20

020

40

Z 01020

(Exp. A): Ha = 1000; Re = 1000; N = 1000

Modeling the manifold experiment

Y

-40

-20

0

20

40

Z

0

10

20

Flow imbalance:center channel = +11.8%side channels = -5.9%

Dependence on Ha, Reand geometry must be studied – Likely to be more imbalanced at higher Ha

CONCLUSIONS

• Basic MHD phenomena that affect blanket performance have been identified

• Preliminary MHD/Heat Transfer analysis have been performed for 3 blanket scenarios using reduced 2-D/3-D models

• More analysis is required to address 3-D issues based on full models and via experiments

• HIMAG is potentially a very effective numerical tool for LM blanket applications