Review of Thermofluid / MHD activities for DCLL Sergey Smolentsev & US TBM Thermofluid/MHD Group 2006 US-Japan Workshop on FUSION HIGH POWER DENSITY COMPONENTS.

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Presentation transcript:

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, USA Nov , 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 key element 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 role A.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 DEMO E g DB  =500  =100  =5 AC

Key DCLL parameters (outboard) ParameterDEMOITER H-HITER D-T Surface heat flux, Mw/m Neutron wall load, Mw/m PbLi In/Out T,  C 500/700470/~450360/470 2a x 2b x L, m 0.22x0.22x20.066x0.12x1.6 PbLi velocity, m/s Magnetic field, T 444 MHD / Heat Transfer phenomena in ITER can be quantitatively/qualitatively different from those in DEMO

Engineering scaling (poloidal flow) PARAMETERITER D-TDEMO Re30,50061,000 Ha635011,640 Ha/Re N Gr7.22x x10 12 r Gr/Re2.36x x10 7 Ha/Gr8.80x x10 -9 a/b L/a5018 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 ab ab No pressure equalization openings With a pressure equalization slot DCLL unit-cell with FCI MHD pressure drop reduction by FCI DEMO (old) B=4 T Ha=16,000

Study of MHD buoyancy-driven flows A. Numerical simulation of unsteady buoyancy-driven flows B. Analytical solution for steady mixed convection (a) (b) B Poloidal distance Present computations are limited to Gr~10 7. The near goal is to achieve Gr~

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 x U(y)U(y) (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 FS GAP FCI Pb-Li 100 S/m 20 S/m  FCI = 5 S/m Temperature Profile for Model DEMO Case k FCI = 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 / U 0 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 (Exp. A): Ha = 1000; Re = 1000; N = 1000

Modeling the manifold experiment Flow imbalance: center channel = +11.8% side channels = -5.9% Dependence on Ha, Re and 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