1 / 18

Review of Thermofluid / MHD activities for DCLL

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. 15-17, 2006. Outline. Introduction. MHD phenomena in DCLL blankets

deanne
Download Presentation

Review of Thermofluid / MHD activities for DCLL

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. 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. 15-17, 2006

  2. Outline • Introduction. MHD phenomena in DCLL blankets • Scaling analysis for DCLL DEMO and ITER TBM • Particular MHD phenomena • MHD software development: HIMAG • Experiment

  3. B-field He FCI PbLi DCLL is current US blanket choice for DEMO and testing in ITER DCLL DEMO ITER TBM SiC/SiC FCI is the key element of DCLL • Blanket performance is strongly affected by MHD phenomena • Studying MHD in DCLL conditions is one of the most important goals

  4. physical/mathematical model development • code development • numerical simulations • experiments 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 These issues are being addressed via:

  5. E D B A C g DEMO Heat Transfer in DCLL blankets is strongly affected by fluid flow phenomena, where MHD plays a major role • 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 =5 =100 =500

  6. Key DCLL parameters (outboard) MHD / Heat Transfer phenomena in ITER can be quantitatively/qualitatively different from those in DEMO

  7. Engineering scaling (poloidal flow) Major differences between ITER and DEMO are expected for buoyancy- driven flows, which are much more intensive in DEMO conditions

  8. a b a b Formation of near-wall jets and MHD pressure drop reduction by FCI No pressure equalization openings DCLL unit-cell with FCI With a pressure equalization slot MHD pressure drop reduction by FCI DEMO (old) B=4 T Ha=16,000

  9. (b) Poloidal distance (a) B Study of MHD buoyancy-driven flows A. Numerical simulation of unsteady buoyancy-driven flows Present computations are limited to Gr~107. The near goal is to achieve Gr~109-1012. B. Analytical solution for steady mixed convection

  10. 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

  11. y U(y) (y) 0 x x 0 l Transitions in MHD flows in a gradient magnetic field A. Linear stability analysis B. Nonlinear analysis BC: Flow will be unstable if the Hartmann number built through the magnetic field gradient > ~ 5 Sketch of the problem. Formation of the double row of staggered vortices from the internal shear layers.

  12. Temperature Profile for Model DEMO Case kFCI = 2 W/m-K FCI Pb-Li FS GAP sFCI = 5 S/m 20 S/m 100 S/m Heat transfer for 3 DCLL scenarios:DEMO, ITER H-H, ITER D-T 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

  13. U / U0 y / a MHD software development: HIMAG Rectangular duct, Ha=10,000 • 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. Circular pipe, Ha=1000

  14. QTOR magnet and LM flow loop BOB magnet JUPITER 2 MHD Heat Transfer Exp. in UCLA FLIHY Electrolyte Loop MTOR Laboratory at UCLA

  15. 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

  16. Modeling the manifold experiment (Exp. A): Ha = 1000; Re = 1000; N = 1000

  17. Modeling the manifold experiment 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

  18. 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

More Related