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Nuclear optimization of the HCCB TBM With Varying Li-6 Enrichment and plan for 3-D analysis

Nuclear optimization of the HCCB TBM With Varying Li-6 Enrichment and plan for 3-D analysis. Presented by M. Youssef UCLA. Contributors: Wei Zhang, M. Z. Youssef, A. Ying. US-ITER TBM Meeting , February 14-15, 2007 Rice Room, Boelter Hall 6764, UCLA. The US HCCB TBM location and dimensions

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Nuclear optimization of the HCCB TBM With Varying Li-6 Enrichment and plan for 3-D analysis

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  1. Nuclear optimization of the HCCB TBM With Varying Li-6 Enrichment and plan for 3-D analysis Presented by M. Youssef UCLA Contributors: Wei Zhang, M. Z. Youssef, A. Ying US-ITER TBM Meeting, February 14-15, 2007 Rice Room, Boelter Hall 6764, UCLA

  2. The US HCCB TBM location and dimensions (the NT-submodule is selected for this study) TBM Dimension: 71 cm Height 38.9 cm width 60 cm depth Frontal area: ~0.28 cm2 (~35% of DCLL) Li2TiO3 pebbles: are 94% theoretical Density 62% packing factor. Be pebbles: 62% Packing Factor 2

  3. Objectives: (1) • Achieve adequate breeding ratio, TBR, with the minimum amount of Beryllium, • Explore optimized nuclear heating profile by varying enrichment of Li-6 in toroidal, poloidal, and radial directions in addition to satisfy the operation requirements, • It is desirable to maximize TBR while tailoring nuclear heating rates distributions throughout the module to ensure breeder is operated within its temperature window with adequate design margins.

  4. Varying Li-6 Enrichment in Breeder Zones to improve heat removal 1 C 30 30 30 90 30 20 90 C 20 H M M M M H Li-6 Enrichment (%) C H M M M M H C 2 70 40 50 50 50 40 70 50 60 50 3 50 60 60 60 60 60 C: Cold Zone H: HOT Zone M: Medium 30 30 4 70 70 70 70 70 70 1st Coolant Circuit 2nd Coolant Circuit MZ youssef-8-11-06 Objectives: (2) • The routes for the helium cooling are envisioned to be implemented through two paths entering through the back manifold in opposite direction (right to left and left to right). When entering the TBM, helium coolant is cold and is hot where it exits the TBM. The Li-6 enrichment is varied such that TPR are maximized in regions where the coolant temperature is low and minimized where the coolant temperature is high. This maximizes the heat extracted from the TBM while ensuring adequate TPR to satisfy tritium self sufficiency criterion.

  5. Fig. 1 Isometric and plain view of HCCB NT sub-module • To study first variation of Li-6 enrichment in the radial direction, toroidal 1-D cylindrical model geometry is considered based on geometry of CAD design • Details of ITER I/B is included in the 1-D model. • The breeder is divided into 4 sub-zones with different Li-6 enrichment and different Be/Breeder volume fraction.

  6. Radial Build and Composition of each zone

  7. Two opposite Li6 enrichment schemes in the 4 sub-zone of CB

  8. Varying Li-6 Enrichment in Breeder Zones to improve heat removal 1 C 30 30 30 90 30 20 90 C 20 H M M M M H Li-6 Enrichment (%) C H M M M M H C 2 70 40 50 50 50 40 70 50 60 50 3 50 60 60 60 60 60 C: Cold Zone H: HOT Zone M: Medium 30 30 4 70 70 70 70 70 70 1st Coolant Circuit 2nd Coolant Circuit MZ youssef-8-11-06 Follow-up • Effort to perform Variation of enrichment in poloidal and toroidal directions is planned to be performed with 3-D codes.ATTILA is a potential tool and is undergoing QA proceduresthrough benchmarking with results obtained from CAD-based MCNP model for ITER

  9. Favorable feature of ATTILA • It has the ability to input geometry from CAD. It is a discrete ordinate FEM 3-D code with arbitrary isotropic scattering. Tetrahedral meshes (cells) are generated everywhere. Same meshing topology can in principle be exported to other codes, e.g. CFD codes, using for example nuclear heating in each mesh as a source for further analysis. Same can be done for stress analysis. • It has the provision of a solution throughout the whole problem geometry, and advanced visualisation of the model and the solution.Hot spots can be easily identified and design changes can be made in an iterative process. • To be approved for ITER analysis, it was agreed to compare ATTILA’s results for Four responses with those obtained from CAD-based MCNP calculations • This benchmarking is currently in progress in a cooperative effort between UCLA and PPPL (Russ Feder and Dave Johnson from The diagnostics group.

  10. ITER Benchmark • Comparing 4 results • Neutron wall loading • Divertor fluxes and heating • Magnet heating • Midplane port shielding/streaming • Participants CAD-based MCNP: • UW, FZK, ASIPP, JAEA + CAD-based-ATTILA: - PPPL, UCLA

  11. SolidWorks Benchmark CAD Modeling 2-D ITER Drawings 40° ITER Solid Model Plasma “Void” Part VV, Cryostat Bio-Shield OH/TF/PF BSM Diverter

  12. Creating the Benchmark Analysis Mesh CAD Modeling Strategies Strongly Effect Mesh and Analysis Results CAD MODEL LAYERING Solid Model in ATTILA Tetrahedral Mesh (496k Cells)

  13. Creating the Benchmark Analysis Mesh CAD Modeling Strategies Strongly Effect Mesh and Analysis Results CAD MODEL LAYERING CAD Model at Equatorial Port Mesh at Equatorial Port

  14. Z R MCNP Plasma Source Definition 1. 40x40 Probability Matrix  Each Cell Assigned a DT-neutron born probability 2. 400 MW neutron power  40° Normalization factor ~ 1.972E+19 3. MCNP Matrix Mapped on to ATILLA Mesh With Specially Written Python Script MCNP Source Distribution 40x40 Grid

  15. ATTILA Analysis Parameters Careful Choice of Parameters Effect: Solution Accuracy, Solution Convergence, Processing Speed, Memory and Disc Space PPPL Dedicated Neutronics Server “ITERPPN”: LINUX Opteron Server w/ 4 Processors 16 GB RAM  May Upgrade to 32 GB ATTILA is developing a distributed memory version that will enable “massively parallel” processing • Discrete Ordinates Parameters • Quadrature or Sn Order • Scattering or Pn Order • Mathematical Treatments for Sn and Pn • Solver Parameters • Converegence Criteria • Choice of Boundary Conditions • CPU Utilization Parameters • Memory Useage Strategy • Sweep Data Strategy • Cross Section Parameters • Energy Groups • Number of Materials and Isotopes • Number of Particles in Solution • CAD Model and Mesh Parameters • CAD model layering and simplification • Total Mesh Cells Current Benchmarking Study Parameters: Sn Order: 4  Increase to Sn=16 for Final Run Pn Order: 2 Mesh Cells: 496,000  May Need Refinement Energy “Few” Groups: 95  Possibly Increase to All Memory Usage Strategy: Low Memory Materials: 17 Isotopes: 83 Particles: 2 (neutron and gamma) 2 Weeks

  16. ATTILA Post-Processing The Benchmarking Run is still Running till this moment- Total expected time 2.5 weeks Log10 Scalar Flux Contours If ATTILA passes successfully this benchmarking tests, it will be used for further TBM design analyses. Equatorial Port Midplane Slice

  17. SolidWorks Benchmark CAD Modeling “Void” Part Diverter Model BSM Model

  18. Benchmark Material Properties and Mixing Equatorial Port Materials BSM First Wall Layer (M11): %44 316LN-IG %16.3 Water %14.3 Be %25.4 CuCrZr-IG V.V. Shell (M5): %100 316LN-IG Void (All Dark Blue) V.V. Shielding (M6): %55 304B7 %45 Water BSM Inner Layers (M12): %70 316LN-IG %30 Water

  19. ATTILA Post-Processing Major Advantage of ATTILA A Well Defined CAD Model and a Well-Healed Analysis Provides All Required Results ATTILA Customized “Edits” Types of Edit Reports: Scalar Flux Reaction Rate Face Flow and Current Uncollided Wall Loading Many More… Types of Energy Sets: 14.1 MeV Neutrons Only Thermal Neutrons Gamma Ray Groups… Types of Spatial Sets: Region Surface Line Points and Grids Many More…

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