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ATTILA* Deterministic Code (Status and plans for validation)

ATTILA* Deterministic Code (Status and plans for validation). Mahmoud Z Youssef UCLA. Presented at ITER-TBM Meeting, May 10-11, 206 * Some of the viewgraphs are taken from Failla and Loughlin presentations (Frascati Meeting, Dec. 2005). Topics.

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ATTILA* Deterministic Code (Status and plans for validation)

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  1. ATTILA* Deterministic Code(Status and plans for validation) Mahmoud Z Youssef UCLA Presented at ITER-TBM Meeting, May 10-11, 206 * Some of the viewgraphs are taken from Failla and Loughlin presentations (Frascati Meeting, Dec. 2005)

  2. Topics • Deterministic versus Monte Carlo methods in nuclear analysis: Pros and Cons • ATTILA code: • Featues • Examples of its application • Status and plans for validating ATTILA for adoption in ITER nuclear analysis such as • Design of ITER-TBM ports • Design of ITER diagnostics port plugs

  3. Features of Deterministic and Monte Carlo codes • Deterministic codes (e.g. DANTSYS,DOORS): • In solving Boltzman neutron balance equation neutron/g energy and angular direction are discretized (Muligroup, Sn). Cross-section are approximated with series of Legendre polynomials (Pn) and averaged over energy bins. • structured meshes are used to approximate complex 3D geometries(no mixing between different coordinate systems, e.g. rectangular, cylindrical). • n/g fluxes and associated reaction rates (tritium production, damage, etc.) are calculated everywhere in the system. • Monte Carlo codes (e.g. MCNP): • It is a stochastic process. Millions of source particles are followed in a random processes to estimate the required fluxes and associated responses at pre-selected locations (tallies). 3D complex geometries are described by combination of surfaces intersections to form bodies (zones). Point-wise nuclear data are used.

  4. Advantages and Disadvantages • Deterministic codes • Advantages: • Fluxes and responses are calculated everywhere. No need to redo separate runs if additional responses are needed. • Shorter time to run a case compared to Monte Carlo methods. • Disadvantages: • Large disc space is required to store angular flux • Ray effect due to angular discretization • Cross section should be shielded particularly in resonance regions • Monte Carlo codes • Advantages: • Complex geometry can be modeled accurately. However, extensive effort is needed to generate the appropriate “geometry cards”. This is why CAD-based versions are in progress. • Disadvantages: • Fluxes and responses are calculated at pre-selected locations • Visualization of the responses in the whole system is not possible.

  5. What is Attila? • A finite element Sn neutron, gamma and charged particle transport code using 3Dunstructured grids (tetrahedral meshes) • Geometry input from CAD (Solid Works, ProE) • Supplied by Transpire Inc.

  6. Version 5.0 – New Features • Released November 15, 2005 • Last Collided Flux Option for Post Processing • High angular resolution achievable, used for: • Resolving streaming paths • Evaluation of solution far from scattering media • Integrated Depletion Module • Functionality similar to ORIGEN • Automated Weight Windows Generation • Writes mc_wwinp file • User control over grid resolution • Post graphics and visualization in the entire system Failla pres

  7. 2006 – New Functionality • Integrated Activation Capability • Extension of current depletion module to include decay source terms • Group-wise Adaptive SN Order • For ITER, can run 14 MeV source bin at a high Sn order to transport the primary flux • Distributed Memory Parallel • Linear scaling achieved on test version up to 256 processors • A primary motivation is to distribute memory resources Failla pres

  8. Benchmark • At the exit to the labyrinth • To the side of the roof penetration. • Opposite the horizontal port in the mid-plane • 50cm above the floor opposite the horizontal port • In the middle of the vessel wall Loughlin pres.

  9. At exit to labyrinth Loughlinpres.

  10. Model of ITER Simplification was needed to reduce the number of bodies and the time taken to read in the geometry Loughlinpres.

  11. Simplified Model of ITER (with unstructured Meshes) • Approx 300,000 elements • For detailed ITER calculation s, estimate about 600,000 elements Failla pres

  12. Another Simplified model with a Diagnostic Port Simplified Source location shown in white Failla pres

  13. Visualization of neutron flux Iso-surface contour of the total flux Failla pres

  14. Visualization of neutron flux (2) Iso-surface contour of the total flux Failla pres

  15. Analysis Geometry read into Attila Attila mesh: 424918 cells Loughlinpres.

  16. Results Loughlinpres.

  17. Results, Cont. Failla pres

  18. Results, cont. Failla pres

  19. ATTILA for Detailed ITER Calculations • Estimate about 600,000 elements needed for detailed calculations of a 40° section • - Would equate to approx 72 CPU hours • - Single collision high SN order for primary flux transport • - S18 scattering calculation • Results at any point can be extracted using the third order finite element spatial representation • Streaming in gaps can be done as a post processing step • Response functions calculated as a post processing stepeverywhere in the system. • Energy dependent flux in selected parts can be output for activation calculations Failla pres

  20. Attila and MCNP • Two complimentary methods • ATTILA • -Scoping studies and design calculations • - Activation • - Global solution field data (mapping) • MCNP • Verification • Through the combination of CAD to MCNP translation and Attila adjoint based weight windows generation, it is now possible to perform two calculations (Attila and MCNP) faster than MCNP alone Failla pres

  21. Computational Requirements • Relative to Monte Carlo • Attila CPU time << Monte Carlo • Much more data available from a single calculation • Very efficient for problems with: • - Large attenuations • - Activation • - Local field values desired (mapping) • Attila Memory consumption >> Monte Carlo • - Primary driver for parallelization • - Recommend 4 GB or more for ITER • -Disk storage requirements can be substantial • - Centralized computing system highly desirable Failla pres

  22. Status and Chronological Events for ATTILA Benchmarking (1) October, 05: Attila was introduced to the fusion community in Garching by Gregory Failla (CEO of Transpire, Inc. ) December, 05: A meeting in Frascati, Italy, was held to discuss CAD-based codes. Fallia and Loughlin (UKAEA) showed comparison between MCNP and Attila for several cases. Franco Federici (ITER-IT) emphasized that for Attila to be adopted for ITER-related nuclear analysis, it must be benchmarked for quality QA purposes. March, 06: Dave Johnson (US Diagnostic leader), in a meeting with M. Sawan and M. Youssef, emphasized the usefulness of Attila in the design of diagnostics portplugs.Hot spots can be easily identified from Attila visualization output plots.

  23. Status and Chronological Events for ATTILA Benchmarking (2) • April 5, 06: • A teleconference was arranged by UCLA in which neutronics experts from both EU and US have participated. Failla, from Transpire Inc., gave an overview. Capabilities and limitations of Attila were discussed. It was decided to: • Benchmarking Attila for 3 integral experiments (tungsten, streaming, and bulk shielding) provided by Paola Batistoni (Frascati). Comparison will be made to MCNP results. • It was agreed that UCLA will undertake this benchmarking task

  24. One on the 3 benchmarks; Streaming Experiment Two benchmarks experiments Streaming Experiment Bulk Shielding Experiment

  25. Status and Chronological Events for ATTILA Benchmarking (3) • April 7, 06: • Logistics were discussed in a teleconference (Nelson, Johnson, Youssef, Sawan): They are: • -Four (4) neutronics and CAD persons from the US will be trained in WA on how to use Attila (may 31-June 2). • - Cost estimates for Attila benchmarking and training. • A meeting will was held in Madison, Wi, (July 24-26,06) to discuss: • - Progress in CAD-based Monte Carlo code development • - Attila benchmarking IF passed QA, Attila can be very powerful tool in ITER-TBM nuclear design

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