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Monaco/MAVRIC: Computational Resources for Radiation Protection and Shielding in SCALE

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Monaco/MAVRIC: Computational Resources for Radiation Protection and Shielding in SCALE

Douglas E. Peplow, Stephen M. Bowman,

James E. Horwedel, and John C. Wagner

Nuclear Science and Technology Division

Oak Ridge National Laboratory

Computational Resources for Radiation Protection and Shielding - II

American Nuclear Society Winter Meeting

November 16, 2006 Albuquerque, New Mexico

- Monaco — multi-group Monte Carlo code
- MORSE physics
- SCALE Generalized Geometry Package (same as KenoVI)

- MAVRIC — Automated Variance Reduction
- CADIS Methodology
- GTRUNCL3D and TORT
- Monaco for Monte Carlo Calculation

- GeeWiz — the Windows GUI for using many SCALE programs
- Monaco/MAVRIC will be part of SCALE 6

- Standardized Computer Analyses for Licensing Evaluation
- Collection of codes for performing
- criticality safety
- radiation shielding
- spent fuel characterization
- reactor physcis
- radiation source terms and decay heat

- Functional modules – physics calculations
- KENO, Monaco, ORIGEN-S, NEWT, XSDRNPM

- Control modules automate the execution and data exchange of individual codes to perform various types of analyses in calculation sequences
- CSAS, MAVRIC, TSUNAMI, TRITON

- Multi-group and continuous energy cross-section data

- SAS1 – 1-D discrete ordinates Shielding Analysis Sequence
- automates cross-section processing, transport calculation, and calculation of dose rates outside a defined shield
- Combined 1-D criticality/shielding analysis (e.g. CAAS)

- SAS4 – 3-D Monte Carlo Sheilding Analysis Sequence designed for calculation of radiation doses exterior to a transport/storage cask. Uses XSDRNPM to calculate adjoint fluxes for the generation of biasing parameters
- MORSE
- 3-D Monte Carlo functional module used in SAS4
- Different geometry package than the SCALE Monte Carlo criticality (KENO) codes
- Legacy code, geometry package has not been updated in >20 years

- SAS4 – Shielding Analysis Sequence
- Automated 1-D axial or radial variance reduction
- Not updated in more than a decade

- Design limitations based on cylindrical cask geometry
- Effective for cask mid-plane and top center doses
- Not well suited to cask corners or very heterogeneous geometries
- Not effective for general purpose shielding analyses
- Hence, need for modern Monte Carlo tool with automated 3-D variance reduction (AVR) for general shielding applications

- 3-D Multi-group Monte Carlo
- MORSE physics
- SCALE Generalized Geometry Package (same as KenoVI)

- Fixed source
- Variety of geometric shapes
- Can use a mesh-based source

- Tallies
- Point detectors, region tallies, mesh tally
- Convolves fluxes with detector responses

- Variance Reduction
- Biased source energy distribution
- Source direction distribution
- Path length stretching
- Point detector tallies
- Weight windows by region and energy group

- Advanced Variance Reduction
- Mesh/energy group based importance map
- Mesh/energy group based biased source

3-D Automated Variance Reduction

- SCALE cross section processing
- GTRUNCL3D and TORT
- Computes the adjoint flux for a given response

- Monaco for Monte Carlo calculation
- Importance map (weight windows for splitting and roulette)
- Biased source distribution

Consistent Adjoint Driven Importance Sampling

- From the adjoint flux
- Importance map for MC transport (weight windows for splitting and roulette)
- Biased source distribution

- Biased source and importance map work together (i.e., are consistent)
- A. Haghighat and J. C. Wagner, “Monte Carlo Variance Reduction with Deterministic Importance Functions,” Progress in Nuclear Energy, 42(1), 25-53, (2003).

- typical problem:

- Want to find:

flux

- Or some detector response related to flux:

- If the adjoint flux for a given detector response is known:

- Then the detector response is simply:

- Unfortunately, the exact adjoint flux may be just as difficult to determine as the forward flux.

- With an approximate adjoint flux for a given detector response:

- Total detector response is approximated as:

- Biased source distribution found to be:

- Sampled particles start with weights of:

- Weight window target weight values:

- Weight window size: (c=upper/lower)

An implementation of the CADIS Methodology

- Cross sections
- Multi-group SCALE libraries
- Create adjoint and forward cross section sets

- Find the approximate adjoint flux
- GRTUNCL3-D – first collision code (for pnt det)
- TORT – 3-D discreet ordinates transport code

- Forward Monte Carlo - Monaco
- Uses mesh-based biased source
- Uses mesh-based importance map (weight windows)

- Automate as much as possible

Monaco with Automated Variance Reduction using Importance Calculations

SCALE

Driver

and

MAVRIC

Input

BONAMI / NITAWL or

BONAMI / CENTRM / PMC

Resonance cross-section

processing

Optional: TORT adjoint cross sections

ICE

Optional: first-collision source calculation

GRTUNCL-3D

TORT

Optional: 3-D discrete ordinates calculation

Monaco

3-D Monte Carlo

End

Speed up: 583

Speed up: 28

- Powerful 3-D interactive visualization tool that displays KENO V.a or KENO-VI geometry models
- Plot calculated results (e.g., fluxes and reaction rates) over geometry

- help
- top view, side view
- toggle wireframe
- toggle highlight edges
- orbit
- rotate
- pan
- zoom options
- axis
- legend
- simple cuts
- rebuild in window
- dockable toolbars

- MAVRIC Sequence
- Automatic homogenization in importance map
- Refine standard set of TORT parameters
- Incorporate new Monaco tallies
- Optimizing mesh tallies

- Monaco
- Modern F95 programming structures
- Modern, block/keyword input structure
- Output to separate (html) tables
- Larger variety of source descriptions
- Larger variety of tally options – multipliers, totals

- Cross-Section Data
- ENDF/B-VI coupled multigroup library

- Testing, Testing, then a bit more Testing

Discussion & Questions