direct use of cad geometry in monte carlo radiation transport
TRANSCRIPT
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Direct Use of CAD Geometry in Monte Carlo
Radiation Transport
Paul Wilson
CNERG/FTI Neutronics Team
U. Wisconsin-Madison
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Nuclear Design & Analysis
3-D Geometry Capability
Enhancements
Radiation Transport
& Effects Code
Development
L. El-Guebaly
M. Sawan
T. Tautges (ANL)
E. Marriott
P. Wilson
D. Henderson
(A. Ibrahim)
T. Bohm
8 Research Staff
1 Visiting Scientist 7 Graduate Students
3 U/G Students
CNERG/FTI Neutronics Team
(K. Dunn) (S. Slattery)
S. Jackson
2
(E. Relson)
(E. Biondo) (A. Jaber)
(A. Robinson)
(M. Klebenow)
(L. Mynsberge) (M. Cusentino)
03.27.2012 P.Wilson: Direct use of CAD in Monte Carlo
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Overview
• Motivation
• Developer’s Perspective
– Core Software Infrastructure
– Fundamental Geometry Operations
– Methods & Accelerations
– Performance
– Robustness
• User’s Perspective
– Workflow
– Examples
• Current Research 3 03.27.2012 P.Wilson: Direct use of CAD in Monte Carlo
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Monte Carlo Transport in Fusion Neutronics
• Complex shielding problems
–Monte Carlo preferred
– Intricate geometries created by hand
• Complex cell boundaries
–Especially tori
• Small numerical gaps in geometry
• Lost particles accepted as necessary
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Three Motivations for CAD-Based Monte Carlo Tools
• Faster
–Reduce human effort – faster design iteration
–Provide common domain for coupling to other analyses
• Cheaper
–Reduce human effort
• Better
–Avoid human error in conversion
– Include higher-order surface descriptions in analysis
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Promise of CAD-based Monte Carlo Transport
6
Robustn
ess
Human Efficiency
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Developer’s Perspective
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Developers Perspective: Software Infrastructure
Direct Accelerated Geometry Monte Carlo
Monte Carlo Application
Geometry Representation A
Geometry Representation B
DAGMC Geometry Representation
Mesh Oriented datABase [MOAB]
Common Geometry Module [CGM]
ACIS Solid Modeling Engine
OpenCascade Solid Modeling Engine
Other Solid Modeling Engine
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Demonstrated Implementations
• MCNP5 (LANL)
– Main development & testing platform
• Tripoli 4 (CEA/France)
– UW implementation
• GEANT4
– Implementation by S. Korean researchers
• FLUKA
– Interest by NASA users and FLUKA developers
• MCNPX 2.x (LANL)
– Initial development platform
– Being merged with MCNP5 MCNP6 03.27.2012 P.Wilson: Direct use of CAD in Monte Carlo 9
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Developers Perspective: Software Infrastructure
Geometry & Mesh Infrastructure
• CGM
– Common API to many solid modeling engines
– Virtual geometry capabilities for merging and metadata
• MOAB
– Robust & efficient mesh representation
– Common API to many mesh formats
• Both are under independent with ongoing improvements
– Access to other mesh operations/services
– Other users benefit from developments
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Developers Perspective: Fundamental Geometry Queries
DISTANCE TO BOUNDARY
• For a given point, x, and direction, W,
find • the nearest boundary, B, and
• the distance, d, to that boundary
11
W
x
B
d
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Developers Perspective : Fundamental Geometry Queries
POINT LOCATION
• For a given point, x, find
– the unique volume, V, containing that
point
12
x
V
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Developers Perspective: Supporting Operations
SURFACE CROSSING
• For a given point, x, on the boundary, B, of volume, V, find
–which volume, V', will be entered next
13
x
V'
V
B
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Developers Perspective: Supporting Operations
SURFACE NORMAL
• For a given point, x, on the boundary, B, of volume, V, find
– the unit normal, n, to that surface
14
x
V'
V
B n
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Developers Perspective: Extra Geometry Information
METADATA QUERIES
• Metadata can be added to geometry to facilitate
–Material assignment
–Boundary conditions
–Source definition
–Tally/response definition
–Variance reduction
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The Need for Acceleration Techniques
• Ray-tracing: fundamental operation of Monte Carlo transport
–Ray-tracing on 2nd order analytic surfaces is efficient
–Ray-tracing on arbitrary high-order surfaces requires high-order root finding
–Also need to detect curves where surfaces meet
• More complexity with high-order surfaces
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Accelerations
• Imprint & merge
– Reduce complexity of determining neighboring regions in space
– Reduce number of ray-firing operations
• Faceting
– Reduce ray-tracing to always be on (planar) facets, but
• introduce approximations
• millions of individual facets
• Oriented Bounding Box Tree
– Accelerate search of millions of surfaces
– Reduce number of surface tests 17 03.27.2012 P.Wilson: Direct use of CAD in Monte Carlo
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Developers Perspective: Methods & Accelerations
Imprint & Merge
A
F
B
C
E
D
• Imprinting
• Merging
• Each surface in max. 2 cells
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Avoiding the Explicit Calculation of the “Complement”
• CAD-based solid models do not typically represent non-solid regions
–e.g. voids, coolants
• Explicit calculation
–Boolean operations in CAD (or CUBIT)
–Often computationally expensive
• Implicit determination
–Volume bounded by surfaces with only 1 cell following imprint & merge
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Accelerate Testing of Each Bounding Box
• Simple (inexpensive) bounding box test
–Streaming distance to closest approach
–Collision distance to closest approach
dstream
x
dcollision
dmax
dmin
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Oriented Bounding Box on Facets as Nodes in a Tree
• Axis-aligned bounding box often larger than necessary
• Oriented bounding box makes smaller boxes
• OBB on facets allows finer-granularity boxes to be arranged in tree
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Tree Traversal Could Have O(log2(n)) Bounding Box Tests
• Distance limit should guarantee improved performance
• Tree root for each cell/volume
–Accelerate ray-tracing in implicit complement
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OBB-Tree Traversal Performance Tested on 3 Geometries
Sphere “Deathstar”
ITER Benchmark Complement
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Performance does not meet expectations
24
0
50
100
150
200
250
300
350
400
450
1.E+04 1.E+05 1.E+06 1.E+07
Avera
ge R
ay-T
racin
g T
ime (ms)
Number of Triangles in Model
Sphere (No Edge Length)
DeathStar (No Edge Length)
ITER Volume (No Edge Length)
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High Valence Vertices
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Edge Length Guidance
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Improved Performance with Better Faceting
27
0
50
100
150
200
250
300
350
400
450
1.E+04 1.E+05 1.E+06 1.E+07
Avera
ge R
ay-T
racin
g T
ime (ms)
Number of Triangles in Model
Sphere (No Edge Length) Sphere (Edge Length)
DeathStar (No Edge Length) DeathStar (Edge Length)
ITER Volume (No Edge Length) ITER (Edge Length)
Most time spent
traversing OBB Tree
Most time spent in ray-
triangle intersection
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CAD-based Monte Carlo Neutronics
• Facilitates even more complex geometry
• More opportunity for
–Small features and geometrical gaps
–Automated precision to close gaps
• Impact on lost particles unclear
• Lost particle rate used as one performance metric (< 10-5 – 10-6 )
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Initial Impact of DAGMC
29
Robustn
ess
Human Efficiency
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New Problems with CAD-based Monte Carlo
• Quality of CAD geometry
–Small gaps & overlaps
–Previous applications of CAD less sensitive
• Human efficiency gains reduced
–New skills required
• DAGMC-specific challenges/opportunities
– Inconsistent faceting
–Robustness of tracking algorithm
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Lost Particle Risk
31
Robustn
ess
Human Efficiency
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Lost Particle Risk
• H. Iida (2008)
• Intrinsically shielding/deep penetration
• Intense variance reduction necessary
• Some lost particles have high weight
32
0.0E+00
5.0E+08
1.0E+09
1.5E+09
2.0E+09
2.5E+09
3.0E+09
3.5E+09
4.0E+09
4.5E+09
5.0E+09
1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05
Window width WUPN
Tota
l flux in t
he #
1 S
phere
ww1-np ww1-nww2-np ww2-nChina-np China-n
10-4
~10-6
3 x 10-4
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Implicit Complement
33
Robustn
ess
Human Efficiency
Handle small modeling gaps
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Implicit Complement
• Merging of adjacent surfaces accelerates ray-tracing
• Complex volume defined by all unmerged surfaces
– Inefficient definition in native MCNP
–OBB-tree preserves efficiency in DAGMC
• Small gaps between volumes are automatically captured in implicit complement
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Watertight Faceting
35
Robustn
ess
Human Efficiency
Avoid modeling holes
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Watertight Geometry
• Watertight faceting not guaranteed in merged geometry
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Robust Tracking
37
Robustn
ess
Human Efficiency
Avoid numerical holes
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Robust Tracking
• Ray-tracing failure modes
X
X
X
X
X
Behind previous surface
(numerical)
Ahead of next
surface (numerical)
Tangent to Surface
(numerical)
Edge/ Point
Intersection (logical)
Leak Between Triangles
(numerical)
Oscillate Between Triangles (logical)
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Robust Tracking
Plücker ray-triangle test
Ray Intersect Facets
Physics Application
Tracking Algorithm
Edge/Point Post-processing
Point Inclusion Test
Model Particles
Simulated [millions]
Lost Particles
Original Robust
UW Nuclear Reactor
41 5649 ± 178 0
Advanced Test Reactor
74 141 ± 32 0
40° ITER Benchmark
225 67 ± 39 0
ITER TBM 205 665 ± 184 0
ITER Module 4
59 59 ± 19 0
ITER Module 13
79 450 ± 60 0
FNG Benchmark
1310 31273 ±
989 0
ARIES First Wall
4070 25 ± 18 0
HAPL IFE 286 65 ± 19 0
Z-Pinch Fusion
409 2454 ± 317 0
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Overlap Tolerance
40
Robustn
ess
Human Efficiency
Handle small overlaps
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Overlap Tolerant Tracking
• User specifies an overlap tolerance
–Only numerical tolerance in DAGMC ray tracing
• Search behind current point for intersection within tolerance
• Update logical location if in overlap
• Does NOT preserve exact physics in overlap region
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User’s Perspective
42
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Workflow Includes a Variety of New Tools and Skills
Generate CAD
Geometry
Annotate CAD
Geometry
Prepare Input File
DAG-MCNP5
Read Model and Initialize Search Tree
Report Tally Results
Perform Random Walks
Standard CAD software tools are used to define the solid model. Models are exported to a standard geometric-model file format supported by Common Geometry Module (CGM).
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Workflow Includes a Variety of New Tools and Skills
Generate CAD
Geometry
Annotate CAD
Geometry
Prepare Input File
DAG-MCNP5
Read Model and Initialize Search Tree
Report Tally Results
Perform Random Walks
Allocate materials and densities Define boundary conditions Define tally locations Imprint & Merge (Currently use CUBIT mesh generation tool for this step)
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Workflow Includes a Variety of New Tools and Skills
Generate CAD
Geometry
Annotate CAD
Geometry
Prepare Input File
DAG-MCNP5
Read Model and Initialize Search Tree
Report Tally Results
Perform Random Walks
Skip cell definitions Skip surface definitions Provide data cards • Material definitions • Tally modifiers • Source definition • etc…
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Workflow Includes a Variety of New Tools and Skills
Generate CAD
Geometry
Annotate CAD
Geometry
Prepare Input File
DAG-MCNP5
Read Model and Initialize Search Tree
Report Tally Results
Perform Random Walks
Generate tree-based decomposition of facets on model surfaces
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Workflow Includes a Variety of New Tools and Skills
Generate CAD
Geometry
Annotate CAD
Geometry
Prepare Input File
DAG-MCNP5
Read Model and Initialize Search Tree
Report Tally Results
Perform Random Walks
Circumvent standard functions involved in ray-tracing, esp. • ray-surface intersection • point-in-volume determination • neighboring cell determination
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ITER Benchmark
• Comparing 4 problems
– Neutron wall loading
– Divertor fluxes and heating
– Magnet heating
– Midplane port shielding/streaming
• Participants
– UW, FZK, ASIPP, JAEA + ATTILA (UCLA/PPPL)
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Neutron Wall Loading
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Module Number
NW
L [
MW
/m2]
ASIPP
FZK
JAEA
UW
UCLA
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IB TFC heating
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0 200 400 600
Nucle
ar
Heating (
kW
)
Distance from top of IB TFC (cm)
ASIPP
FZK
JAEA
UW (geometry fixed)
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Performance Compared Using Translated Models
MCAM Translation
McCad Translation
DAGMC Solid Model
ITER Benchmark Model: >800 cells, ~10,000 surfaces
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Overall Performance Less than 3x Slower than Native Geometry
• Performance of translation approaches vary by 60%
Model Number of Volumes
Number of Surfaces
Relative CPU-Time
MCAM translation
4148 3192 1
McCad translation
6031 3800 1.63
DAGMC 802 9834 2.46
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Analysis for an Initial Mod 13 Design
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Mid-plane T production Mid-plane nuclear heating
Detailed 3-D Neutronics for DCLL TBM
DCLL TBM
g/cc.s
Steel damage at section X2
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Surface Source Approach Applied to ITER FWS Mod. 4
Using full model
Using surface source
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Assessment of Accuracy of Surface Source Approach
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Assessment of Accuracy of Surface Source Approach
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Application to ARIES-CS Compact Stellarator
• Geometry complex
• FW shape and plasma profile vary toroidally within each field period
• Cannot be modeled by standard MCNP
Examined effect of helical geometry and non-uniform blanket and divertor on NWL distribution and total TBR and nuclear heating
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Source Probability Map
Increasing Poloidal Angle (0° at O/B midplane)
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NWL Maps (colormaps in MW/m2)
Poloidal Angle (degrees)
Toro
idal A
ngle
(degre
es)
x max
x max
x max
5 cm SOL
30 cm SOL
uniform src
Radiative heating
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Multi-Physics: Coupling to CFD
• Fine mesh DAG-MCNP5 results
–1-3 mm Cartesian mesh overlay
–Total nuclear heating
• Arbitrary mesh on CAD geometry
–Tetrahedral
–Polyhedral (Star-CCM+)
• Automated interpolation using MOAB
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Multi-Physics: Coupling to CFD
• 1 of 40 fingers in ITER First Wall concept
• Beryllium plasma facing component
• CuCrZr heat sink into pressurized water
• Steel backing for structural support
• 0.2 MW/m^2 heat flux onto Beryllium
• Inlet: 0.2 kg/s water, 373 K, 3 Mpa
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Neutronics+CFD Coupling
Notice “hot spot” at elbow and center due to nuclear heating.
These temperatures are ~30C higher than UCLA results, perhaps due to nuclear heating.
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Fluid Temperature & Velocity
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Fission Applications
ATR National Science User Facility
AFIP Experiment In CFT
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Fission Applications
Irradiation Experiment Design
Simplified MCNP5 Input
DAG-MCNP5
ABAQUS CAE
ABAQUS Input File
ABAQUS
ABAQUS Output File
w/ thermal response
Geometry Model
MCNP5 Output
Geometry File
Solid Modeling Software
Automated Conversion
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Neutron Transport in Deformed Geometries
• Space reactor launch accidents may result in reactor return to earth
• Criticality of intact reactor well understood
• Impact likely to deform reactor
• Is criticality possible?
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The single pin keff increases with deformation.
• 33 volumes, 113 surfaces, 103k hex elements
• Clad is not explicitly modeled
– Clad is homogenized with fuel
• Fuel pin is surrounded by void
• Same MCNP material density was used pre/post deformation
Time Step
Stage keff
1 Undeformed 0.84479 (0.00041)
29 Last deformed step w/out dead elements
0.92412 (0.00045)
50 Last deformed step 0.96939 (0.00046)
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Fission Applications
85-Pin Full-Scale Space Reactor Impact
40 m/s on concrete
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Neutron Transport:
85-Pin Full-Scale Space Reactor Impact
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Research Directions
Advanced Mesh Tallies
• Perform track length tallies on arbitrary polyhedral mesh
–Prototype exists for tetrahedral mesh
• Develop alternative tally estimators
–Functional expansion tallies
–Kernel density estimators
• Explore hps-adaptivity of advanced mesh tallies
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Next Steps: Human Efficiency
• Unstructured mesh tallies
–Small volume fraction tallies
–Multi-physics coupling
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Next Steps: CPU Efficiency
• Hybrid Transport
–Automated mesh generation based on CAD model
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CAD Geometry
SN Calculation • Geometry/materials • Source region • Tally regions
WW Calculation
MC Calculation
• Forward Fluxes • Adjoint Fluxes
• Variance Reduction
• Geometry/materials • Source region • Tally regions
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Research Directions
Hybrid Methods
• Monte Carlo not well-suited to deep penetration problems
• Deterministic methods not well suited to gap streaming problems
• Use deterministic methods to develop importance maps for Monte Carlo problems
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Photons
FW-CADIS (ORNL) Analog
Neutrons
Research Directions
Hybrid Methods
50 CPU-days
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Total neutron flux cumulative distribution functions (50 days)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0% 20% 40% 60% 80% 100%
Fra
ctio
n o
f vo
xels
Relative uncertainty
FW-CADIS
Analog
0.1
0.78
0.99
0.59
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Total gamma flux cumulative distribution functions (50 days)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0% 20% 40% 60% 80% 100%
Fra
ctio
n o
f vo
xels
Relative uncertainty
FW-CADIS
Analog
0.1
0.6
0.95
0.3
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Next Steps: Human Efficiency
• 3-D Activation
–Automated material mesh generation from CAD
–Efficient mesh-based photon source sampling
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CAD Geometry
MC Calculation • Geometry/materials • Source region • Tally regions
Activation Calculation
MC Calculation
• Forward Flux Mesh Tally
• Photon Source
• Geometry/materials • Tally regions
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Summary of Research Directions
• Common Domain Solution Coupling
–Neutronics-Neutronics coupling
• Hybrid acceleration of shielding
• Hybrid acceleration of source convergence
–Neutronics-”other physics” coupling
• N source term
• N feedbacks
• Advanced mesh tallies
–Alternative tally estimators
–hps-adaptivity 79
• Activation dose/depletion • Uncertainty propagation
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CAD-Based Neutronics Brings New Opportunities/Challenges
• Fundamental capability in production use for fusion shielding applications
–Robustness improvements
• Goal: Guarantee no lost particles
–Performance improvements
• Goal: Users don’t care about performance penalty
–Feature enhancement
• Goal: Extend utility of Monte Carlo radiation transport
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