5th International Serpent UGM, Knoxville, TN, Oct. 13-16...

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New features in Serpent 2 for fusion neutronics

5th International Serpent UGM, Knoxville, TN, Oct. 13-16, 2015Jaakko LeppänenVTT Technical Research Center of Finland


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Fifth level

Outline

Background

I Serpent overview

I New applications

CAD-based geometry type in Serpent 2

ITER C-Lite calculations

I First results: M&C 2015

I New results: shut-down dose rate calculations

Ideas for future work




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Background

Serpent is a continuous-energy Monte Carlo reactor physics burnup calculation code,developed at VTT Technical Research Centre of Finland since 2004:1

I Originally developed for lattice physics, although currently used for a variety ofapplications in fission reactor analysis

I Three-dimensional universe-based CSG geometry model, particle transportbased on the combination of surface- and delta-tracking

I Cross sections read from ACE format data libraries (“laws of physics” sharedwith MCNP), decay and fission yield data from standard ENDF files

I Built-in depletion solver (CRAM2 and automated calculation routines for burnupcalculation and spatial homogenization

I Parallelization by OpenMP and MPI

Serpent is distributed by the OECD/NEA Data Bank and RSICC, and has about 460users in 142 organizations in 36 countries around the world.

1For a more complete description, see project website – http://montecarlo.vtt.fi2M. Pusa. "Numerical Methods for Nuclear Fuel Burnup Calculations," D.Sc. Thesis, Aalto University, 2013

http://montecarlo.vtt.fi




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Background

A major part of Serpent development is currently devoted to coupled multi-physicssimulations, which involves two-way coupling to fuel performance, thermal hydraulicsand CFD (OpenFOAM) codes:3

I Based on internal light-weight solvers (FINIX and COSY) and external coupling

I Passing of state-point information is handled via a multi-physics interface,without any modifications to main geometry input

Simulation of gamma heating requires a photon transport mode, which was introducedin the latest update (2.1.24):

I Photon energies ranging from 1 keV to 100 MeV, reaction cross sections fromACE format libraries, additional data for interaction physics (photo-atomic)

I Built-in response functions for dose rates, radioactive decay source mode easilycombined with burnup or activation calculation

I Development of a coupled neutron-photon transport mode will begin in late 2015

3J. Leppänen, et al. "The Numerical Multi-Physics Project (NUMPS) at VTT Technical Research Centre of Finland," Ann.Nucl. Energy 84 (2015) 55-62.




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Background

Work on the multi-physics interface and CFD code coupling also lead to the develop-ment of two new geometry types:

1) Unstructured mesh-based geometry type4

I Geometry composed of a polyhedral unstructured volume mesh

I Based on the OpenFOAM file format

2) CAD-based geometry type5

I Solid bodies formed using unstructured triangulated surface mesh

I Based on the STL file format

Photon transport capability and advanced geometry types offer the possibility to ex-tend the scope of Serpent applications to new fields beyond reactor analysis, includingradiation shielding and fusion neutronics.

4J. Leppänen, et al. "Unstructured Mesh Based Multi-physics Interface for CFD Code Coupling in the Serpent 2 Monte CarloCode," In Proc. PHYSOR 2014, Kyoto, Japan, Sept. 28 - Oct. 3, 2014.

5J. Leppänen. "Development of a CAD Based Geometry Model in Serpent 2 Monte Carlo Code," Trans. Am. Nucl. Soc. 111(2014) 663-667.




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CAD-based geometry type in Serpent 2

Overview of methodology:

I Conversion from advanced formats to triangulated STL can be accomplishedusing most CAD tools, no further processing or conversion to CSG required

I Both ASCII and binary STL supported

I STL geometries are handled as separate universes, individual solids as cells

I Geometries can be nested inside each other – no need to specify void space,can be combined with OpenFOAM mesh-based geometry type

I Cell search routine is based on ray tests, designed to cope with small holesbetween surface triangles (caused, e.g. by limited numerical precision)

I Adaptive N-tree search mesh used to speed up the cell search routine

I Performance of delta-tracking is not strongly dependent on the resolution of thegeometry model

The STL format was chosen for Serpent 2 because of its simplicity – no third-partylibraries or source code used in the implementation.




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C-Lite calculations – first results

The C-Lite model (V1 Rev. 131031) of ITER was used as the test case for the newCAD-based geometry type in a paper presented at M&C 2015 in April:6

I 11 components / 1,548 solids / 1,842,576 points / 614,192 triangular facets

I Conversion from STEP to STL using FreeCAD

The calculations were limited by the lack of material data and a realistic neutron sourcedistribution, so the main purpose of this study was to see if the new geometry typecould handle large and complicated systems:

I The geometry was tested by running a large number of consistency checks

I Volumes were calculated by Monte Carlo sampling and compared to valuesgiven by FreeCAD

I Computational performance tested by running a transport simulation

The calculations revealed that conversion to STL using FreeCAD produced a large holein one of the solids, which was later fixed by switching to SpaceClaim.

6J. Leppänen. "CAD-Based Geometry Type in Serpent 2: Application to Fusion Neutronics," In Proc. SNA + M&C 2015,Nashville, TN, USA, April 19-23, 2015.




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Table 1 : C-Lite model of the ITER fusion reactor. Number of points, triangular facets and solidsin the STL geometry model, and the size of the adaptive search mesh. Cryostat, control andcorrection coils and central solenoid were modeled in the same universe to reduce the number ofgeometry levels, and they share the same search mesh.

STL Geometry Model Adaptive Search MeshComponent Points Facets Solids Cells MemoryBlanket 108,459 36,153 157 2,473,625 354 MBDivertor 161,232 53,744 275 3,869,000 562 MBVacuum vessel ports 10,164 3,388 42 1,985,750 228 MBVacuum vessel 967,002 322,334 674 2,050,750 460 MBToroidal field coils 105,753 35,251 197 2,173,375 347 MBThermal shields 166,836 55,612 51 1,528,125 240 MBPoloidal field coils 34,758 11,586 87 814,125 133 MBBiological shield 1,836 612 7 1,799,500 194 MBCryostat 264,456 88,152 19 136,262 288 MBControl and correction 13,332 4,444 13Central solenoid 8,748 2,916 26Total 1,842,576 614,192 1548 18,056,875 2.7 GB




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Figure 1 : Serpent geometry plot showing a cross-sectional view of the ITER C-Lite geometrymodel. Separate STL solids are plotted with different colors.




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Figure 2 : Serpent geometry plot showing a cross sectional view of a divertor cassette.Separate STL solids are plotted with different colors and the search mesh is shown adaptedaround the boundaries.




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Figure 3 : Left: Large hole in one of the STL solids forming the cryostat caused by conversion toSTL using FreeCAD (used in the calculations of the M&C 2015 paper). Right: Same solidconverted to STL using SpaceClaim (used in the calculations of this study).




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C-Lite calculations – new results

Since the M&C 2015 paper the work has continued to testing the capabilities for acti-vation and shut-down dose rate calculations with a two-stage calculation scheme:

1) Neutron transport simulation

I Constant power operation at 500 MW for 400 seconds, 50/50 D/T mix

I Source distribution from plasma simulation (See Paula’s presentation)

I Result: material activation using the built-in depletion routine in Serpent 2, eachSTL solid handled as a separate material zone (1,548 zones)

2) Photon transport simulation

I Radioactive decay source obtained from the neutron activation calculation

I Result: absorbed dose rates at various cooling times calculated using built-inresponse functions (NIST mass-energy attenuation data)

NOTE: As in the M&C 2015 paper, the results cannot be considered physically realisticbecause of the lack of accurate material data.7

7Biological shield was modeled as concrete, all other components as stainless steel.




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= 0.1= 0.1

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Figure 4 : Results of neutron transport simulation: Volume-averaged flux. Left: XY-plot averagedover axial dimension. Right: RZ-plot averaged over full rotation angle.




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= 0.1= 0.1

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Figure 5 : Results of neutron transport simulation: Volume-averaged total collision density.Left: XY-plot averaged over axial dimension. Right: RZ-plot averaged over full rotation angle.




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= 0.1= 0.1

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Figure 6 : Results of photon transport simulation: Volume-averaged photon emission density.Left: XY-plot averaged over axial dimension. Right: RZ-plot averaged over full rotation angle.One minute after shut-down.




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= 0.1= 0.1

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rate(G

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Figure 7 : Results of photon transport simulation: Volume-averaged dose rate. Left: XY-plotaveraged over axial dimension. Right: RZ-plot averaged over full rotation angle. One minuteafter shut-down.




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= 0.1= 0.1

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Figure 8 : Results of photon transport simulation: Volume-averaged photon emission density.Left: XY-plot averaged over axial dimension. Right: RZ-plot averaged over full rotation angle.One hour after shut-down.




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= 0.1= 0.1

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Figure 9 : Results of photon transport simulation: Volume-averaged dose rate. Left: XY-plotaveraged over axial dimension. Right: RZ-plot averaged over full rotation angle. One hour aftershut-down.




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= 0.1= 0.1

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Figure 10 : Results of photon transport simulation: Volume-averaged photon emission density.Left: XY-plot averaged over axial dimension. Right: RZ-plot averaged over full rotation angle.One day after shut-down.




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= 0.1= 0.1

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Figure 11 : Results of photon transport simulation: Volume-averaged dose rate. Left: XY-plotaveraged over axial dimension. Right: RZ-plot averaged over full rotation angle. One day aftershut-down.




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= 0.1= 0.1

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issiondensity

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Figure 12 : Results of photon transport simulation: Volume-averaged photon emission density.Left: XY-plot averaged over axial dimension. Right: RZ-plot averaged over full rotation angle.One week after shut-down.




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= 0.1= 0.1

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Figure 13 : Results of photon transport simulation: Volume-averaged dose rate. Left: XY-plotaveraged over axial dimension. Right: RZ-plot averaged over full rotation angle. One week aftershut-down.




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Running times:

I All test calculations were run on a 12-core 3.47 GHz Intel Xeon workstation

I Geometry processing takes about 2 minutes (reading of STL data, forming theadaptive search mesh, etc.)

I Activation calculations with 100 million neutron histories run for 6 hours (analogcapture) / 11 hours (implicit capture)

I Running time for depletion solver was negligible (seconds)

I Photon transport simulations with 100 million histories run for 13-19 minutes(implicit source biasing)8 / 80-140 minutes (analog sampling)9

Parallel scalability was practically linear up to 12 OpenMP threads.

8Source points sampled uniformly, statistical weight adjusted according to local emission probability9Source points sampled uniformly, rejection sampling based on local emission probability




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Lessons learned from this study:

I The STL-based geometry type seems to work with photons as well, althoughdelta-tracking runs into problems with very short mfp’s of low energy(E ∼ 1 keV) photons

I Handling 1,548 separate material zones was not a problem for activationcalculation or radioactive decay source, but the spatial sub-division is clearly notsufficient for some of the larger solids, e.g in the biological shield

I It was possible to use the same geometry model in both neutron and photontransport calculation with only a few minor modifications in the input

I Use of implicit capture for neutrons improves the statistics in the outer parts ofthe geometry, but also leads to significant increase in running time (FOM’s notyet compared)

I Simple source biasing routine works well with the radioactive decay source,although this is probably not the case in geometries where high- and low-activeparts are not as well shielded from each other




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The C-Lite model will be used as the test case for future studies as well:

I Accurate material compositions needed for physically realistic simulations(defining the compositions of 1500 material zones is not a trivial task)

I Performance comparison to CSG model (Serpent input exists, but the geometryis not a 100% match with the CAD model)

I Calculations with FENDL or TENDL data (instead of ENDF/B-VII) to account formissing nuclides and high-energy reaction channels in activation calculations

Moving to more complicated models:

I Test calculations with refined geometries for individual components

I Test calculations with hybrid STL solid / OpenFOAM mesh-based geometries

I Finding the practical limitations: what is the impact of model complexity onprocessing time, running time and memory consumption




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Other future plans:

I Studies on the effects of local variation in source distribution on neutron-inducedreaction rates

I Validation by comparison to experiments (JET)

Other potential fusion neutronics applications for Serpent:

I Heat deposition, helium production and material DPA calculations, etc. – can bedone with standard tallies

I Tritium breeding calculations – can be done using built-in depletion routines

I Multi-physics simulations – Serpent-OpenFOAM interface exists and is alreadyused for fission applications

I Fusion power plant (DEMO) simulations with Serpent coupled to the APROSsystem code




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Topics for Serpent development:

I Development of a high-fidelity neutron source model continues as the Ph.D.project of Paula Sirén

I Development of a coupled neutron-photon transport mode will be started in thenear future

I Development of effective variance reduction techniques is a necessity, especiallyfor radiation shielding calculations

I Validation of photon and 14 MeV neutron physics with benchmark calculations(SINBAD)




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Thank you for your attention!

Questions? - [email protected]



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