by Jonathan Shimwell
To perform automated parametric multiphysics analysis of breeder blanket designs with an aim of optimising the design.
Objective
To perform automated parametric multiphysics analysis of breeder blanket designs with an aim of optimising the design.
by Jonathan Shimwell
Selection of design parameters
Parametric CAD construction
Neutronics simulation for TBR and EM
Conversion to unstructured mesh
Neutronics simulation for volumetric heating
Conversion to engineering mesh
Simulations to find stress and temperature
Evaluate design
Conversion to neutronics model
Interpolate performance & design sensitivity
Model generation
PythonOCC
Salome
Parametric
HCPB model
FreeCAD
Parametric
HCLL model
Neutronics model
MCNP
constructive
solid geometry
MCNP
unstructured
mesh geometry
Serpent
STL geometry
Serpent
unstructured
mesh geometry
Engineering
model
Parafem
model
Code Astra
model
Trelis
Hex mesh
Abaqus
Trelis
Hex mesh
OpenFoam
STEP to STL conversion
Geometry conversion
MCam / McCad
CAD to CSG
converters
Meshing
Trelis
Tet mesh
Ensight Gold
GMesh
Salome
MED
Avoid the use of constructive
solid geometry (CSG)
CAD model
Convert to CSG model
Assign materials
Parameterise CSG model
Neutronics simulation
CAD model
Convert to STL model
Assign materials
Parameterise CAD model
Neutronics simulation
No spline support. Void Generation
Lack of tools
Cell based
Rapid and controllable
Mature software
File based
Optimal parameters
Optimal parameters
CAD
model
Traditional CSG work flow
Alternative STL work flow
Blanket geometry construction
Blanket envelop input
Feature recognition
Output geometry
Front face
Edge to fillet
Top face
Variable detail blanket geometry
Surface deviation = 0.01mm
Surface deviation = 1mm
Homogenised first wall
Detailed first wall
Blanket geometry construction
Customizable cooling pipe layouts for the internal cooling plates
Blanket geometry construction
Blanket envelopes from the entire reactor can be parameterised
HCLL blanket geometry parameter options
HCPB blanket geometry parameter options
Computing techniques
Cloud computing and containerization of code was used for this project.
Containerization allows for codes to be combined with their dependencies packaged into a container and deployed on compatible infrastructure.
Serpent II
Nuclear data
Docker
Computing techniques
Docker
Singularity
Swarm
Orchestration
Compute
Containerize
Storage
Day of the week
Cluster utilisation
100%
Your local computing cluster?
Mon
Tue
Wed
Thu
Fri
Sat
Sun
Example parameter study
Interpolation of results
Li4SiO4 with 60% 6Li and Be
Tritium production
Li4SiO4 at 60% 6Li enrichment with Be
Fitting the data using Gaussian Processes and training datasets
The Gaussian functions found fits the provided data points very well?
Fitting the data using Gaussian Processes and training datasets
Red points are used for fitting
Blue points are used for testing the fit
Volumetric heating simulations
Due to the use of CAD throughout the project the same model can be used to obtain TBR, volumetric heating, temperature and stress.
Procedure for obtaining volumetric heating
Automated hex and conformal tet meshing
Neutronics mesh?
Engineering mesh
Do we need meshing algorithms designed for neutronics tallies?
Mesh element density should be concentrated in areas of high gradient.
Simulation time increases with number of mesh elements.
Meshing
Fully automated hex meshing of the geometry. Exporting to Abaques format for use with MCNP 6 unstructured mesh and Open Foam format for use in Serpent II.
Volumetric heating
Heating values obtained on unstructured mesh that conforms to material boundaries.
y
Volumetric heating
Li4SiO4
Be12Ti
Component | Be12Ti | Be |
---|---|---|
Lithium ceramic | 15.9 | 17.2 |
Eurofer first wall | 6.2 | 5.8 |
Tungsten armour | 28.1 | 26.4 |
Neutron multiplier | 4.8 | 5.0 |
Heating W/cm3
with 60% 6Li enrichment
Automatically identifying regions
First wall heat flux
Coolant outlet
Coolant inlet
Current work
Automated Portable
Parametric
Scalable
Neutronics
Conclusion
Figure shows tritium production within EU DEMO
Project carried out as part of a WPBB Eurofusion Engineering Grant