Research Update

Automated parametric design optimisation for fusion components  

J. Shimwell

This work was funded by the RCUK Energy Programme
[Grant number EP/P012450/1]

Objective

To perform automated parametric multiphysics analysis of breeder blanket designs with an aim of optimising the design.

1

Selection of design parameters

Parametric CAD construction

Neutronics simulation for TBR and EM

Converstion to unstructured mesh

Neutronics simulation for volumetric heating

Converstion to engineering mesh

Simulations to find stress and temperature

Evaluate design

    Converstion to      CGS

Interpolate performance    & design sensitivity

Automated

workflow

2

Serpent II

Nuclear data

Containerization

Blanket

design tool

Computing techniques

Cloud computing

Visualisation Web app

Database

3

React.js

 Parametric design

Select a design from the 4 EU blanket modules

Select design parameters to vary

  • First wall thickness
  • Poloidal height of PbLL
  • Lithium 6 enrichment
  • Pebble packing fraction

               etc

4

 Parametric design

4

Sampling techniques

5

Interpolation confidence

6

Interpolation confidence

7

 Results

8

Due to the use of CAD throughout the project the same model can be used to obtain TBR, volumetric heating, temperature and stress.

9

 Volumetric heating simulations

10

 Temperature simulations

  • Volumetric heating obtained with unstructured mesh simulations in DAGMC, MCNP 6, Serpent 2
  • Meshing and boundary condition identification in Trelis / Cubit
  • Temperature dependent material properties assigned using Python
  • Heat transfer performed in Fenics

10

Stress simulations

Automated stress simulations are still required :-(

11

Software projects

  • Generates 3D models of breeder blankets
  • UKAEA github Version control
  • Docker image on UKAEA Docker Hub
  • Continuous integration with Circle CI
  • Readme.md file with documentation
  • Pip install available
  • Produces material cards for simulations
  • UKAEA github Version control
  • Continuous integration with Travis CI
  • Readme.md file with documentation
  • Pip install available
  • test suite using pytest

Automated Portable

Parametric

Scalable

Neutronics

Figure shows tritium production within EU DEMO

Conclusion

12

Research update June 2018

By Jonathan Shimwell

Research update June 2018

For HCLL meeting

  • 442