Spatial variability in the coefficient of thermal expansion induces pre-service stresses in computer models of virgin Gilsocarbon bricks

José David Arregui-Mena, Lee Margetts, D. V. Griffiths, Louise Lever, Graham Hall, Paul M. Mummery

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Abstract In this paper, the authors test the hypothesis that tiny spatial variations in material properties may lead to significant pre-service stresses in virgin graphite bricks. To do this, they have customised ParaFEM, an open source parallel finite element package, adding support for stochastic thermo-mechanical analysis using the Monte Carlo Simulation method. For an Advanced Gas-cooled Reactor brick, three heating cases have been examined: a uniform temperature change; a uniform temperature gradient applied through the thickness of the brick and a simulated temperature profile from an operating reactor. Results are compared for mean and stochastic properties. These show that, for the proof-of-concept analyses carried out, the pre-service von Mises stress is around twenty times higher when spatial variability of material properties is introduced. The paper demonstrates that thermal gradients coupled with material incompatibilities may be important in the generation of stress in nuclear graphite reactor bricks. Tiny spatial variations in coefficient of thermal expansion (CTE) and Young's modulus can lead to the presence of thermal stresses in bricks that are free to expand.

Original languageEnglish
Article number49140
Pages (from-to)793-804
Number of pages12
JournalJournal of Nuclear Materials
Volume465
DOIs
StatePublished - Jul 25 2015
Externally publishedYes

Funding

The authors wish to thank the support and resources provided by the Mexican National Science and Technology Council (CONACYT) and the Secretaría de Educación Pública (SEP). This work made use of the facilities of N8 HPC provided and funded by the N8 consortium and EPSRC (Grant No. EP/K000225/1 ). The Centre is co-ordinated by the Universities of Leeds and Manchester, UK. The authors gratefully acknowledge the STFC Batteries grant awarded for the project “Random FEM for Energy Applications” which funded a research visit to the Colorado School of Mines.

Keywords

  • Finite element method
  • Gilsocarbon
  • Modelling
  • Monte Carlo Simulation
  • Nuclear graphite

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