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

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.

[1]  S. Majumdar,et al.  Constitutive modeling and finite element procedure development for stress analysis of prismatic high temperature gas cooled reactor graphite core components , 2013 .

[2]  D. V. Griffiths,et al.  Risk Assessment in Geotechnical Engineering , 2008 .

[3]  Lee Margetts,et al.  Three-dimensional cellular automata modelling of cleavage propagation across crystal boundaries in polycrystalline microstructures , 2015, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[4]  Arthur Cyril Davies The science and practice of welding , 1993 .

[5]  Barry Marsden,et al.  The development of a stress analysis code for nuclear graphite components in gas-cooled reactors , 2006 .

[6]  Barry Marsden,et al.  The microstructural modelling of nuclear grade graphite , 2004 .

[7]  H. Millwater,et al.  Random field assessment of nanoscopic inhomogeneity of bone. , 2010, Bone.

[8]  Chenfeng Li,et al.  Failure probability study of HTR graphite component using microstructure-based model , 2012 .

[9]  D. V. Griffiths,et al.  Programming the finite element method , 1982 .

[10]  D. V. Griffiths,et al.  SEEPAGE BENEATH WATER RETAINING STRUCTURES FOUNDED ON SPATIALLY RANDOM SOIL , 1993 .

[11]  S. Lamont,et al.  Fundamental principles of structural behaviour under thermal effects , 2001 .

[12]  B. Marsden,et al.  Graphite in Gas-Cooled Reactors , 2015 .

[13]  E. Eason,et al.  A model of Young’s modulus for Gilsocarbon graphites irradiated in oxidising environments , 2013 .

[14]  Lee Margetts,et al.  Fortran 2008 coarrays , 2015, FORF.

[15]  Stephen McArthur,et al.  Knowledge-directed characterization of nuclear power plant reactor core parameters , 2011 .

[16]  S. Yoda,et al.  An approximate relation between Young's modulus and thermal expansion coefficient for nuclear-grade graphite , 1983 .

[17]  E. Eason,et al.  Models of Coefficient of Thermal Expansion (CTE) for Gilsocarbon Graphites Irradiated in Inert and Oxidising Environments , 2013 .

[18]  David T. Rohrbaugh,et al.  Baseline Graphite Characterization: First Billet , 2010 .

[19]  B. Marsden,et al.  Constitutive material model for the prediction of stresses in irradiated anisotropic graphite components , 2008 .

[20]  K. Huebner The finite element method for engineers , 1975 .

[21]  Gordon A. Fenton,et al.  Random Field Generation and the Local Average Subdivision Method , 2007 .

[22]  Lee Margetts,et al.  The convergence variability of parallel iterative solvers , 2006 .

[23]  T. Marrow,et al.  The microstructure of nuclear graphite binders , 2008 .