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

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

doi:10.1016/j.jnucmat.2015.05.058

Cited by 19 publications

(11 citation statements)

References 17 publications

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“…Unfortunately, by only using the mean value of the material properties all the spatial and statistical information 3 such as standard deviation and probability distribution are lost. A previous study that includes spatial material variability into FEM has demonstrated that heterogeneity of material properties in AGR reactors can lead to stress concentrations [10]. Moreover, recent studies [11][12][13] have included or analysed the heterogeneity of material properties as they relate to the mechanical properties of graphite.…”

Section: Part Of the Routine Assessments And Predictions Of The Lifetmentioning

confidence: 99%

Characterisation of the spatial variability of material properties of Gilsocarbon and NBG-18 using random fields

Arregui-Mena

Edmondson

Margetts

et al. 2018

Journal of Nuclear Materials

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☆ This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Characterisation of the spatial variability of material properties of Gilsocarbon and NBG-18 using random fields ☆

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Section: Part Of the Routine Assessments And Predictions Of The Lifetmentioning

confidence: 99%

Characterisation of the spatial variability of material properties of Gilsocarbon and NBG-18 using random fields

Arregui-Mena

Edmondson

Margetts

et al. 2018

Journal of Nuclear Materials

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“…Previously ParaFEM has been used in large scale simulations in nuclear fusion research [20], [21] and bio-mechanics [22], [23].…”

Section: The Coarray/mpi Frameworkmentioning

confidence: 99%

Multi-scale CAFE Framework for Simulating Fracture in Heterogeneous Materials Implemented in Fortran Co-arrays and MPI

Shterenlikht

Margetts²,

Arregui-Mena³

et al. 2016

2016 PGAS Applications Workshop (PAW)

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“…Another motivation for this work is that the material properties obtained can be used to calibrate stochastic finite element models to test the effect of spatial material variability on the structural integrity of graphite components. A study on the effects of material variability in nuclear graphite can be found in reference [7]. For more information about stochastic finite element modelling the reader is referred to [8].…”

Section: Introductionmentioning

confidence: 99%

Spatial variability in the mechanical properties of Gilsocarbon

Arregui-Mena

Bodel

Worth

et al. 2016

Carbon

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The objective of this study is to investigate whether there is significant spatial variability in the mechanical properties of Gilsocarbon nuclear graphite at different sections of the billet; specifically the dynamic Poisson's ratio, dynamic shear modulus, dynamic Young's modulus and density. Similar studies have been done, usually in the context of manufacturing, to assess the quality of graphite components for nuclear reactors. In this new study, the measurements have been carried out at a much higher spatial resolution than previously. A Torness/Heysham B billet was machined into cubes so that measurements could be made across the circumference and height of the billet. ASTM standards were followed to assess the measurements of the samples. The spatial variability of material properties is described and analysed statistically. The study shows that material variability is present at different heights and circumferential locations of the billet. This discovery will have a significant impact on the structural integrity and through life performance predictions made in industry; both in current and future nuclear reactors. The computer modelling of graphite components may predict different outcomes to standard analyses (that use mean values) if this variability is incorporated into the analysis workflow; specifically through stochastic modelling.

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

Cited by 19 publications

References 17 publications

Characterisation of the spatial variability of material properties of Gilsocarbon and NBG-18 using random fields

Characterisation of the spatial variability of material properties of Gilsocarbon and NBG-18 using random fields

Multi-scale CAFE Framework for Simulating Fracture in Heterogeneous Materials Implemented in Fortran Co-arrays and MPI

Spatial variability in the mechanical properties of Gilsocarbon

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