Using porous random fields to predict the elastic modulus of unoxidized and oxidized superfine graphite

José David Arregui-Mena; D. V. Griffiths; Robert N. Worth; Christa E. Torrence; Aaron Selby; Cristian Contescu; Nidia Gallego; Philip D. Edmondson; Paul M. Mummery; Lee Margetts

doi:10.1016/j.matdes.2022.110840

Using porous random fields to predict the elastic modulus of unoxidized and oxidized superfine graphite

José David Arregui-Mena, D. V. Griffiths, Robert N. Worth, Christa E. Torrence, Aaron Selby, Cristian Contescu, Nidia Gallego, Philip D. Edmondson, Paul M. Mummery, Lee Margetts

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Nuclear graphite is a candidate material for Generation IV nuclear power plants. Porous materials such as graphite can contain complex networks of pores that influence the material's mechanical and irradiation response. A methodology known as the random finite element method (RFEM) was adapted to create synthetic microstructures and predict the influence of porosity on the elastic properties of graphite during oxidation. RFEM combines random field theory and the finite element method in a Monte Carlo framework to estimate the mechanical response of a given grade of graphite. In this research, the random fields were verified through experimental characterization to predict the elastic response of three nuclear graphite grades, ETU-10, IG-110, and 2114. Finite element models (FEM) were generated using segmentations of x-ray computed tomography (XCT) data known as image-based models (IBMs) to validate and compare with the RFEM results and better understand the effects of uniform oxidation in these graphite grades. The RFEM predictions appear to correlate well with the experimental values of the measured Young's modulus of the three graphite grades and display the same trends as IBMs.

Original language	English
Article number	110840
Journal	Materials and Design
Volume	220
DOIs	https://doi.org/10.1016/j.matdes.2022.110840
State	Published - Aug 2022

Funding

This work was supported by the U. S. Department of Energy, Office of Nuclear Energy, under the Advanced Reactor Technologies (ART) program. This work was also supported by the Office of Nuclear Energy under DOE Idaho Operations Office Contract DE-AC07- 051D14517 as part of a Nuclear Science User Facilities experiment. A portion of this research used the resources of the Low Activation Materials Development and Analysis Laboratory (LAMDA), a DOE Office of Science research facility operated by the Oak Ridge National Laboratory (ORNL). Oak Ridge National Laboratory is managed by UT-Battelle under contract DE-AC05-00OR22725. Lee Margetts was supported by EPSRC grants EP/N026136/1 and EP/T026782/1 awarded in the UK. The authors would like to thank Hughie Spinoza for his valuable comments and discussion. 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).

Funders	Funder number
Advanced Reactor Technologies
U.S. Department of Energy	DE-AC07- 051D14517
Office of Nuclear Energy
Oak Ridge National Laboratory
UT-Battelle	DE-AC05-00OR22725
Engineering and Physical Sciences Research Council	EP/N026136/1, EP/T026782/1

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title = "Using porous random fields to predict the elastic modulus of unoxidized and oxidized superfine graphite",

abstract = "Nuclear graphite is a candidate material for Generation IV nuclear power plants. Porous materials such as graphite can contain complex networks of pores that influence the material's mechanical and irradiation response. A methodology known as the random finite element method (RFEM) was adapted to create synthetic microstructures and predict the influence of porosity on the elastic properties of graphite during oxidation. RFEM combines random field theory and the finite element method in a Monte Carlo framework to estimate the mechanical response of a given grade of graphite. In this research, the random fields were verified through experimental characterization to predict the elastic response of three nuclear graphite grades, ETU-10, IG-110, and 2114. Finite element models (FEM) were generated using segmentations of x-ray computed tomography (XCT) data known as image-based models (IBMs) to validate and compare with the RFEM results and better understand the effects of uniform oxidation in these graphite grades. The RFEM predictions appear to correlate well with the experimental values of the measured Young's modulus of the three graphite grades and display the same trends as IBMs.",

author = "Arregui-Mena, {Jos{\'e} David} and Griffiths, {D. V.} and Worth, {Robert N.} and Torrence, {Christa E.} and Aaron Selby and Cristian Contescu and Nidia Gallego and Edmondson, {Philip D.} and Mummery, {Paul M.} and Lee Margetts",

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AU - Griffiths, D. V.

AU - Worth, Robert N.

AU - Torrence, Christa E.

AU - Selby, Aaron

AU - Contescu, Cristian

AU - Gallego, Nidia

AU - Edmondson, Philip D.

AU - Mummery, Paul M.

AU - Margetts, Lee

PY - 2022/8

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N2 - Nuclear graphite is a candidate material for Generation IV nuclear power plants. Porous materials such as graphite can contain complex networks of pores that influence the material's mechanical and irradiation response. A methodology known as the random finite element method (RFEM) was adapted to create synthetic microstructures and predict the influence of porosity on the elastic properties of graphite during oxidation. RFEM combines random field theory and the finite element method in a Monte Carlo framework to estimate the mechanical response of a given grade of graphite. In this research, the random fields were verified through experimental characterization to predict the elastic response of three nuclear graphite grades, ETU-10, IG-110, and 2114. Finite element models (FEM) were generated using segmentations of x-ray computed tomography (XCT) data known as image-based models (IBMs) to validate and compare with the RFEM results and better understand the effects of uniform oxidation in these graphite grades. The RFEM predictions appear to correlate well with the experimental values of the measured Young's modulus of the three graphite grades and display the same trends as IBMs.

AB - Nuclear graphite is a candidate material for Generation IV nuclear power plants. Porous materials such as graphite can contain complex networks of pores that influence the material's mechanical and irradiation response. A methodology known as the random finite element method (RFEM) was adapted to create synthetic microstructures and predict the influence of porosity on the elastic properties of graphite during oxidation. RFEM combines random field theory and the finite element method in a Monte Carlo framework to estimate the mechanical response of a given grade of graphite. In this research, the random fields were verified through experimental characterization to predict the elastic response of three nuclear graphite grades, ETU-10, IG-110, and 2114. Finite element models (FEM) were generated using segmentations of x-ray computed tomography (XCT) data known as image-based models (IBMs) to validate and compare with the RFEM results and better understand the effects of uniform oxidation in these graphite grades. The RFEM predictions appear to correlate well with the experimental values of the measured Young's modulus of the three graphite grades and display the same trends as IBMs.

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Using porous random fields to predict the elastic modulus of unoxidized and oxidized superfine graphite

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