Asymptotic expansion homogenization for multiscale nuclear fuel analysis

J. D. Hales, M. R. Tonks, K. Chockalingam, D. M. Perez, S. R. Novascone, B. W. Spencer, R. L. Williamson

    Research output: Contribution to journalArticlepeer-review

    41 Scopus citations


    Engineering scale nuclear fuel performance simulations can benefit by utilizing high-fidelity models running at a lower length scale. Lower length-scale models provide a detailed view of the material behavior that is used to determine the average material response at the macroscale. These lower length-scale calculations may provide insight into material behavior where experimental data is sparse or nonexistent. This multiscale approach is especially useful in the nuclear field, since irradiation experiments are difficult and expensive to conduct. The lower length-scale models complement the experiments by influencing the types of experiments required and by reducing the total number of experiments needed. This multiscale modeling approach is a central motivation in the development of the BISON and MARMOT fuel performance codes. These codes seek to provide more accurate and predictive solutions for nuclear fuel behavior. One critical aspect of multiscale modeling is the ability to extract the relevant information from the lower length-scale simulations. One approach, the asymptotic expansion homogenization (AEH) technique, has proven to be an effective method for determining homogenized material parameters. The AEH technique prescribes a system of equations to solve at the mesoscale that are used to compute homogenized material constants for use at the engineering scale. In this work, we employ AEH to explore the effect of evolving microstructural thermal conductivity and elastic constants on nuclear fuel performance. We show that the AEH approach fits cleanly into the BISON and MARMOT codes and provides a natural, multidimensional homogenization capability.

    Original languageEnglish (US)
    Pages (from-to)290-297
    Number of pages8
    JournalComputational Materials Science
    StatePublished - Mar 2015

    All Science Journal Classification (ASJC) codes

    • General Computer Science
    • General Chemistry
    • General Materials Science
    • Mechanics of Materials
    • General Physics and Astronomy
    • Computational Mathematics


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