A three-dimensional axial fuel relocation framework with discrete element method to support burnup extension

ZH Ma and K Shirvan and YW Wu and GH Su, JOURNAL OF NUCLEAR MATERIALS, 541, 152408 (2020).

DOI: 10.1016/j.jnucmat.2020.152408

Under normal operation, oxide nuclear fuel pellets subjected to high thermomechanical loading and irradiation damage can develop complex crack networks, separating the fuel pellet into a pile of fragments. During a Loss of Coolant Accident (LOCA), these pellet fragments, or fine powder especially when originating from the high-burnup fuel pellet periphery, may relocate axially into the ballooned region of the zircaloy cladding. In this work, the axial relocation process of fuel fragments and powder is modeled based on the three-dimensional Discrete Element Method (DEM) in the Abaqus software. A Voronoi tessellation technique is adopted to generate random convex polyhedrons in order to mimic a coarse fragmentation pattern. A parametric study in terms of the mean fragment size from 1.3 mm to 3.0 mm was conducted to investigate its effect on the axial profile of fuel mass fraction and filling ratio after fuel relocation. Then a sensitivity study of the randomness in fragmentation on axial fuel relocation was performed. For high-burnup fuels, in order to characterize the porous High Burnup Structure (HBS), the pellet rim was discretized into separate spherical shape particles. The effect of powder fraction on fuel relocation was demonstrated, and the results indicated that higher powder fraction can significantly increase the fuel mass fraction and filling ratio level in the ballooned region, which showed qualitative agreement with experimental observations. Finally, the verification against a one-dimensional theoretical relocation model was conducted to verify the robustness and high fidelity features of the DEM model in simulating axial fuel relocation under LOCA. The modeling approach serves as a mechanistic framework to support future burnup extensions for the oxide nuclear fuel. (C) 2020 Elsevier B.V. All rights reserved.

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