Abstract
The pursuit of enhanced nuclear safety has spurred the development of accident-tolerant cladding (ATC) materials for light water reactors (LWRs). This study investigates the potential of repurposing these ATCs in advanced reactor designs, aiming to expedite material development and reduce costs. The research employs a multi-physics approach, encompassing neutronics, heat transfer, thermodynamics, and structural mechanics, to evaluate four candidate materials (Haynes 230, Zircaloy-4, FeCrAl, and SiC–SiC) within the context of a high-temperature, sodium-cooled microreactor, exemplified by the Kilopower design. While neutronic simulations revealed negligible power profile variations among the materials, finite element analyses highlighted the superior thermal stability of SiC–SiC and the favorable stress resistance of Haynes 230. The high-temperature environment significantly impacted material performance, particularly for Zircaloy-4 and FeCrAl, while SiC–SiC's inherent properties limited its ability to withstand stress loads. Additionally, AI-driven uncertainty quantification and sensitivity analysis were conducted to assess the influence of material property variations on maximum hoop stress. The findings underscore the need for further research into high-temperature material properties to facilitate broader applicability of existing materials to advanced reactors. Haynes 230 is identified as the most promising candidate based on the evaluated criteria.
Recommended Citation
A. Foutch et al., "AI-driven Uncertainty Quantification & Multi-physics Approach to Evaluate Cladding Materials in a Microreactor," Progress in Nuclear Energy, vol. 186, article no. 105793, Elsevier, Aug 2025.
The definitive version is available at https://doi.org/10.1016/j.pnucene.2025.105793
Department(s)
Nuclear Engineering and Radiation Science
Publication Status
Open Access
Keywords and Phrases
Microreactor; Uncertainty
International Standard Serial Number (ISSN)
0149-1970
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Elsevier, All rights reserved.
Publication Date
01 Aug 2025
