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DOE OSTI · 3013836

An Integrated ML/AI Framework for Digitizing, Structuring and Searching DOE U-TRU-Fuels Data with Gap Analysis of Non-DOE Records

Carbonneau, Leala [Idaho National Laboratory (INL), Idaho Falls, ID (United States)]·Hubbard, Victor [Univ. of Wisconsin, Madison, WI (United States)]·D'Souza, Karen [Idaho National Laboratory (INL), Idaho Falls, ID (United States)]·Jensen, Bradlee Hope [Idaho National Laboratory (INL), Idaho Falls, ID (United States)]·Otani, Courtney [Idaho National Laboratory (INL), Idaho Falls, ID (United States)] (ORCID:0000000204125818)·Anderson, Matthew William [Idaho National Laboratory (INL), Idaho Falls, ID (United States)]·Jensen, Colby J. [Idaho National Laboratory (INL), Idaho Falls, ID (United States)] (ORCID:0000000189257758)·Yao, Tiankai [Idaho National Laboratory (INL), Idaho Falls, ID (United States)] (ORCID:0000000183307638)·Pavey, Todd A. [Idaho National Laboratory (INL), Idaho Falls, ID (United States)]
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Abstract

The U.S. Department of Energy (DOE) Advanced Fuels Campaign (AFC) is advancing transmutation fuel technologies to reduce long-lived radioactive waste by converting minor actinides into shorter-lived or stable elements through irradiation in sodium-cooled fast reactors. Key experiments such as AFC-1, AFC-2, FUels for the transmutation of Trans-URanium elements In phéniX (FUTURIX)-Fortes Teneurs en Actinides (FTA), and Experimental Breeder Reactor-II (EBR-II) X501 have provided fuel fabrication, irradiation, and performance data on various transuranic-bearing fuel forms. This report documents the creation of an artificial-intelligence assisted database, which has consolidated all DOE-owned data related to Transuranic (TRU)-bearing fuel experiments and stored across it across both the Idaho National Laboratory (INL) Nuclear Data Management and Analysis System and the INL high performance computing (HPC) infrastructure. A dedicated webpage, hosted on the INL HPC system, has been developed to support role-based access and data interaction. The database architecture allows researchers to navigate large, heterogeneous archives with far greater speed and accuracy than manual search and lays the foundation for future expansion into multimodal nuclear materials analysis environments. The database represents a major step towards a nationally integrated fuels database utilizing artificial intelligence tools.

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11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS97 MATHEMATICS AND COMPUTINGAIData gapsHigh performance computingTRU

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Carbonneau, Leala [Idaho National Laboratory (INL), Idaho Falls, ID (United States)], Hubbard, Victor [Univ. of Wisconsin, Madison, WI (United States)], D'Souza, Karen [Idaho National Laboratory (INL), Idaho Falls, ID (United States)], Jensen, Bradlee Hope [Idaho National Laboratory (INL), Idaho Falls, ID (United States)], Otani, Courtney [Idaho National Laboratory (INL), Idaho Falls, ID (United States)] (ORCID:0000000204125818), Anderson, Matthew William [Idaho National Laboratory (INL), Idaho Falls, ID (United States)], Jensen, Colby J. [Idaho National Laboratory (INL), Idaho Falls, ID (United States)] (ORCID:0000000189257758), Yao, Tiankai [Idaho National Laboratory (INL), Idaho Falls, ID (United States)] (ORCID:0000000183307638), Pavey, Todd A. [Idaho National Laboratory (INL), Idaho Falls, ID (United States)]. 2025-12-23. An Integrated ML/AI Framework for Digitizing, Structuring and Searching DOE U-TRU-Fuels Data with Gap Analysis of Non-DOE Records. https://doi.org/10.2172/3013836

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