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Conference Spotlight
2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
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Center for Used Fuel Research: Building confidence in storage and transport
Used nuclear fuel storage and transportation have reached a critical juncture.
Dozens of utilities need reliable data on how used nuclear fuel performs in dry storage casks and canisters to extend regulatory licenses at sites across the United States. Likewise, the Department of Energy expects to take ownership of the used nuclear fuel—termed “spent nuclear fuel” in the laws and regulations governing its stewardship—and transfer it to one or more federal staging facilities for management and disposition.
Meanwhile, dozens of reactor companies are testing prototypes of advanced reactors and advanced reactor fuels. Eventually, regulators and industry must also verify the safety and security of storage methods for these advanced fuel types.
To help address these challenges, the DOE established the Center for Used Fuel Research (CUFR) in January 2026 for work related to the long-term storage and transport of used nuclear fuel.
Technical Session|Computational Methods, Artificial Intelligence, and Machine Learning
Saturday, April 6, 2024|1:35–2:55PM EDT|Engineering Services Building Room 122
Session Chair:
Luiz C. Aldeia Machado (Penn State University)
Alternate Chair:
Alexander S. Hauck (Penn State University)
Session Organizer:
Jonathan B. Balog (Penn State University)
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Machine Learning for Time-Series Prediction of the Cryogenic Moderator System in Oak Ridge National Laboratory's Spallation Neutron Source Facility
1:35–1:55PM EDT
Gavin McDuffee (Tennessee Technological Univ.), William Gurecky (Univ. Texas, Austin), Wesley C. Williams (ORNL), Xingang Zhao (ORNL)
Paper
ML-LIBS: Machine Learning-Based Spectra Predictions of Time-Dependent Lithium Emission Spectroscopy Imaging
1:55–2:15PM EDT
Lauren A. Kohler (NCSU), Jason P. Clifford (NCSU), Nursat Karim (NCSU), Sivanandan S. Harilal (PNNL), Elizabeth Kautz (NCSU), Xu Wu (NCSU)
Parameter Importances from Random Forest Machine Learning for Accident Tolerant Fuel Pool Boiling
2:15–2:35PM EDT
Eliot R. Ciuperca (Univ. Wisconsin, Madison), Juliana P. Duarte (Univ. Wisconsin, Madison), Bruno P. Serrao (Univ. Wisconsin, Madison)
A Preliminary Exploration into Using Mixture Density Networks to Compress Data in Monte Carlo Codes
2:35–2:55PM EDT
Eappen S. Nelluvelil (Univ. Colorado, Boulder), Anna Matsekh (LANL), Arvind Mohan (LANL), Mathew A. Cleveland (LANL), Alex Long (LANL)