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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Latest News
NNSA awards BWXT $1.5B defense fuels contract
The Department of Energy’s National Nuclear Security Administration has awarded BWX Technologies a contract valued at $1.5 billion to build a Domestic Uranium Enrichment Centrifuge Experiment (DUECE) pilot plant in Tennessee in support of the administration’s efforts to build out a domestic supply of unobligated enriched uranium for defense-related nuclear fuel.
Andreas Ikonomopoulos, Miltiadis Alamaniotis, Stylianos Chatzidakis, Lefteri H. Tsoukalas
Nuclear Technology | Volume 182 | Number 1 | April 2013 | Pages 1-12
Technical Paper | Fission Reactors | doi.org/10.13182/NT13-A15821
Articles are hosted by Taylor and Francis Online.
A novel machine learning approach for nuclear power plant modeling and state identification is presented together with its test results using data from the Loss-of-Fluid Test experimental facility. The approach exploits Gaussian processes whose principal function is to tackle the temporal problem of forecasting the actual system state in the varying environment of a nuclear reactor facility that undergoes successive overcooling transients. The approach fuses independent Gaussian process expert predictions to provide a single recommendation to the plant operators in a form that is suitable to appear on a decision support system screen. A variety of test cases are developed to explore the validity and relevance of Gaussian processes. The proposed implementation is examined with various predictor variables under different conditions, and the results obtained are in accordance with model expectations.