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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
A wave of new U.S.-U.K. deals ahead of Trump’s state visit
President Trump will arrive in the United Kingdom this week for a state visit that promises to include the usual pomp and ceremony alongside the signing of a landmark new agreement on U.S.-U.K. nuclear collaboration.
Patrick J. O’Neal, Sean P. Martinson, Sunil S. Chirayath
Nuclear Science and Engineering | Volume 198 | Number 9 | September 2024 | Pages 1817-1829
Research Article | doi.org/10.1080/00295639.2023.2271711
Articles are hosted by Taylor and Francis Online.
When the foundation of a method is simulated data, it is paramount that the method is validated with data from physical samples when possible. This study presents the results of validating a recently developed nuclear forensics methodology with a new low-burnup plutonium sample, chemically separated from low-enriched uranium irradiated in thermal neutron flux. The nuclear forensics methodology uses machine learning models to discriminate the reactor type of origin, fuel burnup, and time since irradiation (TSI) of chemically separated plutonium samples. The machine learning models use intra-elemental isotope ratios of cesium, samarium, europium, and plutonium as features; the isotopic ratio data for training the models were generated through fuel burnup simulations of various nuclear reactor types. The methodology predicted the reactor type and fuel burnup of the plutonium sample successfully. Initial difficulties to predict the TSI were resolved with the inclusion of a new intra-elemental isotope ratio of cerium.