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Argonne: Where AI research meets education and training
Last September, in the Chicago suburb of Lemont, Ill., Argonne National Laboratory hosted its first AI STEM Education Summit. More than 180 educators from high schools, community colleges, and universities; STEM administrators; and experts in various disciplines convened at “One Ecosystem, Many Pathways–Building an AI-Ready STEM Workforce” to discuss how artificial intelligence is reshaping STEM-related industries, including the implications for the nuclear engineering classroom and workforce.
M. A. Gaafer, L. Mango, + F. V. Orestano,†, F. Pistella
Nuclear Technology | Volume 27 | Number 2 | October 1975 | Pages 187-206
Technical Paper | Reactor | doi.org/10.13182/NT75-A24286
Articles are hosted by Taylor and Francis Online.
Methods have been formulated to treat the rod cluster control for present-generation presurized water reactors within the computational codes available at Comitato Nazionale per l’Energia Nucleare (CNEN) for light water reactors. The reliability of these procedures has been verified by comparing the calculated results with the most significant experimental data available from measurements performed by the Centre d’Étude de l’Énergie Nucléaire-Studiecentrum Voor Kernenergie (Belgian Plutonium Recycling Program), Babcock & Wilcox (Lumped Burnable Poison Program), Westinghouse, and CNEN (Italian Nuclear Ship Propulsion Program). Reactivity and power distributions have been evaluated for a wide set of experimental configurations including several types of absorbing rods (e.g., B4C, Pyrex, and Ag-In-Cd alloy) with different radii in different lattices made of various fuel materials (e.g., UO2, PuO2, and UO2/PuO2).