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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.
R. A. Bari, H. Ludewig, W. T. Pratt, Y. H. Sun
Nuclear Technology | Volume 44 | Number 3 | August 1979 | Pages 357-380
Technical Paper | Reactor | doi.org/10.13182/NT79-A32272
Articles are hosted by Taylor and Francis Online.
An analysis of a slow core meltdown in a liquid-metal fast breeder reactor was performed for the conditions of loss-of-heat-sink following neutronic shutdown. Simple models were developed for the prediction of phase changes and/or relocation of the core materials, including fuel, coolant, cladding, ducts, control rod absorber material (B4C), and plenum gases. The sequence of events was accounted for, and the accident progression was described up to the point of recriticality. The neutronic behavior of the disrupted core was analyzed in r-z geometry with a static transport theory code (TWOTRAN). For most scenarios assessed, the reactor is expected to become recritical, although large ramp rates are not anticipated.