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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.
W. F. Naughton, M. J. Cenko, S. H. Levine, W. F. Witzig
Nuclear Technology | Volume 23 | Number 3 | September 1974 | Pages 256-272
Technical Paper | Fuel | doi.org/10.13182/NT74-A15918
Articles are hosted by Taylor and Francis Online.
A core management program has been effected for TRIGA reactors (TRICOM) which utilizes three basic types of information: (a) keff as a function of burnup, (b) relative changes in power fractions of fuel elements as a function of core burnup, and (c) reactivity worth curves for fissile isotopes and neutron absorbers. TRICOM has been programmed for an IBM system/360 using the FORTRAN IV language. Experimental measurements have been made with 8.5 wt% uranium and a mixture of 8.5 and 12 wt% uranium-fueled cores, and the results have been compared with those calculated by TRICOM. The analytical and experimental results compare favorably in all cases, particularly when some of the experimentally measured parameters are substituted for those derived theoretically. A significant result of this study program has been the development of an improved refueling scheme for The Pennsylvania State University’s Breazeale Nuclear Reactor which replaces depleted 8.5 wt% fuel with 12 wt% uranium fuel.