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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.
H. G. Stoll, R. A. Axford
Nuclear Technology | Volume 21 | Number 2 | February 1974 | Pages 85-98
Technical Paper | Reactor | doi.org/10.13182/NT74-A31365
Articles are hosted by Taylor and Francis Online.
A utility system operational planning model of a Liquid Metal Fast Breeder Reactor is developed together with an in-core optimization algorithm to minimize the fuel cost of each cycle. The optimization algorithm determines the batch size and position of two refueling enrichments, the shuffling of partially irradiated fuel, and the fuel to be discharged such that the utility system energy and reactor plant maintenance requirements are met. The in-core model includes a description of the fuel depletion and discrete fuel assembly configuration.