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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.
Karl Hornyik, John E. Grund
Nuclear Technology | Volume 23 | Number 1 | July 1974 | Pages 28-37
Technical Paper | Reactor Siting | doi.org/10.13182/NT74-A31431
Articles are hosted by Taylor and Francis Online.
Analytic models have been developed and applied by the authors to investigate the hazards to a nuclear power plant from air traffic. Separate models applying to collisions with and crashes into the plant, respectively, employ concepts of traffic density and crash site distributions. These, along with the more conventional concepts of accident rates and effective plant area, are used to determine the annual strike probability of aircraft into safety-related plant structures. Although the models are quite general, they are applied to two specific flight patterns of common interest. The probability maps which are obtained may be used to resolve siting problems in a quantitative manner.