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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.
Kenneth A. Solomon, Robert C. Erdmann, David Okrent
Nuclear Technology | Volume 25 | Number 1 | January 1975 | Pages 68-71
Technical Paper | Reactor Siting | doi.org/10.13182/NT75-A24349
Articles are hosted by Taylor and Francis Online.
A method and statistics given by V. E. Blake have been employed to estimate the probability per year that a nuclear reactor could be seriously damaged by a meteorite strike. The probability per year that a target area of 104 ft2 will be struck by a meteorite weighing more than a pound is estimated to be 4.3 × 10−9 per reactor year. However, only a fraction of these meteorites, corresponding to weights exceeding 100 lb (0.05 ton), is very likely to seriously damage or destroy the reactor to the point of an uncontrolled release of fission products. For a vulnerable target area of 104 ft2, this probability is estimated to be 7× 10−10 per reactor year. If the vulnerable target area per reactor were 102 ft2, the probability of serious damage is estimated to be 7 × 10−9 per reactor year. The probability that a coastal plant will suffer serious damage arising from either a direct hit of a meteorite or from a tidal wave induced by a meteorite is estimated to be of the order of 9 × 10−10 per reactor year for a target area of 104ft2.