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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.
T. A. Gabriel, B. L. Bishop, F. W. Wiffen
Nuclear Technology | Volume 38 | Number 3 | May 1978 | Pages 427-433
Technical Paper | Material | doi.org/10.13182/NT78-A32040
Articles are hosted by Taylor and Francis Online.
The displacement per atom and gas production rates have been calculated for a number of alloys and elements using a design neutron spectrum at the first wall of a fusion reactor. These rates can be combined for most alloys to yield the defect production rates, the parameters currently used to extrapolate available irradiation effects data to fusion reactor conditions. Calculated rates of atom displacement and hydrogen generation in stainless steels are relatively insensitive to recent changes in the nuclear data files and to neutron spectrum differences produced by slight reactor design changes. In contrast, the helium production rate is sensitive to these changes and to the exact alloy composition. Composition variation within the specification range for Type 316 stainless steel can produce variations of ±9% in the helium generation rate.