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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.
G. R. Odette, R. L. Simons, W. N. McElroy, D. G. Doran
Nuclear Technology | Volume 32 | Number 2 | February 1977 | Pages 125-141
Technical Paper | Reactor | doi.org/10.13182/NT77-A31718
Articles are hosted by Taylor and Francis Online.
Some limits to appropriate application and the characteristics of uncertainties in damage function analysis (DFA) for breeder reactor spectra were investigated by means of computer experiments. Simulated irradiations in available neutron spectra were evaluated in terms of simple damage models and were used to study (a) the existence of damage functions, (b) the uniqueness of damage function solutions, (c) data error propagation, and (d) procedures for combining various errors to provide a total lower-bound fluence limit for a specified property change. An important factor in achieving a successful DFA was found to be the similarity between the experimental spectra used to generate the damage function and the spectra in which it was applied.