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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.
R. C. Lloyd, S. W. Heaberlin, E. D. Clayton, R. D. Carter
Nuclear Technology | Volume 42 | Number 1 | January 1979 | Pages 13-21
Technical Paper | Reactor | doi.org/10.13182/NT79-A32158
Articles are hosted by Taylor and Francis Online.
A study was made of 100 violations of criticality safety specifications reported over a 10-yr period in the operations of fuel reprocessing plants. The seriousness of each rule violation was evaluated by assigning it a severity index value. The underlying causes, or reasons, for the violations were identified. A criticality event tree was constructed using the parameters, causes, and reasons found in the analysis of the infractions. The event tree provides a means for visualizing the paths to an accidental criticality. Some 65% of the violations were caused by misinterpretation on the part of the operator, being attributed to a lack of clarity in the specification and insufficient training; 33% were attributed to lack of care, whereas only 2% were caused by mechanical failure. A fault tree was constructed by assembling the events that could contribute to an accident. With suitable data on the probabilities of contributing events, the probability of the accident’s occurrence can be forecast. Estimated probabilities for criticality were made, based on the limited data available, that in this case indicate a minimum time span of 244 yr of plant operation per accident ranging up to ∼3000 yr subject to the various underlying assumptions made. Some general suggestions for improvement are formulated based on the cases studied. Although conclusions for other plants may differ in detail, the general method of analysis and the fault tree logic should prove applicable.