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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.
H. Brücher
Nuclear Technology | Volume 39 | Number 1 | June 1978 | Pages 25-29
Nuclear Safety Analysis | Energy Modeling and Forecasting / Radioactive Waste | doi.org/10.13182/NT78-A17004
Articles are hosted by Taylor and Francis Online.
An analysis has been made dealing with the evaluation of risk of a high-level waste solidification plant. Fault-tree methodology was used to identify all possible accidents and to evaluate their probability of occurrence. The analysis shows that with regard to risk, the most important accidents occur during off-gas cleaning. Furthermore, the routine risk is of the same order of magnitude or greater than the most important accident risks.