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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.
Fumio Murata, Kanji Kato, Fumio Tomizawa, Isao Sumida
Nuclear Technology | Volume 44 | Number 1 | June 1979 | Pages 104-117
Technical Paper | Reactor | doi.org/10.13182/NT79-A32244
Articles are hosted by Taylor and Francis Online.
A new diagnosis system for a boiling water reactor has been developed. In this diagnosis system, a block-monitoring index, obtained through the use of a dynamic model of a nuclear power plant, is used to indicate changes in the operating characteristics of plant equipment. The performance of this diagnosis system using the block-monitoring index was evaluated using actual plant data and was shown to be a feasible method for detecting and identifying anomalies in the plant at an early stage. Diagnosis takes <1 s, which means that the system has on-line and realtime diagnosis capabilities. It is expected that this system will help in improving the safety and availability of nuclear power plants.