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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.
Marilyn M. Osterhout
Nuclear Technology | Volume 40 | Number 2 | September 1978 | Pages 159-169
Technical Paper | Tutorial Materials/Design Interaction in Nuclear System / Reactor | doi.org/10.13182/NT78-A26712
Articles are hosted by Taylor and Francis Online.
A water-to-sodium leak detection system was installed at the Experimental Breeder Reactor II in April 1975. The system is designed for early detection of steam generator leaks, using hydrogen meters at the sodium outlets of the evaporators and superheaters. The leak detectors operate by measuring the rate of diffusion of hydrogen from the liquid sodium through a nickel membrane into a dynamic vacuum system. The advantages of this detection system are rapid response time, high sensitivity, stability, and reliability. The system was operated on an experimental basis for the first two years. During this period, data were obtained on detector stability, reliability, maintenance needs, computer interface requirements, calibration, and background hydrogen-level fluctuations. A generic defect in the original detectors was also discovered, requiring redesign of the units. When the new units were installed and proven to be reliable, the system was made fully operational. The data from the hydrogen meters are now used as the primary basis for detection of water-to-sodium leaks.