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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.
Hideaki Nishihara
Nuclear Technology | Volume 23 | Number 3 | September 1974 | Pages 222-232
Technical Paper | Reactor | doi.org/10.13182/NT74-A15915
Articles are hosted by Taylor and Francis Online.
Unambiguous and early detection of anomalous coolant boiling in nonboiling liquid-cooled reactors, especially in liquid-metal fast breeder reactors, is of great significance from the viewpoint of reactor safety. Acoustic detection of boiling is promising but is often hampered by existing background noise. Cross-correlating noise signals may alleviate this problem and also locate the anomaly. The characteristics of the cross-correlation functions of acoustic boiling noise were investigated experimentally. A pair of hydrophones detected local boiling of water in a container tank. The nucleate local boiling was generated in the tank by electrically heating a small segment of simulated fuel rod. Measurements were taken in pure water as well as in a heterogeneous medium with simulated rod bundles. In general, acoustic boiling noise signals with duration times of <50 msec successfully located the boiling site from the observed peak shifts of the cross-correlation functions when the signals were used in the off-resonance frequency region.