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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.
Naomichi Kanegae, Koh Hashiguchi, Ichiro Ikemoto, Masao Hori
Nuclear Technology | Volume 40 | Number 3 | October 1978 | Pages 261-277
Technical Paper | Reactor | doi.org/10.13182/NT78-A26724
Articles are hosted by Taylor and Francis Online.
The wastage effects of a sodium-water reaction resulting from a small leak in a liquid-metal fast breeder reactor steam generator were investigated. These experiments were conducted at low steam injection rates, ranging from 0.07 to 13.8 g/s, with the following test conditions: sodium temperature 480°C, sodium velocity 0.24 m/s, and target material Cr—1 Mo steel. Employed were nozzle diameters (D) from 0.2 to 1.5 mm, nozzle-to-target distances (L) from 5 to 100 mm, and L/D ratios from 7.14 to 400. An empirical equation of wastage rate of Cr— 1 Mo steel was obtained, including parameters of sodium temperature, steam injection rate, and nozzle-to-target distance. The depth curves and the widths of the area affected by wastage were examined. These test results were applied to the safety considerations for the prototype steam generators in Japan.