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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.
Michio Murase, Isao Sumida, Koichi Kotani, Hajime Yamamoto
Nuclear Technology | Volume 37 | Number 2 | February 1978 | Pages 138-147
Technical Paper | Plant Water Chemistry / Material | doi.org/10.13182/NT78-A31981
Articles are hosted by Taylor and Francis Online.
An impurity interaction code for a mesh-packed cold trap was developed, and the properties of the packed trap, such as the trapping efficiency and capacity, were calculated using this code. As a result, the trapping efficiency and capacity are greatly affected by the packing ratio and the wire diameter of the mesh packing. Precipitation of impurity is promoted at the entrance to the mesh packing. This facilitating effect hastens flow blockage and decreases the capacity. Moreover, the capacity decreases with increase in the efficiency.