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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.
David H. Lester, Gerald R. Bloom
Nuclear Technology | Volume 23 | Number 3 | September 1974 | Pages 284-289
Technical Paper | Material | doi.org/10.13182/NT74-A15920
Articles are hosted by Taylor and Francis Online.
Use of inlet mixing nozzles to distribute flow in sodium cold trap crystallizers was investigated. Water modeling tests were run in a 100-gal plastic model at water flows of 5.7 to 30 gal/min. During these tests a salt water tracer pulse was introduced into the inlet stream. This tracer was detected by conductivity probes placed in the tank at various angular locations at the top, middle, and bottom. Flow and water temperature in the tank were adjusted to satisfy hydraulic similarity, defined by matching a mixing and flow Reynolds number in the model and sodium component. The results of these tests indicate that modification of the inlet pipe at a 90-deg bend, directed tangentially on the annulus centerline, will produce significant improvements of flow distribution.