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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.
D. J. Pellarin, J. L. Jarriel
Nuclear Technology | Volume 42 | Number 2 | February 1979 | Pages 150-154
Technical Paper | Thorium Fuel Cycle in a Breeder Economy / Reactor | doi.org/10.13182/NT79-A32145
Articles are hosted by Taylor and Francis Online.
Subcritical multiplication constants have been derived from pulsed-neutron measurements for 2×3 square pitch and hexagonal arrays of massive hollow cylinders of uranium-aluminum alloy in H2O. The cylinders were 22.02-cm-o.d., 14.80-cm-i.d. bare 235U-Al alloy castings of 30.50 wt% uranium (76.97% 235U) in aluminum. These measurements extend previous benchmark experiments on similar castings with lower enrichments. KENO-IV, a multigroup Monte Carlo criticality code (with Hansen-Roach cross sections), calculates the subcritical multiplication constants for these lattices over the reactivity range 0.77 < keff < 0.98, with an average conservative bias of ∼0.005 in keff.