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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.
R. C. Greenwood, R. G. Helmer, J W Rogers, N. D. Dudey, R. J. Popek, L. S. Kellogg, W. H. Zimmer
Nuclear Technology | Volume 25 | Number 2 | February 1975 | Pages 274-288
Technical Paper | Material Dosimetry | doi.org/10.13182/NT75-A24368
Articles are hosted by Taylor and Francis Online.
Foils of various nonfissile materials commonly utilized in neutron dosimetry were irradiated in the Coupled Fast Reactivity Measurement Facility and quantitatively gamma counted by five groups at four laboratories. Each laboratory used an independently calibrated Ge(Li) detector, and in some cases an NaI(Tl) detector also. These measurements were undertaken as a part of the Interlaboratory LMFBR Reaction Rate (ILRR) program. A primary goal of this initial set of measurements made under the ILRR program was to intercompare the reaction rates determined by the participating groups. The reaction rate values determined by the five groups were all in excellent agreement, generally consistent to within ±2% with respect to each other. Based upon this consistency and the quoted measurement errors, we would estimate that for most nonfissile dosimetry foils, where the nuclear data are adequate, reaction rates can be determined with an accuracy of ∼±2% (standard deviation uncertainty) using these techniques. This accuracy then easily surpasses the accuracy goal of ±5% (1σ uncertainty) of the ILRR program for nonfissile dosimetry foils. These reaction rates are of sufficient accuracy to be used to test and evaluate energy-dependent cross-section sets currently being evaluated in ENDF/B.