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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.
W. N. McElroy, L. S. Kellogg
Nuclear Technology | Volume 25 | Number 2 | February 1975 | Pages 180-223
Technical Paper | Material Dosimetry | doi.org/10.13182/NT75-A24364
Articles are hosted by Taylor and Francis Online.
The development, design, and operation of nuclear reactors require the accurate prediction of (a) fission rates and burnup for fuels and (b) neutron exposure for neutron-induced property changes for fuels and materials. Goal accuracies of as low as 1% (1σ) have been set for the determination of fission rates, burnup, and neutron fluences for the fast-reactor development program. Based on the discussion of the status of fuels and materials fast-reactor dosimetry data development and testing, attainable goal accuracies presently appear to be in the range of 2 to 5%. Significant progress has been made in achieving high-accuracy measurements through a coordinated interlaboratory effort of integral measurements in low- and high-intensity neutron fields. A few of the major accomplishments of this interlaboratory work are as follows.