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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.
Michael J. Kolar, Nolan C. Olson
Nuclear Technology | Volume 36 | Number 1 | November 1977 | Pages 56-64
Radiation Environments in Nuclear Reactor Power Plant | Reactor | doi.org/10.13182/NT77-A31958
Articles are hosted by Taylor and Francis Online.
A mathematical model was developed to calculate the dose to equipment inside containment of power reactors following a maximum hypothetical accident (MHA). The model permitted both instantaneous and time-dependent releases and incorporated decay chains up to six isotopes in length. The release of noble gases produced by the decay of halogens that plate out on surfaces or are trapped by filters was taken into account. The resulting equations were solved analytically. The gamma and beta dose due to an MHA from a 3-GW(th) reactor was computed using this model. Results show that the use of decay chains produces a 38% increase in dose, and an instantaneous release produces a dose that is 14% higher than the time-dependent release.