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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.
J. N. Chung, P. S. Ayyaswamy
Nuclear Technology | Volume 35 | Number 3 | October 1977 | Pages 603-610
Technical Paper | Reactor | doi.org/10.13182/NT77-A31869
Articles are hosted by Taylor and Francis Online.
Heat removal rates from containment spray droplets following a loss-of-coolant accident in a nuclear reactor have been calculated by three different droplet models: the complete mixing model, the model with internal circulation, and the rigid sphere. Irrespective of the model, the thermalization time is found to increase with increasing droplet size. It is noticed that the thermalization times predicted by the complete mixing and nonmixing models either underestimate or overestimate the value provided by the internal circulation model. It is concluded that the effect of internal circulation cannot be ignored in estimating heat removal rates from spray droplets.