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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.
Hsiang-Shou Cheng, Ming-Shih Lu, David J. Diamond
Nuclear Technology | Volume 41 | Number 3 | December 1978 | Pages 283-298
Technical Paper | Reactor | doi.org/10.13182/NT78-A32114
Articles are hosted by Taylor and Francis Online.
The space-time effects associated with the void reactivity feedback in a commercial boiling water reactor were studied with the aid of the two-dimensional (R,Z) time-dependent coupled neutronics thermal-hydraulics computer code BNL-TWIGL. The statistical weight factor (SWF), which equates a point-reactor model to an appropriate space-dependent model, was used to quantify these effects. The SWF varied for the different reference reactor conditions and types of void perturbations considered. Its significant magnitude demonstrated that unless proper account is taken of multidimensional effects in plant transient calculations, the void feedback will be incorrect, and this will lead to errors in power and temperature. The presence of bypass void was found to increase the void reactivity feedback. The influence of other feedback mechanisms was studied, and a suggestion was offered for obtaining a measurement of the void reactivity coefficient.