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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.
E. L. Simmons, Donald J. Dudziak, S. A. W. Gerstl
Nuclear Technology | Volume 34 | Number 3 | August 1977 | Pages 317-340
Technical Paper | Reactor | doi.org/10.13182/NT77-A31797
Articles are hosted by Taylor and Francis Online.
The final design of a nuclear reactor and any component thereof evolves through an iterative process that necessitates the evaluation of many alternative concepts. In particular, conceptual and preliminary reactor systems studies require many quick survey calculations to determine changes of certain important design parameters in response to changes of layout, material compositions, and other design features. Effective methods to perform such design sensitivity analyses are described and applied to the nuclear design of a fusion reactor. Generalized perturbation theory is used to calculate sensitivities of integral nuclear design parameters to certain design changes. The accuracy of this method is evaluated for specific cases where large ranges of design perturbations are considered. Specifically, the effects on tritium breeding, energy deposition, atom displacements and transmutations in the Reference Theta-Pinch Reactor design due to variations in the beryllium thickness, choices of molybdenum, vanadium, or niobium structural material, BeO versus beryllium neutron multiplier, graphite region thickness, and 6Li enrichment are investigated.