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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.
Petros T. Antonopoulos, Joe C. Turnage
Nuclear Technology | Volume 34 | Number 3 | August 1977 | Pages 347-361
Technical Paper | Reactor | doi.org/10.13182/NT77-A31799
Articles are hosted by Taylor and Francis Online.
In an effort to provide a basis for satisfying nuclear utility needs in generation planning, an improved computational tool has been developed that is capable of determining near-optimal operating strategy for generation systems comprised of nuclear, fossil, hydro, and pumped storage units. This strategy attempts to minimize the system generation costs while maintaining an acceptable system reliability. The computer program developed, MANAGE, is capable of performing scoping calculations to analyze multicycle fuel management options. In applying MANAGE, the techniques of risk and decision analysis are found to be useful approaches to utility system planning under uncertainty.