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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.
Richard H. Williamson, Edward J. Hanrahan
Nuclear Technology | Volume 39 | Number 1 | June 1978 | Pages 10-17
Technical Paper | Energy Modeling and Forecasting / Reactor | doi.org/10.13182/NT78-A17002
Articles are hosted by Taylor and Francis Online.
The application of a combined set of energy and economic models describing the complex interactions of the nation’s energy system improved the planning processes at the U.S. Energy Research and Development Administration for new technology development. The models include econometric techniques for macroeconomic projections, input-output techniques for sector detail, linear programming approaches for resource allocation, and accounting tools for other physical constraints. Comparison studies on the use of energy prices alone versus a combination of energy prices and new technology show that new technology permits higher gross national product growth rate, more jobs, lower delivered energy prices, and improved energy-economic efficiency.