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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.
K. Rady, A. A. Abouelsoud, S. A. Kotb, M. M. El Metwally
Nuclear Science and Engineering | Volume 194 | Number 7 | July 2020 | Pages 572-582
Technical Paper | doi.org/10.1080/00295639.2020.1755808
Articles are hosted by Taylor and Francis Online.
This paper discusses modeling of the performance of a VVER-type nuclear power plant using the Fractional Neutron Point Kinetics (FNPK) model. The modeling intent is to achieve a nonlinear system of fractional-order differential equations that are solved using SIMULINK by developing a scheme with the FOMCON Toolbox in the Matlab® environment. The model is shown to be identifiable, and the goodness of fit between the measurements and the model’s output is improved as a result of employing the optimized fractional differential equation. Benchmarking the results of the FNPK model against those from the optimized Classical Neutron Point Kinetics model shows that the FNPK model is superior.