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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.
T. Shimooke, K. Matsumoto
Nuclear Technology | Volume 35 | Number 1 | August 1977 | Pages 119-130
Technical Paper | Fuel | doi.org/10.13182/NT77-A31855
Articles are hosted by Taylor and Francis Online.
The probability distributions of the peak-clad temperature (PCT) and of the maximum cladding oxidation thickness supposed to occur in the hypothetical loss-of-coolant accidents (LOCAs) for a typical boiling water reactor (BWR) are studied by a computer-simulated experiment, using the computer program MOXY-EM, one of the fuel heatup analysis codes for a BWR. To reduce the numbers of the computer runs, the theory and techniques of the factorial design of experiments are used. We have specially developed the partially orthogonal factorial design, which not only selects the small fraction of all possible runs that correspond to the various input sets, but also produces under this small number of runs the right statistical distributions of the PCT and of the cladding oxidation thickness. The PCT is found statistically to distribute normally, and the maximum cladding oxidation thickness obeys the log-normal distribution in our survey for the LOCAs at a typical BWR.