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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. Elias, Y. Segal, A. Notea
Nuclear Technology | Volume 28 | Number 2 | February 1976 | Pages 261-269
Technical Paper | Radiation | doi.org/10.13182/NT76-A31567
Articles are hosted by Taylor and Francis Online.
The properties of energy distributions resulting from transmission of gamma rays through finite cylindrical barriers were studied using a modified version of the MORSE Monte Carlo transport code. Systematic studies were carried out to investigate the effects of density, composition, source energy, and cylinder diameter on the scattered and unscattered flux. In addition the average number of collisions and the contribution of the single-, double-, and triple-scattered photons were calculated for each run. It was found that for the same energy group, the intensity of the scattered flux reaches a maximum at a density that depended directly on the leakage probability but only slightly on composition. The correspondence between the Monte Carlo simulation and experimental results was found to be good.