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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.
John W. Wilson, G. S. Khandelwal
Nuclear Technology | Volume 23 | Number 3 | September 1974 | Pages 298-305
Technical Paper | Shielding | doi.org/10.13182/NT74-A15922
Articles are hosted by Taylor and Francis Online.
A convenient property of energetic heavy charged particles in passing through matter is that the primaries and their secondary particles remain relatively confined to the primary beam axis. As a consequence, the particle beam in matter is not strongly affected by near boundaries and the problem of calculating dose in a complicated geometric object is greatly simplified. Furthermore, the small beam width is a useful expansion parameter to develop a series that converges rapidly for most practical dose calculations. The final result relates dose at any point in an arbitrary convex region to an integral over the fluence-to-dose conversion factors for normal incidence on a semi-infinite slab. A representation of these fluence-to-dose conversion factors and all the necessary information required to calculate dose in arbitrary convex regions of tissue for proton energies below 1 GeV are found in terms of two energy-dependent parameters and known functions.