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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.
Tony H. Shin, Jesson Hutchinson, Rian Bahran, Sara A. Pozzi
Nuclear Science and Engineering | Volume 193 | Number 6 | June 2019 | Pages 663-679
Technical Note | doi.org/10.1080/00295639.2018.1560758
Articles are hosted by Taylor and Francis Online.
The purpose of this technical note is to consolidate the notations used for describing parameters that pertain to neutron multiplicity mathematics relevant to various applications including nonproliferation, international safeguards, and criticality safety among others. The nomenclatures used in these techniques vary widely depending on the origin of the work and their applications. We aim to consolidate many of the previously used notations in a single document to enhance past, present, and future technical exchanges pertaining to neutron multiplicity. This will help avoid confusion in future publications and will facilitate wider application-independent advancements and utility of peer-reviewed findings. A brief introduction and history of neutron multiplicity counting is presented, followed by a summary of commonly used techniques in a variety of different applications. In each section, we present the notations used in previous publications for the reader’s reference.