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Division Spotlight
Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
Meeting Spotlight
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
ANS designates Armour Research Foundation Reactor as Nuclear Historic Landmark
The American Nuclear Society presented the Illinois Institute of Technology with a plaque last week to officially designate the Armour Research Foundation Reactor a Nuclear Historic Landmark, following the Society’s decision to confer the status onto the reactor in September 2024.
Dean V. Power
Nuclear Technology | Volume 27 | Number 4 | December 1975 | Pages 680-691
Technical Paper | Nuclear Explosive | doi.org/10.13182/NT75-A24341
Articles are hosted by Taylor and Francis Online.
The coherency transfer function (CTF) is a method for summing seismograms from multiple nearly coherent sources by using a frequency domain transformation. Ground motion predictions for the nuclear explosive Rio Blanco experiment are calculated for peak vector amplitudes of acceleration, velocity, and displacement and are compared to the Rio Blanco data and the results of other prediction techniques. Predictions of amplitudes are higher than experimental results by a few percent for acceleration and displacement and by 20% for velocity. Data regression slopes are ∼12% greater than predicted values for acceleration but <5% greater for displacement and velocity. CTF predictions are found to agree with experimental results as good as or better than values predicted by other methods.