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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.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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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General Kenneth Nichols and the Manhattan Project
Nichols
The Oak Ridger has published the latest in a series of articles about General Kenneth D. Nichols, the Manhattan Project, and the 1954 Atomic Energy Act. The series has been produced by Nichols’ grandniece Barbara Rogers Scollin and Oak Ridge (Tenn.) city historian David Ray Smith. Gen. Nichols (1907–2000) was the district engineer for the Manhattan Engineer District during the Manhattan Project.
As Smith and Scollin explain, Nichols “had supervision of the research and development connected with, and the design, construction, and operation of, all plants required to produce plutonium-239 and uranium-235, including the construction of the towns of Oak Ridge, Tennessee, and Richland, Washington. The responsibility of his position was massive as he oversaw a workforce of both military and civilian personnel of approximately 125,000; his Oak Ridge office became the center of the wartime atomic energy’s activities.”
Brandon Rasmussen, J. Wesley Hines, Robert E. Uhrig
Nuclear Technology | Volume 143 | Number 2 | August 2003 | Pages 217-226
Technical Paper | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies | doi.org/10.13182/NT03-A3411
Articles are hosted by Taylor and Francis Online.
This work presents an empirical modeling approach combining a bilinear modeling technique, partial least squares, with the universal function approximation abilities of single hidden layer nonlinear artificial neural networks. This approach, referred to as neural network partial least squares (NNPLS), is compared to the common autoassociative artificial neural network. The NNPLS model is embedded into a graphical user interface and implemented at the Electrical Power Research Institute's Instrumentation and Control Center located at Tennessee Valley Authority's Kingston fossil power plant. Results are presented for 51 process signals with an average absolute estimation error of ~1.7% of the mean value, and sample drift detection performances are shown.
