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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
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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Strong performances across the board
Craig Piercycpiercy@ans.org
Another year, another stellar performance by America’s nuclear plants. We’ve come to expect high capacity factors, and it’s a credit to the men and women of the profession. They’ve made routine something that was unimaginable not so long ago.
The decadal challenge for the nuclear enterprise now is to maintain this high level of operational excellence for the current fleet, while at the same time ushering in a new generation of technologies at scale. It will be a big job—but one that seems more and more likely with each passing day.
Pola Lydia Lagari, Styliani Pantopoulou, Miltos Alamaniotis, Lefteri H. Tsoukalas
Nuclear Technology | Volume 207 | Number 8 | August 2021 | Pages 1270-1279
Technical Paper | doi.org/10.1080/00295450.2020.1816743
Articles are hosted by Taylor and Francis Online.
Since radionuclides have unique characteristic gamma-ray spectra, usually maintained as a set of (energy, counts/energy) ordered pairs, an explicit functional representation would be indisputably useful. In this paper, the Gamma Detector Response and Analysis Software has been used to simulate the gamma-ray spectra as it would be collected by an NaI detector for a set of 70 radionuclides. Gaussian radial basis function (RBF) networks that offer simple, closed-form expressions are then trained to represent each of these spectra. Hence, a library consisting of 70 RBF networks for the corresponding radionuclides has been built. The presence of these library-contained radionuclides in a given gamma-ray spectrum of an unknown source is identified by an algorithm that employs a linear combination of the library spectra to approximate the unknown spectrum. The combination coefficients are then determined by minimizing the squared deviation error function under convexity constraints.