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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
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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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Nuclear Science and Engineering
August 2024
Nuclear Technology
Fusion Science and Technology
Latest News
ARPA-E announces $40 million to develop transmutation technologies for UNF
The Department of Energy’s Advanced Research Projects Agency–Energy (ARPA-E) announced $40 million in funding to develop cutting-edge technologies to enable the transmutation of used nuclear fuel into less-radioactive substances. According to ARPA-E, the new initiative addresses one of the agency’s core goals as outlined by Congress: to provide transformative solutions to improve the management, cleanup, and disposal of radioactive waste and spent nuclear fuel.
Korbinian Moser, Alexander Bock, Pierre David, Matthias Bernert, Rainer Fischer, ASDEX Upgrade Team
Fusion Science and Technology | Volume 78 | Number 8 | November 2022 | Pages 607-616
Technical Paper | doi.org/10.1080/15361055.2022.2072659
Articles are hosted by Taylor and Francis Online.
This paper explores the application of Gaussian process tomography (GPT) to the bolometer diagnostic at ASDEX Upgrade. Previous work is extended by nonstationary Cartesian kernels and kernels that incorporate magnetic equilibrium information. With the help of existing tomograms from actual shots, a set of hyperparameters working well on a broad range of bolometer measurements is found. While other tomography methods usually rely on additional information like the magnetic equilibrium, those are not required by the GPT method, and it is shown that the method presented here can produce good results without additional information. In addition, the real-time capability of this approach is successfully demonstrated by computing tomograms for 10s of bolometer data in under 5s. This is possible without providing additional information besides bolometer measurements and enables the possibility of real-time reactor control for the future.