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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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Fusion Science and Technology
Latest News
Framatome signs contracts with Sizewell C
French nuclear developer Framatome is slated to deliver key equipment for Sizewell C Ltd.’s two large reactors planned for the United Kingdom’s Suffolk coast.
The agreement, reportedly worth multiple billions of euros, was announced this week and will involve Framatome from the design phase until commissioning. The company also agreed to a long-term fuel supply deal. Framatome is 80.5 percent owned by France’s EDF and 19.5 percent owned by Mitsubishi Heavy Industries.
Jae-Uk Lee, Min Ho Chang, Sei-Hun Yun, Jin-Kuk Ha, Euy Soo Lee, In-Beum Lee
Fusion Science and Technology | Volume 71 | Number 3 | April 2017 | Pages 296-304
Technical Paper | doi.org/10.1080/15361055.2017.1291027
Articles are hosted by Taylor and Francis Online.
A Tokamak has startup and shutdown periods during which demand specifications differ from those during steady fueling operation. These periods can affect the required number of getter beds of the Storage and Delivery System. In this study, we developed a mathematical model based on the State Task Network, and an algorithm that considers daily operation which includes the period from startup to shutdown to find the optimal number of getter beds. This algorithm can estimate the optimal initial inventory of tritium or deuterium in a getter bed to compensate for fuel consumption until shutdown. The inductive operation mode of the Tokamak is analyzed to illustrate the applicability of the model and algorithm.