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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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Fusion Science and Technology
Latest News
Vogtle-3 shuts down for valve issue
One of the new Vogtle units in Georgia was shut down unexpectedly on Monday last week for a valve issue that has been investigated and repaired. According to multiple local news outlets, Georgia Power reported on July 17 that unit 3 was back in service.
Southern Company spokesperson Jacob Hawkins confirmed that Vogtle-3 went off line at 9:25 p.m. on July 8 “due to lowering water levels in the steam generators caused by a valve issue on one of the three main feedwater pumps.”
Javier E. Vitela
Fusion Science and Technology | Volume 52 | Number 1 | July 2007 | Pages 1-28
Technical Paper | doi.org/10.13182/FST07-A1484
Articles are hosted by Taylor and Francis Online.
We report on the burn control studies of a D-T-fueled tokamak reactor using a two-temperature, zero-dimensional, volume-averaged model, assuming that electrons and ions have the same radial profile with different central temperatures. Balance equations for the particle and energy densities are used assuming that energy and particle transport losses are independent of each other and can be estimated online; thermalization time delays of the energetic alpha particles produced by fusion are taken into account in the dynamical equations. The burn stabilization is achieved with radial basis neural networks (RBNNs) that concurrently modulate a D-T refueling rate, a neutral 4He beam, and auxiliary heating powers to the electrons and the ions, all constrained to maximum allowable levels. The resulting network provides feedback stabilization in a wide range of energy confinement times for plasma density and temperature excursions significantly far from their nominal values. Transient examples using different ELMy scaling laws show that the RBNN controller is stable with respect to any particular scaling law that the tokamak may actually follow for the energy and particle transport losses and is also robust with respect to noise in the measurement of the confinement times. Furthermore, it satisfactorily responds to sudden changes in fast-alpha-particle losses due to increments in magnetohydrodynamic events.