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Division Spotlight
Fusion Energy
This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
Meeting Spotlight
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
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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Latest News
Argonne’s METL gears up to test more sodium fast reactor components
Argonne National Laboratory has successfully swapped out an aging cold trap in the sodium test loop called METL (Mechanisms Engineering Test Loop), the Department of Energy announced April 23. The upgrade is the first of its kind in the United States in more than 30 years, according to the DOE, and will help test components and operations for the sodium-cooled fast reactors being developed now.
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.