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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.
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2027 ANS Winter Conference and Expo
October 31–November 4, 2027
Washington, DC|The Westin Washington, DC 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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Disney World should have gone nuclear
There is extra significance to the American Nuclear Society holding its annual meeting in Orlando, Florida, this past week. That’s because in 1967, the state of Florida passed a law allowing Disney World to build a nuclear power plant.
Marco Ariola, Giuseppe Ambrosino, Jonathan B. Lister, Alfredo Pironti, Fabio Villone, P. Vyas
Fusion Science and Technology | Volume 36 | Number 2 | September 1999 | Pages 126-138
Technical Paper | doi.org/10.13182/FST99-A97
Articles are hosted by Taylor and Francis Online.
A high-order, multivariable, modern plasma controller has been designed using H optimal control techniques and tested on the Tokamak Configuration Variable (TCV) tokamak. An initial design for the control of the plasma current, position, and shape parameters is described. The design process was based on the CREATE-L linearized model of TCV, and the controller was implemented on a digital processor. The results demonstrated that the required performance was delivered and the controller response was in good agreement with predictions using the model.