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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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
Report spotlights energy sector’s growing nuclear investment
As part of a broader series on the future of global energy markets, S&P Global has released a report on examining the growing interest in nuclear power as the solution to many of the problems the energy sector faces.
To read the full details and conclusions of the report, click here.
Payam Vaezi, Christopher Holland
Fusion Science and Technology | Volume 74 | Number 1 | July-August 2018 | Pages 77-88
Technical Paper | doi.org/10.1080/15361055.2017.1372987
Articles are hosted by Taylor and Francis Online.
Due to the strong nonlinear dependence of plasma turbulence on drive and dissipation mechanisms, uncertainties in experimental inputs can be greatly magnified in simulations of this turbulence. Thus, careful uncertainty quantification (UQ) and its inclusion within validation metrics is an integral part of plasma turbulence validation studies. To minimize the number of simulations required for UQ, we investigate the use of the rapidly converging nonintrusive probabilistic collocation method (PCM) for efficient plasma turbulence UQ. This approach is shown to yield more realistic uncertainty estimates than simple uniform sampling methods for a practical number of nonlinear simulations. The inclusion of UQ above and near critical gradients is discussed. To demonstrate its utility, the advantages of PCM are first illustrated using a simple model of critical gradient turbulence. It is then used on simulations from a validation study of drift-wave turbulence in the CSDX linear plasma device experiment. The advantage of more advanced methods for selecting samples from the uncertainties in the plasma turbulence simulations is also discussed.