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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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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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Fusion Science and Technology
Latest News
Bacteria found to reduce uranium mobility in clay
Researchers at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) research laboratory in Germany have investigated a microorganism capable of transforming water-soluble hexavalent uranium [U(VI)] to the less-mobile tetravalent uranium [U(IV)]. The researchers found that the sulfate-reducing bacterium Desulfosporosinus hippei, a relative of naturally occurring microorganisms present in clay rock and bentonite, showed a relatively fast removal of uranium from clay pore water.
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.