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Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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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Latest News
G7 pledges support for nuclear at Italy meeting
The Group of Seven (G7) recommitted its support for nuclear energy in the countries that opt to use it at a Ministerial Meeting on Climate in Italy last month.
In a statement following the April meeting, the group committed to support multilateral efforts to strengthen the resilience of nuclear supply chains, referencing the goal set by 25 countries during last year’s COP28 climate conference in Dubai to triple global nuclear generating capacity by 2050.
Cody J. Permann, Andrea M. Jokisaari, Michael R. Tonks, Daniel Schwen, Derek R. Gaston, Fande Kong, Robert Hiromoto, Richard C. Martineau
Nuclear Technology | Volume 207 | Number 7 | July 2021 | Pages 885-904
Technical Paper | doi.org/10.1080/00295450.2020.1843893
Articles are hosted by Taylor and Francis Online.
The ability to identify features within finite element simulations and track them over time is necessary for understanding and quantifying complex behaviors as disparate as turbulent vortices in a flow field to microstructure evolution. We extend our previous research on feature identification in parallel unstructured meshes with the novel ability to maintain feature distinctness by dynamically remapping individual features to new simulation variables as the simulation evolves. We utilize this capability to drastically reduce the number of variables required in a simulation while maintaining the same fidelity as simulations without these reductions. We present this novel remapping algorithm and the corresponding implementation within the open-source Multiphysics Object Oriented Simulation Environment (MOOSE) framework. We demonstrate the utility of the method with a novel phase-field model of irradiation-driven grain subdivision in UO2. Grain population statistics are tracked over time, and a dynamically stable population of grains with a reduced size evolves. These results indicate that the small grain sizes observed in high-burnup UO2 can be explained by this mechanism.