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Conference Spotlight
2025 ANS Winter Conference & Expo
November 8–12, 2025
Washington, DC|Washington Hilton
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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
Nuclear News 40 under 40: The wait is over
Following the enthusiastic response from the nuclear community in 2024 for the inaugural NN 40 under 40, the Nuclear News team knew we had to take up the difficult task in 2025 of turning it into a recurring annual issue—though there was plenty of uncertainty as to how the community would receive a second iteration this year. That uncertainty was unfounded, clearly, as the tight-knit nuclear community embraced the chance to celebrate the up-and-coming generation of scientists, engineers, and policy makers who are working to grow the influence of this oft misunderstood technology.
Imane Khalil, Quinn Pratt
Nuclear Technology | Volume 205 | Number 7 | July 2019 | Pages 987-991
Technical Note | doi.org/10.1080/00295450.2018.1554026
Articles are hosted by Taylor and Francis Online.
A MATLAB tool that combines computational fluid dynamics with uncertainty quantification (UQ) applied to a two-dimensional FLUENT computational model to predict the heat transfer and the maximum temperature inside a spent fuel assembly is presented in this technical note. The tool is used to establish a connection between MATLAB and ANSYS-FLUENT for the purpose of UQ using the Sandia National Laboratory’s UQ Toolkit. This tool allows users to adapt the UQ methodology to existing ANSYS-FLUENT models in order to automate the quadrature-based simulation process. The novelty of the tool presented in this technical note is its ability to generate results covering a continuous range of input parameters by using polynomial chaos expansions for the representation of random variables and the propagation of uncertainty in computational models.