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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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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Deep Space: The new frontier of radiation controls
In commercial nuclear power, there has always been a deliberate tension between the regulator and the utility owner. The regulator fundamentally exists to protect the worker, and the utility, to make a profit. It is a win-win balance.
From the U.S. nuclear industry has emerged a brilliantly successful occupational nuclear safety record—largely the result of an ALARA (as low as reasonably achievable) process that has driven exposure rates down to what only a decade ago would have been considered unthinkable. In the U.S. nuclear industry, the system has accomplished an excellent, nearly seamless process that succeeds to the benefit of both employee and utility owner.
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.