ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Standards Program
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!
Latest Magazine Issues
Dec 2025
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
January 2026
Nuclear Technology
December 2025
Fusion Science and Technology
November 2025
Latest News
Creekstone Energy taps EnergySolutions to study nuclear-powered data center
Utah-based Creekstone Energy has signed a memorandum of understanding (MOU) with EnergySolutions to study the feasibility of building at least 2 gigawatts of advanced nuclear capacity to power a 25-acre data center Creekstone is planning in Delta, Utah.
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.