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.
Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
2021 Student Conference
April 8–10, 2021
North Carolina State University|Raleigh Marriott City Center
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
Latest Journal Issues
Nuclear Science and Engineering
Fusion Science and Technology
Baranwal reviews virtual STEM lessons for U.S. tribal communities
In a blog post to the Department of Energy’s website on November 23, Rita Baranwal, assistant secretary for the Office of Nuclear Energy, commended recent virtual lesson projects from the Office of Nuclear Energy and the Nuclear Energy Tribal Working Group to increase STEM opportunities for Native American tribes.
The spotlighted lesson discussed in the article focused on a 3D-printed clip that turns a smartphone or tablet into a microscope with the ability to magnify items by 100 times. The Office of Nuclear Energy shipped nearly 1,000 of these microscope clips to students across the country, many of them going to U.S. tribal communities.
Jeremy A. Roberts, Leidong Xu, Rabab Elzohery, Mohammad Abdo
Nuclear Science and Engineering | Volume 193 | Number 12 | December 2019 | Pages 1371-1378
Technical Paper | dx.doi.org/10.1080/00295639.2019.1634928
Articles are hosted by Taylor and Francis Online.
An algorithm based on dynamic mode decomposition (DMD) for acceleration of the power method (PM) is presented. The PM is a simple technique for determining the dominant eigenmode of an operator A, and variants of the PM are widely used in reactor analysis. DMD is an algorithm for decomposing a time series of spatially dependent data and producing an explicit-in-time reconstruction for that data. By viewing successive PM iterates as snapshots of a time-varying system tending toward a steady state, DMD can be used to predict that steady state using (sometimes surprisingly small) iterates. The process of generating snapshots with the PM and extrapolating forward with DMD can be repeated. The resulting restarted, DMD-accelerated PM [or DMD-PM()] was applied to the two-dimensional International Atomic Energy Agency diffusion benchmark and compared to the unaccelerated PM and the Arnoldi method. Results indicate that DMD-PM() can reduce the number of power iterations required by a factor of approximately 5. However, the Arnoldi method always outperformed DMD-PM() for an equivalent number of matrix-vector products Av. In other words, DMD-PM() cannot compete with leading eigensolvers if one is not limited to snapshots produced by the PM. Contrarily, DMD-PM() can be readily applied as a postprocess to existing PM applications for which the Arnoldi method and similar methods are not directly applicable. A slight variation of the method was also found to produce reasonable approximations to the first and second harmonics without substantially affecting convergence of the dominant mode.