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Radiation Protection & Shielding
The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
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Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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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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Fusion Science and Technology
Latest News
Taking shape: Fusion energy ecosystems built with public-private partnerships
It’s possible to describe fusion in simple terms: heat and squeeze small atoms to get abundant clean energy. But there’s nothing simple about getting fusion ready for the grid.
Private developers, national lab and university researchers, suppliers, and end users working toward that goal are developing a range of complex technologies to reach fusion temperatures and pressures, confounded by science and technology gaps linked to plasma behavior; materials, diagnostics, and electronics for extreme environments; fuel cycle sustainability; and economics.
Jeremy A. Roberts, Leidong Xu, Rabab Elzohery, Mohammad Abdo
Nuclear Science and Engineering | Volume 193 | Number 12 | December 2019 | Pages 1371-1378
Technical Paper | 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.