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Nuclear Criticality Safety
NCSD provides communication among nuclear criticality safety professionals through the development of standards, the evolution of training methods and materials, the presentation of technical data and procedures, and the creation of specialty publications. In these ways, the division furthers the exchange of technical information on nuclear criticality safety with the ultimate goal of promoting the safe handling of fissionable materials outside reactors.
Materials in Nuclear Energy Systems (MiNES 2023)
December 10–14, 2023
New Orleans, LA|New Orleans Marriott
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Nuclear Science and Engineering
Fusion Science and Technology
Eisenhower’s “Atoms for Peace” at 70
Seventy years ago to the day, President Dwight D. Eisenhower gave his historic address to the United Nations General Assembly in New York City. (See December 2023 Nuclear News's “Leaders” column to read the reflections of Kathryn Huff, the Department of Energy’s assistant secretary for nuclear energy, on the speech’s anniversary.)
Scott W. Mosher, Stephen C. Wilson
Fusion Science and Technology | Volume 74 | Number 4 | November 2018 | Pages 263-276
Technical Paper | doi.org/10.1080/15361055.2018.1496691
Articles are hosted by Taylor and Francis Online.
Neutronics analyses of the ITER experimental fusion reactor rely on increasingly complex geometry models and estimates of energy-dependent neutron flux and radiation dose-rate distributions generated at ever higher resolutions. There are significant practical challenges with applying the Monte Carlo N-Particle (MCNP) continuous-energy transport code to high-resolution analyses. For models consisting of more than 100 000 surfaces and cells, geometry initialization can take several hours, thus slowing down model integration and transport analysis efforts. In multithreaded simulations, the amount of memory consumed by superimposed mesh tally data increases in proportion to the number of threads. This behavior limits either the tally resolution or the number of processor cores that can be utilized in the simulation. This paper describes algorithmic improvements that were implemented in a modified version of MCNP5 to overcome these limitations. These improvements are referred to as the Oak Ridge National Laboratory Transformative Neutronics (ORNL-TN) upgrade. A comparison of the performance and memory usage of both MCNP5 and ORNL-TN on several relevant fusion neutronics models is presented. In these tests and in actual high-resolution neutronics analyses, ORNL-TN reduces geometry processing times from hours to a few seconds and increases in-memory mesh tally capacity from the order of 108 to 1010 space-energy bins.