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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Latest News
The RAIN scale: A good intention that falls short
Radiation protection specialists agree that clear communication of radiation risks remains a vexing challenge that cannot be solved solely by finding new ways to convey technical information.
Earlier this year, an article in Nuclear News described a new radiation risk communication tool, known as the Radiation Index, or, RAIN (“Let it RAIN: A new approach to radiation communication,” NN, Jan. 2025, p. 36). The authors of the article created the RAIN scale to improve radiation risk communication to the general public who are not well-versed in important aspects of radiation exposures, including radiation dose quantities, units, and values; associated health consequences; and the benefits derived from radiation exposures.
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.