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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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.
Kaushik Banerjee, William R. Martin
Nuclear Science and Engineering | Volume 174 | Number 1 | May 2013 | Pages 30-45
Technical Paper | doi.org/10.13182/NSE11-94
Articles are hosted by Taylor and Francis Online.
Monte Carlo point detector and surface crossing flux tallies are two widely used tallies, but they suffer from an unbounded variance. As a result, the central limit theorem cannot be used for these tallies to estimate confidence intervals. By construction, kernel density estimator (KDE) tallies can be directly used to estimate flux at a point, but the variance of this point estimate does not converge as 1/N, which is not unexpected for a point quantity. However, an improved approach is to modify both point detector and surface crossing flux tallies directly by using KDE within a variance reduction approach and taking advantage of the fact that KDE estimates the underlying probability density function. This methodology is illustrated by several numerical examples and shows numerically that both the surface crossing tally and the point detector tally converge as 1/N (in variance), and both are asymptotically unbiased.