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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.
Tsutomu Hoshino*
Nuclear Science and Engineering | Volume 49 | Number 1 | September 1972 | Pages 59-71
Technical Paper | doi.org/10.13182/NSE72-A22527
Articles are hosted by Taylor and Francis Online.
The optimization of the multistage refueling decision process was studied by the heuristic approach for four-region batch refueling including shuffling. The current state of the process is assumed to be well characterized by so called heuristic features, as excess reactivity or peaking factor. The features are summed up with each weight, defining the decision evaluation function which should be maximized at each refueling by the best decision. Thus the final criterion, i.e., the average discharge burnup at the end of the whole reactor life can be regarded as a function of the weight and is maximized in the weight space by the hill climbing algorithm. The approach can also be interpreted as an attempt to determine, through learning, the general importances of the rules of thumb in the refueling policy as maximization of the excess reactivity or power flattening. A numerical simulation is given, and the maximum burnup, the refueling scheme, and the optimal weight are discussed in relation to the power-peaking factor constraint. Though the method is not guaranteed as for the optimality, reasonable solutions are obtained and the intuitive understanding of the process is possible by discussing the optimum weight of each rule.