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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.
Chaung Lin, Dih-Hua Yang
Nuclear Technology | Volume 122 | Number 3 | June 1998 | Pages 318-329
Technical Paper | Reactor Operations and Control | doi.org/10.13182/NT98-A2873
Articles are hosted by Taylor and Francis Online.
A fuzzy logic controller (FLC) has been designed to control the water level in an advanced boiling water reactor (ABWR). The performance was comparable to that of a proportional-integral controller. However, the feedwater flow rate did not change smoothly to the steady state. Therefore, a method based on input-output data was adopted to prevent this problem. The data required for deriving the fuzzy rules were the results of various instances of satisfactory manual control of an ABWR simulation model. To construct the membership functions of the linguistic variable, the data were clustered using the fuzzy C-means method. The fuzzy rules were then generated from the data. Because the control actions were not guaranteed to be proper in all the cases and the data were not complete for all the possible operation conditions, the fuzzy rules were modified and extra rules were added based on human knowledge so that satisfactory performance can be achieved. Nevertheless, the method is helpful in deriving a set of important control rules at the beginning stage of design, especially when the importance of the linguistic variables is not clear. The simulation results showed that the designed controller followed the desired control action, which was imposed on the designed data, and the performance of the controller was better than the previously designed FLC.