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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.
Kenji Takeshita, Yoshio Nakano
Nuclear Technology | Volume 133 | Number 3 | March 2001 | Pages 338-345
Technical Paper | Reprocessing | doi.org/10.13182/NT01-A3178
Articles are hosted by Taylor and Francis Online.
An adsorption process of iodine using Ag0-loaded adsorbents was studied for the removal of radioactive iodine in the process off-gas from a spent nuclear fuel reprocessing plant. A mathematical model to predict a breakthrough curve of I2 on the adsorbent bed was proposed. This model consists of the mass balance equation of I2 in the adsorbent bed, the mass transfer equation of I2 through the boundary layer surrounding the adsorbent particle, the intraparticle diffusion equation of I2, and the kinetic equation for the gas-solid reaction between I2 and loaded Ag0. Two unknown parameters in the model, the intraparticle diffusivity De and the apparent rate constant for the gas-solid reaction kr were determined simultaneously from the adsorption data measured by a thermogravimetric analyzer. The breakthrough curves predicted by the model using these parameters were in good agreement with the experimental ones. The rate-controlling step was evaluated by the effectiveness factor calculated from the kr value and the concentration gradient of I2 in the adsorbent particles, which was estimated by the model. From these results, the adsorbent structure required to improve the process performance is discussed. The proposed model is available as a calculation tool to support the design of the adsorption process.
