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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.
Fan Li, Belle R. Upadhyaya
Nuclear Technology | Volume 173 | Number 1 | January 2011 | Pages 17-25
Technical Paper | NPIC&HMIT Special / Nuclear Plant Operations and Control | doi.org/10.13182/NT11-A11480
Articles are hosted by Taylor and Francis Online.
Fault diagnosis is an important area in the nuclear industry for effective and continuous operation of power plants. All the approaches for fault diagnosis depend critically on the sensors that measure important process variables in the system. The locations of these sensors determine the effectiveness of the diagnostic methods. However, the emphasis of most fault diagnosis approaches is primarily on procedures to perform fault detection and isolation (FDI) given a set of sensors. Little attention has been given to the actual allocation of sensors for achieving efficient FDI performance. A graph-based approach, the directed graph (DG), is proposed in this paper as a solution for the optimization of sensor locations for efficient fault identification. The application of the DG modeling in deciding the locations of sensors based on the concepts of observability and fault resolution is introduced. A reliability maximization-based optimization framework for sensor placement from a fault diagnosis perspective is described. The helical coil steam generator unit of the International Reactor Innovative and Secure system is outlined to underscore the utility of the algorithms for large systems.