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Conference Spotlight
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.
Glenn T. Gobbel, Ruth M. Reeves (Vanderbilt Univ), Shawn St. Germain (INL), Mark Pierson, Nathan Lau (Virginia Tech)
Proceedings | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technolgies (NPIC&HMIT 2019) | Orlando, FL, February 9-14, 2019 | Pages 1558-1567
Comprehending and assessing the vast amount of information within technical specifications, procedure manuals, and work orders associated with nuclear power plants is challenging. The demands associated with this task are particularly evident during power plant outages, which create a pressing need for quickly and effectively identifying the right information at the right time for making the right decision. Text mining methods that use natural language processing (NLP) approaches to automatically extract and store document information might assist managers of power plant outages by reducing the cognitive load. NLP can parse unstructured text in documents and convert it into structured form for storage of conceptual information and relationships. We are exploring the feasibility of using NLP for helping in outage management. As a proof-of-principle, we are designing an NLP tool to identify constraints in the configuration of components during the procedure used to test a low-pressure safety injection (LPSI) pump. The NLP tool is extracting action verbs that represent instructions for changing the state of power plant components. The extracted information will form the analytical backend for determining whether proposed changes in configuration lead to constraint violations, which will be displayed via a graphical user interface.