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Meeting Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
The U.S. Million Person Study of Low-Dose-Rate Health Effects
There is a critical knowledge gap regarding the health consequences of exposure to radiation received gradually over time. While there is a plethora of studies on the risks of adverse outcomes from both acute and high-dose exposures, including the landmark study of atomic bomb survivors, these are not characteristic of the chronic exposure to low-dose radiation encountered in occupational and public settings. In addition, smaller cohorts have limited numbers leading to reduced statistical power.
Hyeonmin Kim, Seo-Ryong Koo, Geon-Pil Choi, Jung Taek Kim (KAERI)
Proceedings | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technolgies (NPIC&HMIT 2019) | Orlando, FL, February 9-14, 2019 | Pages 563-572
There are five operating modes of Nuclear Power Plants (NPPs): refueling, startup, low power, normal power, and shutdown. In these operating modes, the startup and the shutdown operating modes of NPPs are completely manually operated. From the Operational Performance Information System (OPIS) for NPPs, which is the overall database for controlling safety performance, human error under startup and shutdown was found to be 9% during last 20 years in South Korea. For reducing the operator’s load from the startup and shutdown operations of existing NPPs, it is necessary to develop an operator support system based on Artificial Intelligence (AI). Recently, AI technology has facilitated a breakthrough by accumulating data, advanced algorithms, and growing computing power. Among these factors, the key technology of the breakthrough is deep learning that leads current AI technology. In many technical fields, the development of automation and autonomous systems has been studied by using deep learning. Therefore, in this study, an automation system for the startup and shutdown in NPPs develop using deep learning. The automation system is based on an expert system due to characteristics of the startup and shutdown operating modes, and a variety of operating controls depending on each operator are simulated by deep learning. A feasibility study is conducted by using the Compact Nuclear Simulator (CNS) that is a simulator based on Westinghouse 3-loop NPPs. The target scenario for the feasibility study is bubble creation in a pressurizer under startup. In addition, a selected deep-learning algorithm is a Recurrent Neural Network (RNN), which is a robust method for time series analysis.