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Division Spotlight
Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
Meeting Spotlight
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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!
Latest Magazine Issues
Jul 2024
Jan 2024
Latest Journal Issues
Nuclear Science and Engineering
August 2024
Nuclear Technology
Fusion Science and Technology
Latest News
Vogtle-3 shuts down for valve issue
One of the new Vogtle units in Georgia was shut down unexpectedly on Monday last week for a valve issue that has since been investigated and repaired. According to multiple local news outlets, Georgia Power reported on July 17 that Unit 3 was back in service.
Southern Company spokesperson Jacob Hawkins confirmed that Vogtle-3 went off line at 9:25 p.m. local time on July 8 “due to lowering water levels in the steam generators caused by a valve issue on one of the three main feedwater pumps.”
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.