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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!
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Nuclear Science and Engineering
August 2024
Nuclear Technology
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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.”
Dongjune Chang, Maolong Liu, Youho Lee (Univ of New Mexico)
Proceedings | Advances in Thermal Hydraulics 2018 | Orlando, FL, November 11-15, 2018 | Pages 212-226
A Loss of Flow Accident (LOFA) is an accident that causes cooling to slow down due to pump failure or stopping during operation. A fast or slow change in two-phase flow, when overlooked, can lead to an accident like LOFA, and thus, understanding its nature is essential for nuclear reactor safety. In this paper, we demonstrate that using one of the machine learning techniques called Support Vector Machine, one can find the most important factors in two-phase flow change. Using one of the commercial thermal hydraulics analysis code, MARS (A multi-dimensional thermal-hydraulic system code), simulation results were obtained for several scenarios where the mass flow rate decreased sharply. The transient flow change phenomenon near a single PWR rod, which is the simplest case of the reactor, is modeled. The outlet temperature of the coolant which is the final output factor of the transient flow change and the peak temperature of the cladding rod are very important factors for safety analysis. We also show that the outlet temperature profile of the coolant can be used to predict the unknown mass flux and the peak temperature of the cladding rod using the Multi-class Support vector machine algorithm. These results suggest that machine learning techniques may be used to analyze the complex systems of accidents that may occur in the nuclear system.