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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
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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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.”
J. Wesley Hines, Brandon Rasmussen
Nuclear Technology | Volume 151 | Number 3 | September 2005 | Pages 281-288
Technical Paper | Nuclear Plant Operations and Control | doi.org/10.13182/NT05-A3650
Articles are hosted by Taylor and Francis Online.
Empirical modeling techniques have been applied to online process monitoring to detect equipment and instrumentation degradations. However, few applications provide prediction uncertainty estimates, which can provide a measure of confidence in decisions. This paper presents the development of analytical prediction interval estimation methods for three common nonlinear empirical modeling strategies: artificial neural networks, neural network partial least squares, and local polynomial regression. The techniques are applied to nuclear power plant operational data for sensor calibration monitoring, and the prediction intervals are verified via bootstrap simulation studies.