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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.
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Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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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 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. 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.”
Andrea Murari, Guido Vagliasindi, Eleonora Arena, Paolo Arena, Luigi Fortuna, JET-EFDA Contributors
Fusion Science and Technology | Volume 58 | Number 2 | October 2010 | Pages 685-694
Selected Paper from the Sixth Fusion Data Validation Workshop 2010 (Part 1) | doi.org/10.13182/FST10-A10893
Articles are hosted by Taylor and Francis Online.
In practically all fields of science, measurements are affected by noise, which can sometimes be modeled with an appropriate probability distribution function. The results of measurements are therefore known only with uncertainties that sometimes can be significant. In many cases the noise source is independent of the system to be studied and the quantities to be measured. In this paper, a numerical approach to handle statistical uncertainties, due to an independent noise source, in a fuzzy logic system is developed. Numerical analysis and various tests with a benchmark show how statistical error bars can be interpreted as an independent "axis of complexity" with respect to the fuzzy boundaries of the membership functions. The uncertainties in the inputs can be transferred to the output and handled separately from the system intrinsic fuzzyness. The main advantages of this independent treatment of the measurement errors are shown in the case of a binary classification task: the regime confinement identification in high-temperature tokamak plasmas. Significant improvements in the correct prediction rate have been achieved with respect to the classification performed without considering the error bars in the measurements.