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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.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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
Kathryn Huff stepping down from DOE Nuclear Energy post
Huff
After serving two years as the Department of Energy’s assistant secretary for Nuclear Energy, Kathryn Huff will vacate that position on May 3 and return to teaching. Huff had started at the DOE in May 2021, serving for one year as the principal deputy assistant secretary for Nuclear Energy
“Serving in this capacity has been an unparalleled privilege, and I’m immensely grateful for the opportunity to have worked alongside you--the dedicated and talented public servants in Nuclear Energy, in DOE, and across the Biden-Harris Administration,” Huff wrote in an email announcement to colleagues last week. “I chose this timing to enable the smoothest transition back to my professorship at the University of Illinois at Urbana-Champaign where my beloved research, students, husband, and dog await.”
Jinkyun Park, Wondea Jung, Jaewhan Kim, Jaejoo Ha
Nuclear Technology | Volume 143 | Number 3 | September 2003 | Pages 290-308
Technical Paper | Nuclear Plant Operations and Control | doi.org/10.13182/NT03-A3418
Articles are hosted by Taylor and Francis Online.
In complex systems, such as nuclear power plants (NPPs) or airplane control systems, human error has been regarded as the primary cause of many events. Therefore, to ensure system safety, extensive effort has been made to identify the significant factors that can cause human error. According to related studies, written manuals or operating procedures are revealed as one of the important factors, and the understandability is pointed out as one of the major reasons for procedure-related human errors.Many qualitative checklists have been suggested to evaluate emergency operating procedures (EOPs) of NPPs so as to minimize procedure-related human errors. However, since qualitative evaluations using checklists have some drawbacks, a quantitative measure that can quantify the complexity of EOPs is indispensable.From this necessity, Park et al. suggested the step complexity (SC) measure to quantify the complexity of procedural steps included in EOPs. To verify the appropriateness of the SC measure, averaged step performance time data obtained from emergency training records of the loss-of-coolant accident (LOCA) and the excess steam demand event were compared with estimated SC scores. However, although averaged step performance time data and estimated SC scores show meaningful correlation, some important issues such as determining proper weighting factors have to be clarified to ensure the appropriateness of the SC measure. These were not properly dealt with due to a lack of backup data.In this paper, to resolve one of the important issues, emergency training records are additionally collected and analyzed in order to determine proper weighting factors. The total number of collected records is 66, and the training scenarios cover five emergency conditions including the LOCA, the steam generator tube rupture, the loss of all feedwater, the loss of off-site power, and the station blackout. From these records, average step performance time data are retrieved, and new weighting factors are determined by using a nonlinear regression analysis. The results show that the SC scores quantified by the new weighting factors show statistically meaningful correlation with averaged step performance time data. Thus, it can be concluded that the SC measure can represent the complexity of procedural steps included in EOPs.
