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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
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
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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Dragonfly, a Pu-fueled drone heading to Titan, gets key NASA approval
Curiosity landed on Mars sporting a radioisotope thermoelectric generator (RTG) in 2012, and a second NASA rover, Perseverance, landed in 2021. Both are still rolling across the red planet in the name of science. Another exploratory craft with a similar plutonium-238–fueled RTG but a very different mission—to fly between multiple test sites on Titan, Saturn’s largest moon—recently got one step closer to deployment.
On April 25, NASA and the Johns Hopkins University Applied Physics Laboratory (APL) announced that the Dragonfly mission to Saturn’s icy moon passed its critical design review. “Passing this mission milestone means that Dragonfly’s mission design, fabrication, integration, and test plans are all approved, and the mission can now turn its attention to the construction of the spacecraft itself,” according to NASA.
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.