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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.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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Fusion Science and Technology
Latest News
Commercial nuclear innovation "new space" age
In early 2006, a start-up company launched a small rocket from a tiny island in the Pacific. It exploded, showering the island with debris. A year later, a second launch attempt sent a rocket to space but failed to make orbit, burning up in the atmosphere. Another year brought a third attempt—and a third failure. The following month, in September 2008, the company used the last of its funds to launch a fourth rocket. It reached orbit, making history as the first privately funded liquid-fueled rocket to do so.
S. González, J. Vega, A. Murari, A. Pereira, JET-EFDA Contributors
Fusion Science and Technology | Volume 62 | Number 3 | November 2012 | Pages 403-408
Selected Paper from Seventh Fusion Data Validation Workshop 2012 (Part 2) | doi.org/10.13182/FST12-A15339
Articles are hosted by Taylor and Francis Online.
New automated analysis methods allow the analysis of large amounts of data without human interaction. Tokamak machines, such as JET, are perfect candidates to apply data mining techniques in order to obtain results with high statistical relevance. In this paper, an automated technique to analyze the pedestal edge gradient is introduced. This technique does not require human intervention and therefore can be applied to many pulses. The pedestal edge gradient is the temperature gradient corresponding to the edge transport barrier at the edge of high-confinement-mode plasmas. This gradient is quantified using the temperature profiles obtained from the electron cyclotron emission diagnostic. An automated technique to locate events in plasma pulses is applied in order to locate edge-localized modes (ELMs), and then the evolution of the edge pedestal gradient is analyzed during the ELMs. The degradation of the edge pedestal gradient during an ELM is quantified using the edge pedestal gradient 2 ms before the ELM as a reference of the amplitude of the gradient. This technique has been applied to a JET database containing >700 pulses and >46 000 ELMs.