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Materials Science & Technology
The objectives of MSTD are: promote the advancement of materials science in Nuclear Science Technology; support the multidisciplines which constitute it; encourage research by providing a forum for the presentation, exchange, and documentation of relevant information; promote the interaction and communication among its members; and recognize and reward its members for significant contributions to the field of materials science in nuclear technology.
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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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Fusion Science and Technology
Latest News
College students help develop waste-measuring device at Hanford
A partnership between Washington River Protection Solutions (WRPS) and Washington State University has resulted in the development of a device to measure radioactive and chemical tank waste at the Hanford Site. WRPS is the contractor at Hanford for the Department of Energy’s Office of Environmental Management.
S. González, J. Vega, A. Murari, A. Pereira, M. Beurskens, JET-EFDA Contributors
Fusion Science and Technology | Volume 58 | Number 3 | November 2010 | Pages 755-762
Selected Paper from Sixth Fusion Data Validation Workshop 2010 (Part 2) | doi.org/10.13182/FST10-A10924
Articles are hosted by Taylor and Francis Online.
Massive amounts of data generated by fusion machines (such as JET) require developing automatic methods for data analysis. Edge-localized modes (ELMs) are instabilities occurring in the edge of H-mode plasmas. The aim of this work is to develop an automatic off-line method for identifying and locating ELMs. This method uses Universal Multi-Event Locator (UMEL) as the event locator. The combination of information from D emission and diamagnetic energy allows the recognition of single ELMs. This paper shows the way in which waveforms of a wide range of discharges can be treated and how UMEL is applied in order to identify and locate ELMs independently of the signal amplitudes. A large database of more than 1200 discharges has been used to test the performance of the method obtaining 226 751 ELMs.