Amorphous/crystalline Fe55Ni20Cu5P10Si5B5composite produced by two-component melt–spinning

Krzysztof Ziewiec , Mirosława Wojciechowska , Kristian Prusik , Jarosław Ferenc , Dariusz Mucha , Aneta Ziewiec

Abstract

The aim of this paper is to present a signal processing algorithm that, applied to the raw Locked Mode signal, allows us to obtain a disruption indicator in principle exploitable on different tokamaks. A common definition of such an indicator for different machines would facilitate the development of portable systems for disruption prediction, which is becoming of increasingly importance for the next tokamak generations. Moreover, the indicator allows us to overcome some intrinsic problems in the diagnostic system such as drift and offset. The behavior of the proposed indicator as disruption predictor, based on crossing optimized thresholds of the signal amplitude, has been analyzed using data of both JET and ASDEX Upgrade experiments. A thorough analysis of the disruption prediction performance shows how the indicator is able to recover some missed and tardy detections of the raw signal. Moreover, it intervenes and corrects premature or even wrong alarms due to, e.g., drifts and/or offsets. © 2018 Elsevier B.V.
Author Krzysztof Ziewiec - Uniwersytet Pedagogiczny im. Komisji Edukacji Narodowej w Krakowie
Krzysztof Ziewiec,,
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, Mirosława Wojciechowska - Uniwersytet Pedagogiczny im. Komisji Edukacji Narodowej w Krakowie
Mirosława Wojciechowska,,
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, Kristian Prusik - University of Silesia (UŚ)
Kristian Prusik,,
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, Jarosław Ferenc (FMSE / DCFM)
Jarosław Ferenc,,
- Division of Construction and Functional Materials
, Dariusz Mucha - Instytut Katalizy i Fizykochemii Powierzchni im. Jerzego Habera Polskiej Akademii Nauk (IKiFP PAN)
Dariusz Mucha,,
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, Aneta Ziewiec - AGH University of Science and Technology (AGH)
Aneta Ziewiec,,
-
Journal seriesMaterials Science and Technology, ISSN 0267-0836, e-ISSN 1743-2847
Issue year2020
Vol36
No9
Pages982-988
Publication size in sheets0.5
Keywords in EnglishDisruption indicators; Disruption prediction; Feature extraction; Locked mode signal; Tokamak
ASJC Classification2210 Mechanical Engineering; 2211 Mechanics of Materials; 2500 General Materials Science; 3104 Condensed Matter Physics
DOIDOI:10.1080/02670836.2019.1603900
URL https://doi.org/10.1080/02670836.2019.1603900
Languageen angielski
File
MaterSciTechnol=in_press=(2019)=J.Ferenc.pdf 2.04 MB
Score (nominal)70
Score sourcejournalList
ScoreMinisterial score = 70.0, 24-08-2020, ArticleFromJournal
Publication indicators Scopus Citations = 0; WoS Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2017 = 1.004; WoS Impact Factor: 2018 = 1.938 (2) - 2018=1.882 (5)
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