NDLI: Identifying JET instabilities with neural networks

Content Provider	IEEE Xplore Digital Library
Author	Murari, A. Buscarino, A. Fortuna, L. Frasca, M. Iachello, M. Mazzitelli, G.
Copyright Year	2012
Description	Author affiliation: Frascati Research Center, Management of Large Experiment Facilities FTU group, ENEA, Frascati, Rome - Italy (Buscarino, A.) \|\| Dipartimento di Ingegneria Elettrica Elettronica e Informatica, Universit degli Studi di Catania, 95125 Catania, Italy (Fortuna, L.; Frasca, M.; Iachello, M.; Mazzitelli, G.) \|\| Associazione EURATOM-ENEA per la Fusione, Consorzio RFX, 4-35127 Padova, Italy (Murari, A.)
Abstract	The identification of plasma instabilities occurring during experimental pulses is of particular relevance for avoiding dangerous events in high performance discharges. In order to predict the onset of plasma instabilities, an identification method, based on the use of artificial neural networks (ANNs), has been applied. The potential of the networks to identify the dynamics of edge-localized mode (ELM) and sawtooth instabilities has been first tested using synthetic data obtained through a suitable mathematical model. The networks have then been applied to experimental measurement from JET pulses. An appropriate selection of the networks topology allows identifying quite well the time evolution of the edge temperature and of magnetic fields, considered the best indicators of the ELMs. A quite limited number of periodic oscillations are used to train the networks, which then manage to follow quite well the dynamics of the instabilities. Furthermore, a careful analysis of the various terms appearing in the rule identified by the ANNs gives clear indications about the nature of these instabilities and their dynamical behavior.
Starting Page	932
Ending Page	935
File Size	621860
Page Count	4
File Format	PDF
ISBN	9781467307826
ISSN	21588473
e-ISBN	9781467307840
DOI	10.1109/MELCON.2012.6196580
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-25
Publisher Place	Tunisia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Temperature measurement Network topology Topology Neural networks Mathematical model Plasmas Neurons
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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