Authors: A. Murari, J. Vega, G. De Arcas, G. Vagliasindi, JET EFDA contributors
Addresses: Consorzio RFX – Associazione EURATOM ENEA per la Fusione, Corso Stati Uniti 4, Padova, Italy. ' Asociacion EURATOM/CIEMAT para Fusion, Avda. Complutense, 22, 28040, Madrid, Spain. ' Grupo de Investigacion en Instrumentacion y Acustica Aplicada, Universidad Politecnica de Madrid, Crta. Valencia Km 7, 28031, Madrid, Spain. ' Universita degli Studi di Catania – Dip. di Ingegneria Elettrica, Elettronica e dei Sistemi, v.le A. Doria 6, 95125, Catania, Italy. ' JET-EFDA, Culham Science Centre, OX14 3DB, Abingdon, UK
Abstract: Thermonuclear plasmas are complex and highly nonlinear physical objects and, therefore, are the most advanced present-day devices for the study of magnetic confinement fusion. Thousands of signals have to be acquired for each experiment in order to progress the understanding that is indispensable for the final reactor. On the other hand, the resulting massive databases, more than 40 Tbytes in the case of the Joint European Torus (JET) Joint Undertaking, pose significant problems. In this paper, solutions to reduce the sheer amount of data by different compression techniques and adaptive sampling frequency architectures are presented. As an example of methods capable of providing significant help in data analysis and real-time control, a Classification and Regression Tree (CART) software is applied to the problem of regime identification to discriminate in an automatic way whether the plasma is in the Low (L) or High (H) confinement mode.
Keywords: soft computing; classification trees; regression trees; CARTs; data compression; decimation; magnetic confinement nuclear fusion; information processing; thermonuclear plasmas; nuclear energy; nuclear power.
International Journal of Nuclear Knowledge Management, 2010 Vol.4 No.1, pp.3 - 9
Published online: 22 Jan 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article