This paper reports the first quantitative analysis of the measurements of the damping rate (γ/ω) for stable Alfvén Eigenmodes (AEs) with toroidal mode number (n) in the range |n|=3÷15 as function of the edge plasma elongation (κ 95 ). We find that the damping rate γ/ω vs. κ 95 for medium-n Toroidal AEs, with n=3 and n=7, increases for increasing elongation, i.e. its scaling vs. κ 95 follows the same trend previously measured and explained theoretically for the n=1 and n=2 TAE modes.Theoretical analysis of the measurements for the n=3 TAEs has been performed using the LEMan code. The results are in excellent agreement for all the magnetic configurations where there is only a very minor up/down asymmetry in the poloidal cross-section of the plasma. These experimental results further confirm the possibility of using the edge shape parameters as a real-time actuator for control of the stability of alpha-particles driven AEs in burning plasma experiments, such as ITER. PACS Classification scheme: D0, Te.

Abstract. The stability of Alfvén eigenmodes (AEs) is studied experimentally in the JET tokamak by observing the plasma response to antenna-driven frequency-sweeping perturbations at the plasma edge. During the 2008/9 experimental campaigns, the complete set of the new antennas was operated and AEs with toroidal mode numbers (n) in the intermediate-n range were excited under various plasma conditions. In this paper, we describe the results of the work achieved on the technical aspects of the diagnostic. The antenna currents have been optimized to improve the antenna-plasma coupling. The mode-tracking system has been upgraded for real-time targeting of modes with specific n. As an example of the optimized performance of the diagnostic, the paper concludes with a report on the damping rates of n = 3 − 5 toroidal AEs (TAEs) that were measured dynamically while the background plasma parameters were evolving in time.

In this work we report the successful application of an innovative method, based on the Sparse Representation of signals, to perform a real-time, unsupervised detection of the individual components in a frequency degenerate, multi-harmonic spectrum, using a small number of data un-evenly sampled in the spatial domain. This method has been developed from its original applications in astronomy, and is now routinely used in the JET thermonuclear fusion experiment to obtain the decomposition of a spectrum of high-frequency (~10-500kHz range) magnetic instabilities with a sub-ms time resolution, allowing the real-time tracking of its individual components as the plasma background evolves. This work opens a path towards developing real-time control tools for electro-magnetic instabilities in future fusion devices aimed at achieving a net energy gain. More generally, the speed and accuracy of this algorithm is recommended for instances of physics measurements and control engineering where an unsupervised, real-time decomposition of a degenerate signal is required from a small number of data.

We present the real-time VME system used to detect and track MHD instabilities, and particularly Alfvén Eigenmodes, on the JET tokamak [J.Wesson, Tokamaks, 3 rd edition, (Oxford Science Publication, Oxford, 2003), p.617]. This system runs on a 1kHz clock cycle, and allows performing a real-time, unsupervised and blind detection, decomposition and tracking of the individual components in a frequency-degenerate, multi-harmonic spectrum, using a small number of input data which are unevenly sampled in the spatial domain. This makes it possible to follow in real-time the detected modes as the plasma background evolves, and measure in real-time their frequency, damping rate, toroidal mode-number and relative amplitude. The successful implementation of this system opens a clear path towards developing real-time control tools for electro-magnetic instabilities in future fusion devices aimed at achieving a net energy gain, such as ITER [J.Wesson, Tokamaks,3 1) Introduction.The problem of blind and unsupervised real-time detection of the different components in a multiharmonics spectrum using a small number of input data which are un-evenly sampled in the spatial domain is now becoming one of the main aspects required for machine protection and the control of plasma discharges in thermonuclear fusion experiments, and a wealth of literature is available on this subject (for some examples see Chapter3 and Chapter7 and references therein in Ref. [1] and Chapter2 and references therein in Ref. [2]). The method routinely used for this analysis involves sampling of a (relatively) small set of magnetic and non-magnetic signals, often containing some spatial periodicities so as to enhance or eliminate detection of certain components when the input signals are processed appropriately. A real-time algorithm then runs, and a global alarm is generated which may trigger a feedback control mechanism under certain specified conditions. The main drawback of this method is that it can only detect modes when they have become unstable, i.e. when they may have already had some, possibly detrimental, effect on the plasma background parameters.Conversely, an innovative method has been employed for quite some time now on the JET tokamak [3], which combines active excitation of magnetic field perturbations with a very small amplitude at the plasma edge (maximum intensity max(|B DRIVEN |)~0.1G, i.e. 10 5 times smaller than the typical value of the toroidal magnetic field in JET, B TOR~( 1-3)T) with synchronous real-time detection of the driven perturbations. This is the so-called Alfvén Eigenmodes (AEs) Active Diagnostic (AEAD) system [4,5], of which the real-time Alfvén Eigenmodes Local Manager (AELM) constitutes one essential, moreover worldwide unique component. This diagnostic system allows the real-time detection and tracking of the driven modes, usually magneto-hydrodynamic (MHD) Eigenmodes supported by the plasma, when still stable, i.e. when the modes have a positive damping >0, and have not yet caused any effect on the plas...