Evidence for a new path to the self-sustainment of the thermonuclear fusion in magnetically confined burning plasma experiments

In this work we provide the first explanation for observations made in 1997 on the Joint European Torus of unexpected ion heating with fusion-born alpha particles occurring over time scales much shorter than those theoretically foreseen. We demonstrate that non-thermal alpha particles above a critical concentration stabilize ion-drift-wave turbulence, therefore significantly reducing one of the main energy loss channels for thermal ions. As such ion heating occurs over times scales much shorter than those classically predicted, this mechanism opens new prospects on additional paths for the self-sustainment of thermonuclear fusion reactions in magnetically confined plasmas

A phenomenological explanation for the anomalous ion heating observed in the JET alpha-heating experiment of 1997

In the so-called alpha-heating experiment performed on the JET tokamak during the deuterium-tritium campaign of 1997, the ion temperature was found to be far exceeding (both in absolute value and in its rise time) the level that could have been expected from direct collisional heating by the fusion-born alpha particles themselves and energy equi-partition with the electrons. To date, no explanation has been put forward for this long standing puzzle, despite much work having been performed on this subject in the early 2000s. Two analysis methods that have recently become available have been employed to re-analyse these observations of an anomalous ion heating. First, an algorithm based on the Sparse Representation of Signals has been used to analyse magnetic, reflectometry and electron cyclotron emission measurements of the turbulence spectra in the drift-wave range of frequencies. This analysis has then been complemented with turbulence simulations performed with the GENE code. We find, both experimentally and in the simulations, that the presence of a minority, but sufficiently large, population of fusion-born alpha particles that have not yet fully thermalized stabilizes the turbulence in the ion-drift direction, but practically does not affect the turbulence in the electron-drift direction. We link such stabilization of the ion-drift-wave turbulence to the increase in the ion temperature above the level achieved in similar discharges that did not have (at all or enough) alpha particles. When the fusion-born alpha particles have fully thermalized, the turbulence spectrum in the ion-drift direction re-appears at somewhat larger amplitudes, which we link to the ensuing reduction in the ion temperature. This phenomenological dynamics fully corresponds to the actual experimental observations. By taking into account an effect of the alpha particles that had not been previously considered, our new analysis finally presents a phenomenological explanation for the so-far-unexplained anomalous ion heating observed in the JET alpha-heating experiment of 1997. Through the formulation of an empirical criterion for ion-drift-wave turbulence stabilization by fusion-born alpha particles, we also show why similar observations were not made in the other deuterium-tritium experiments run so far in JET and TFTR. This allows assessing the operational domain for this stabilization mechanism for ion-drift-wave turbulence in future burning plasma experiments such as ITER, which may open a new path towards the sustainment of a high energy gain in such forthcoming devices

Sparse representation of signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Efficient, real-time and automated data analysis is one of the key elements for achieving scientific success in complex engineering and physical systems, of which two examples are the JET and ITER tokamaks. One problem which is common to these fields is the determination of pulsation modes from irregularly sampled time-series. To this end, there is a wealth of signal processing techniques that are being applied to post-pulse and real-time data analysis in such complex systems. Here we wish to present a review of the applications of a method based on the Sparse Representation of Signals, using examples of the synergies that can be exploited when combining ideas and methods from very different fields, such as astronomy and astrophysics and thermonuclear fusion plasmas. Examples of this work in astronomy and astrophysics are the analysis of pulsation modes in various classes of stars and the orbit determination software of the Pioneer spacecrafts. Two examples of this work in thermonuclear fusion plasmas are the detection of magneto-hydrodynamic instabilities, which is now performed routinely in JET in real-time on a sub-millisecond time-scale, and the studies leading to the optimization of the magnetic diagnostic system in ITER and TCV. These questions have been solved formulating them as inverse problems, despite the fact that these applicative frameworks are extremely different from the classical use of Sparse Representations, on both the theoretical and computational points of view. Requirements, prospects and ideas for the signal processing and real-time data analysis applications of this method to routine operation of ITER will also be discussed. Finally, a very recent development has been an attempt at the application of this method to the deconvolution of the measurement of electric potential performed during a ground-based survey of a proto-Villanovian necropolis in central Italy

Sparse representation of signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

International audienc

Sparse representation of signals: From astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Efficient, real-time and automated data analysis is one of the key elements for achieving scientific success in complex engineering and physical systems, two examples of which include the JET and ITER tokamaks. One problem which is common to these fields is the determination of the pulsation modes from an irregularly sampled time series. To this end, there are a wealth of signal processing techniques that are being applied to post-pulse and real-time data analysis in such complex systems. Here, we wish to present a review of the applications of a method based on the sparse representation of signals, using examples of the synergies that can be exploited when combining ideas and methods from very different fields, such as astronomy, astrophysics and thermonuclear fusion plasmas. Examples of this work in astronomy and astrophysics are the analysis of pulsation modes in various classes of stars and the orbit determination software of the Pioneer spacecraft. Two examples of this work in thermonuclear fusion plasmas include the detection of magneto-hydrodynamic instabilities, which is now performed routinely in JET in real-time on a sub-millisecond time scale, and the studies leading to the optimization of the magnetic diagnostic system in ITER and TCV. These questions have been solved by formulating them as inverse problems, despite the fact that these applicative frameworks are extremely different from the classical use of sparse representations, from both the theoretical and computational point of view. The requirements, prospects and ideas for the signal processing and real-time data analysis applications of this method to the routine operation of ITER will also be discussed. Finally, a very recent development has been the attempt to apply this method to the deconvolution of the measurement of electric potential performed during a ground-based survey of a proto-Villanovian necropolis in central Italy