Visualization of Fast Ion Phase-Space Flow Driven by Alfvén Instabilities

Fast ion phase-space flow, driven by Alfvén eigenmodes (AEs), is measured by an imaging neutral particle analyzer in the DIII-D tokamak. The flow firstly appears near the minimum safety factor at the injection energy of neutral beams, and then moves radially inward and outward by gaining and losing energy, respectively. The flow trajectories in phase space align well with the intersection lines of the constant magnetic moment surfaces and constant E−(ω/n)Pζ surfaces, where E, Pζ are the energy and canonical toroidal momentum of ions; ω and n are angular frequencies and toroidal mode numbers of AEs. It is found that the flow is so destructive that the thermalization of fast ions is no longer observed in regions of strong interaction. The measured phase-space flow is consistent with nonlinear hybrid kinetic-magnetohydrodynamics simulation. Calculations of the relatively narrow phase-space islands reveal that fast ions must transition between different flow trajectories to experience large-scale phase-space transport

Fast particle-driven ion cyclotron emission (ICE) in tokamak plasmas and the case for an ICE diagnostic in ITER

The detection of fast particle-driven waves in the ion cyclotron frequency range (ion cyclotron emission or ICE) could provide a passive, non-invasive diagnostic of confined and escaping fast particles (fusion α-particles and beam ions) in ITER, and would be compatible with the high radiation environment of deuterium–tritium plasmas in that device. Recent experimental results from ASDEX Upgrade and DIII-D demonstrate the efficacy of ICE as a diagnostic of different fast ion species and of fast ion losses, while recent particle-in-cell (PIC) and hybrid simulations provide a more exact comparison with measured ICE spectra and open the prospect of exploiting ICE more fully as a fast ion diagnostic in future experiments. In particular the PIC/hybrid approach should soon make it possible to simulate the nonlinear physics of ICE in full toroidal geometry. Emission has been observed previously at a wide range of poloidal angles, so there is flexibility in the location of ICE detectors. Such a detector could be implemented in ITER by installing a small toroidally orientated loop near the plasma edge or by adding a detection capability to the ion cyclotron resonance heating (ICRH) antennae. In the latter case, the antenna could be used simultaneously to heat the plasma and detect ICE, provided that frequencies close to those of the ICRH source are strongly attenuated in the detection system using a suitable filter. Wavenumber information, providing additional constraints on the fast ion distribution exciting the emission, could be obtained by measuring ICE using a toroidally distributed array of detectors or different straps of the ICRH antenna

Exploring data-driven models for spatiotemporally local classification of Alfven eigenmodes

Alfven eigenmodes (AEs) are an important and complex class of plasma dynamics commonly observed in tokamaks and other plasma devices. In this work, we manually labeled a small database of 26 discharges from the DIII-D tokamak in order to train simple neural-network-based models for classifying AEs. The models provide spatiotemporally local identification of four types of AEs by using an array of 40 electron cyclotron emission (ECE) signals as inputs. Despite the minimal dataset, this strategy performs well at spatiotemporally localized classification of AEs, indicating future opportunities for more sophisticated models and incorporation into real-time control strategies. The trained model is then used to generate spatiotemporally-resolved labels for each of the 40 ECE measurements on a much larger database of 1112 DIII-D discharges. This large set of precision labels can be used in future studies for advanced deep predictors and new physical insights

"BAAE" instabilities observed without fast ion drive

The instability that was previously identified [Phys. Pl. 16 (2009) 056107] as a fast-ion driven beta-induced Alfven-acoustic eigenmode (BAAE) in DIII-D was misidentified. In a dedicated experiment, low frequency modes (LFM) with characteristic ``Christmas light\u27\u27 patterns of brief instability linked to the safety factor evolution occur in plasmas with electron temperature T_e >= 2.1 keV but modest beta. To isolate the importance of different driving gradients on these modes, the electron cyclotron heating power and 80 keV, sub-Alfvenic neutral beams are altered for 50-100 ms durations in reproducible discharges. Although beta-induced Alfven eigenmodes and reversed-shear Alfven eigenmodes stabilize when beam injection ceases (as expected for a fast-ion driven instability), the low frequency modes that were called BAAEs persist. Data mining reveals that characteristic LFM instabilities can occur in discharges with no beam heating but strong electron cyclotron heating. A large database of over 1000 discharges shows that LFMs are only unstable in plasmas with hot electrons but modest overall beta. The experimental LFMs have low frequencies (comparable to diamagnetic drift frequencies) in the plasma frame, occur near the minimum of the safety factor q_{min}, and appear when q_{min} is close to rational values. Theoretical analysis suggests that the LFMs are a low frequency reactive instability of predominately Alfvenic polarization

Alfven eigenmode classification based on ECE diagnostics at DIII-D using deep recurrent neural networks

Modern tokamaks have achieved significant fusion production, but further progress towards steady-state operation has been stymied by a host of kinetic and MHD instabilities. Control and identification of these instabilities is often complicated, warranting the application of data-driven methods to complement and improve physical understanding. In particular, Alfven eigenmodes are a class of ubiquitous mixed kinetic and MHD instabilities that are important to identify and control because they can lead to loss of confinement and potential damage to the walls of a plasma device. In the present work, we use reservoir computing networks to classify Alfven eigenmodes in a large labeled database of DIII-D discharges, covering a broad range of operational parameter space. Despite the large parameter space, we show excellent classification and prediction performance, with an average hit rate of 91% and false alarm ratio of 7%, indicating promise for future implementation with additional diagnostic data and consolidation into a real-time control strategy

Evaluation of an Energetic Particle Profile Using a Tangential-FIDA Diagnostic in the Large Helical Device

A tangential Fast-Ion D Alpha (FIDA) diagnostic is applied to the Large Helical Device (LHD) in order to observe energetic distribution of toroidal circulating energetic particles which are produced by tangential Negative Neutral Beams (NNB). A perpendicular Positive NB (PNB) is used as the diagnostic probe beam of the tangential-FIDA diagnostic in this observation geometry. In order to assess the appropriateness of the tangential-FIDA diagnostic, the experimental result was compared with a Silicon-diode-based Fast Neutral Analyzer (Si-FNA) which was installed on the same line of sight. As a result of the comparison, the tangential-FIDA and the Si-FNA experimental data obtained good linearity in the energy region from 60 keV to 180 keV. In addition, an enhanced FIDASIM was applied for analyzing the FIDA on the three-dimensional magnetic configuration fusion device

Active control of Alfvén eigenmodes in magnetically confined toroidal plasmas

Alfvén waves are electromagnetic perturbations inherent to magnetized plasmas that can be driven unstable by a free energy associated with gradients in the energetic particles' distribution function. The energetic particles with velocities comparable to the Alfvén velocity may excite Alfvén instabilities via resonant wave–particle energy and momentum exchange. Burning plasmas with large population of fusion born super-Alfvénic alpha particles in magnetically confined fusion devices are prone to excite weakly-damped Alfvén eigenmodes (AEs) that, if allowed to grow unabated, can cause a degradation of fusion performance and loss of energetic ions through a secular radial transport. In order to control the fast-ion distribution and associated Alfvénic activity, the fusion community is currently searching for external actuators that can control AEs and energetic ions in the harsh environment of a fusion reactor. Most promising control techniques are based on (i) variable fast-ion sources to modify gradients in the energetic particles' distribution, (ii) localized electron cyclotron resonance heating to affect the fast-ion slowing-down distribution, (iii) localized electron cyclotron current drive to modify the equilibrium magnetic helicity and thus the AE existence criteria and damping mechanisms, and (iv) externally applied 3D perturbative fields to manipulate the fast-ion distribution and thus the wave drive. Advanced simulations help to identify the key physics mechanisms underlying the observed AE mitigation and suppression and thus to develop robust control techniques towards future burning plasmas.This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 and 2019–2020 under grant agreement No 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission. Support by US DOE and ITER-CN is also acknowledged. The support from the FP7 People: Marie-Curie Actions (Grant No. 321455) and the Spanish Ministry of Economy and Competitiveness (Grants No. RYC-2011-09152, No. FIS2015-69362-P) is gratefully acknowledged. The work of AVM was funded by the Russian Science Foundation, project 14-22-00193, and was partly supported by the Competitiveness Program of NRNU MEPhI.Peer ReviewedPostprint (published version