arXiv subjects

JET Contributors

Publications and source records attributed to JET Contributors.

36 records · Page 2Linked to original sources

arXiv2020

Experimental studies of plasma-antenna coupling with the JET Alfven Eigenmode Active Diagnostic

This paper presents a dedicated study of plasma-antenna (PA) coupling with the Alfven Eigenmode Active Diagnostic (AEAD) in JET. Stable AEs and their resonant frequencies f, damping rates $γ$ < 0, and toroidal mode numbers n are measured for various PA separations and limiter versus X-point magnetic configurations. Two stable AEs are observed to be resonantly excited at distinct low and high frequencies in limiter plasmas. The values of f and n do not vary with PA separation. However, $\vertγ\vert$ increases with PA separation for the low-f, but not high-f, mode, yet this may be due to slightly different edge conditions. The high-f AE is detected throughout the transition from limiter to X-point configuration, though its damping rate increases; the low-f mode, on the other hand, becomes unidentifiable. The linear resistive MHD code CASTOR is used to simulate the frequency scan of an AEAD-like external antenna. For the limiter pulses, the high-f mode is determined to be an n = 0 GAE, while the low-f mode is likely an n = 2 TAE. During the transition from limiter to X-point configuration, CASTOR indicates that n = 1 and 2 EAEs are excited in the edge gap. These results extend previous experimental studies in JET and Alcator C-Mod; validate the computational work performed by Dvornova et al 2020 Phys. Plasmas 27 012507; and provide guidance for the optimization of PA coupling in upcoming JET energetic particle experiments, for which the AEAD will aim to identify the contribution of alpha particles to AE drive during the DT campaign.

physics.plasm-ph↗

arXiv2020

Toroidal and slab ETG instability dominance in the linear spectrum of JET-ILW pedestals

Local linear gyrokinetic simulations show that electron temperature gradient (ETG) instabilities are the fastest growing modes for $k_y ρ_i \gtrsim 0.1$ in the steep gradient region for a JET pedestal discharge (92174) where the electron temperature gradient is steeper than the ion temperature gradient. Here, $k_y$ is the wavenumber in the direction perpendicular to both the magnetic field and the radial direction, and $ρ_i$ is the ion gyroradius. At $k_y ρ_i \gtrsim 1$, the fastest growing mode is often a novel type of toroidal ETG instability. This toroidal ETG mode is driven at scales as large as $k_y ρ_i \sim (ρ_i/ρ_e) L_{Te} / R_0 \sim 1$ and at a sufficiently large radial wavenumber that electron finite Larmor radius effects become important; that is, $K_x ρ_e \sim 1$, where $K_x$ is the effective radial wavenumber. Here, $ρ_e$ is the electron gyroradius, $R_0$ is the major radius of the last closed flux surface, and $1/L_{Te}$ is an inverse length proportional to the logarithmic gradient of the equilibrium electron temperature. The fastest growing toroidal ETG modes are often driven far away from the outboard midplane. In this equilibrium, ion temperature gradient instability is subdominant at all scales and kinetic ballooning modes are shown to be suppressed by $\mathbf{ E} \times \mathbf{ B} $ shear. ETG modes are very resilient to $\mathbf{ E} \times \mathbf{ B}$ shear. Heuristic quasilinear arguments suggest that the novel toroidal ETG instability is important for transport.

physics.plasm-ph↗

arXiv2020

Deep Learning for the Analysis of Disruption Precursors based on Plasma Tomography

The JET baseline scenario is being developed to achieve high fusion performance and sustained fusion power. However, with higher plasma current and higher input power, an increase in pulse disruptivity is being observed. Although there is a wide range of possible disruption causes, the present disruptions seem to be closely related to radiative phenomena such as impurity accumulation, core radiation, and radiative collapse. In this work, we focus on bolometer tomography to reconstruct the plasma radiation profile and, on top of it, we apply anomaly detection to identify the radiation patterns that precede major disruptions. The approach makes extensive use of machine learning. First, we train a surrogate model for plasma tomography based on matrix multiplication, which provides a fast method to compute the plasma radiation profiles across the full extent of any given pulse. Then, we train a variational autoencoder to reproduce the radiation profiles by encoding them into a latent distribution and subsequently decoding them. As an anomaly detector, the variational autoencoder struggles to reproduce unusual behaviors, which includes not only the actual disruptions but their precursors as well. These precursors are identified based on an analysis of the anomaly score across all baseline pulses in two recent campaigns at JET.

physics.plasm-ph↗

arXiv2020

Results from the Alfvén Eigenmode Active Diagnostic during the 2019-2020 JET deuterium campaign

This paper presents results of extensive analysis of mode excitation observed during the operation of the Alfvén Eigenmode Active Diagnostic (AEAD) in the JET tokamak during the 2019-2020 deuterium campaign. Six of eight toroidally spaced antennas, each with independent power and phasing, were successful in actively exciting stable MHD modes in 479 plasmas. In total, 4768 magnetic resonances were detected with up to fourteen fast magnetic probes. In this work, we present the calculations of resonant frequencies $f_0$, damping rates $γ< 0$, and toroidal mode numbers $n$, spanning the parameter range $f_0 \approx$ 30 - 250 kHz, $-γ\approx$ 0 - 13 kHz, and $\vert n \vert \leq 30$. In general, good agreement is seen between the resonant and the calculated toroidal Alfvén Eigenmode frequencies, and between the toroidal mode numbers applied by the AEAD and estimated of the excited resonances. We note several trends in the database: the probability of resonance detection decreases with plasma current and external heating power; the normalized damping rate increases with edge safety factor but decreases with external heating. These results provide key information to prepare future experimental campaigns and to better understand the physics of excitation and damping of Alfvén Eigenmodes in the presence of alpha particles during the upcoming DT campaign, thereby extrapolating with confidence to future tokamaks.

physics.plasm-ph↗

arXiv2020

Assessing energy dependence of the transport of relativistic electrons in perturbed magnetic fields with orbit-following simulations

Experimental observations, as well as theoretical predictions, indicate that the transport of energetic electrons decreases with energy. This reduction in transport is attributed to finite orbit width (FOW) effects. Using orbit-following simulations in perturbed tokamak magnetic fields that have an ideal homogeneous stochastic layer at the edge, we quantify the energy dependence of energetic electrons transport and confirm previous theoretical estimates. However, using magnetic configurations characteristic of JET disruptions, we find no reduction in RE transport at higher energies, which we attribute to the mode widths being comparable to the minor radius, making the FOW effects negligible. Instead, the presence of islands and nonuniform magnetic perturbations are found to be more important. The diffusive-advective transport coefficients calculated in this work, based on simulations for electron energies 10 keV -- 100 MeV, can be used in reduced kinetic models to account for the transport due to the magnetic field perturbations.

physics.plasm-ph↗

arXiv2020

Recent progress towards a quantitative description of filamentary SOL transport

A summary of recent results on filamentary transport, mostly obtained in the ASDEX-Upgrade tokamak (AUG), is presented and discussed in an attempt to produce a coherent picture of SOL filamentary transport: A clear correlation is found between L-mode density shoulder formation in the outer midplane and a transition between the sheath limited and the inertial filamentary regimes. Divertor collisionality is found to be the parameter triggering the transition. A clear reduction of the ion temperature takes place in the far SOL after the transition, both for the background and the filaments. This coincides with a strong variation of the ion temperature distribution, which deviates from Gaussianity and becomes dominated by a strong peak below $5$ eV. The filament transition mechanism triggered by a critical value of collisionality seems to be generally applicable to inter-ELM H-mode plasmas, although a secondary threshold related to deuterium fueling is observed. EMC3-EIRENE simulations of neutral dynamics show that an ionization front near the main chamber wall is formed after the shoulder formation. Finally, a clear increase of SOL opacity to neutrals is observed associated to the shoulder formation. A common SOL transport framework is proposed account for all these results, and their potential implications for future generation devices are discussed.

physics.plasm-ph↗

arXiv2020

Fast modeling of turbulent transport in fusion plasmas using neural networks

We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. The database covers a wide range of realistic tokamak core parameters. Physical features such as the existence of a critical gradient for the onset of turbulent transport were integrated into the neural network training methodology. We have coupled QLKNN to the tokamak modelling framework JINTRAC and rapid control-oriented tokamak transport solver RAPTOR. The coupled frameworks are demonstrated and validated through application to three JET shots covering a representative spread of H-mode operating space, predicting turbulent transport of energy and particles in the plasma core. JINTRAC-QLKNN and RAPTOR-QLKNN are able to accurately reproduce JINTRAC-QuaLiKiz T i,e and n e profiles, but 3 to 5 orders of magnitude faster. Simulations which take hours are reduced down to only a few tens of seconds. The discrepancy in the final source-driven predicted profiles between QLKNN and QuaLiKiz is on the order 1%-15%. Also the dynamic behaviour was well captured by QLKNN, with differences of only 4%-10% compared to JINTRAC-QuaLiKiz observed at mid-radius, for a study of density buildup following the L-H transition. Deployment of neural network surrogate models in multi-physics integrated tokamak modelling is a promising route towards enabling accurate and fast tokamak scenario optimization, Uncertainty Quantification, and control applications.

physics.plasm-ph↗

arXiv2019

Gyrokinetic analysis and simulation of pedestals, to identify the culprits for energy losses using fingerprints

Fusion performance in tokamaks hinges critically on the efficacy of the Edge Transport Barrier (ETB) at suppressing energy losses. The new concept of fingerprints is introduced to identify the instabilities that cause the transport losses in the ETB of many of today's experiments, from widely posited candidates. Analysis of the Gyrokinetic-Maxwell equations, and gyrokinetic simulations of experiments, find that each mode type produces characteristic ratios of transport in the various channels: density, heat and impurities. This, together with experimental observations of transport in some channel, or, of the relative size of the driving sources of channels, can identify or determine the dominant modes causing energy transport. In multiple ELMy H-mode cases that are examined, these fingerprints indicate that MHD-like modes are apparently not the dominant agent of energy transport; rather, this role is played by Micro-Tearing Modes (MTM) and Electron Temperature Gradient (ETG) modes, and in addition, possibly Ion Temperature Gradient (ITG)/Trapped Electron Modes (ITG/TEM) on JET. MHD-like modes may dominate the electron particle losses. Fluctuation frequency can also be an important means of identification, and is often closely related to the transport fingerprint. The analytical arguments unify and explain previously disparate experimental observations on multiple devices, including DIII-D, JET and ASDEX-U, and detailed simulations of two DIII-D ETBs also demonstrate and corroborate this.

physics.plasm-ph↗

arXiv2018

Observations and modelling of ion cyclotron emission observed in JET plasmas using a sub-harmonic arc detection system during ion cyclotron resonance heating

Measurements are reported of electromagnetic emission close to the cyclotron frequency of energetic ions in JET plasmas heated by waves in the ion cyclotron range of frequencies (ICRF). Hydrogen was the majority ion species in all of these plasmas. The measurements were obtained using a sub-harmonic arc detection (SHAD) system in the transmission lines of one of the ICRF antennas. The measured ion cyclotron emission (ICE) spectra were strongly filtered by the antenna system, and typically contained sub-structure, consisting of sets of peaks with a separation of a few kHz, suggesting the excitation of compressional Alfven eigenmodes (CAEs) closely spaced in frequency. In most cases the energetic ions can be clearly identified as ICRF-accelerated He-3 minority ions, although in two pulses the emission may have been produced by energetic He-4 ions, originating from third harmonic ICRF wave acceleration. It is proposed that the emission close to the He-3 cyclotron frequency was produced by energetic ions of this species undergoing drift orbit excursions to the outer midplane plasma edge. Particle-in-cell and hybrid (kinetic ion, fluid electron) simulations using plasma parameters corresponding to edge plasma conditions in these JET pulses, and energetic particle parameters inferred from the cyclotron resonance location, indicate strong excitation of waves at He-3 cyclotron harmonics, including the fundamental, which is identified with the observed emission. These results underline the potential importance of ICE measurements as a method of studying confined fast particles that are strongly suprathermal but have insufficient energies or are not present in sufficient numbers to excite detectable levels of gamma-ray emission or other collective instabilities.

physics.plasm-ph↗

arXiv2018

Non-Maxwellian fast particle effects in gyrokinetic GENE simulations

Fast ions have recently been found to significantly impact and partially suppress plasma turbulence both in experimental and numerical studies in a number of scenarios. Understanding the underlying physics and identifying the range of their beneficial effect is an essential task for future fusion reactors, where highly energetic ions are generated through fusion reactions and external heating schemes. However, in many of the gyrokinetic codes fast ions are, for simplicity, treated as equivalent-Maxwellian-distributed particle species, although it is well known that to rigorously model highly non-thermalised particles, a non-Maxwellian background distribution function is needed. To study the impact of this assumption, the gyrokinetic code GENE has recently been extended to support arbitrary background distribution functions which might be either analytic, e.g. slowing down and bi-Maxwellian, or obtained from numerical fast ion models. A particular JET plasma with strong fast-ion related turbulence suppression is revised with these new code capabilities both with linear and nonlinear gyrokinetic simulations. It appears that the fast ion stabilization tends to be less strong but still substantial with more realistic distributions, and this improves the quantitative power balance agreement with experiments.

physics.plasm-ph↗

arXiv2017

Tractable flux-driven temperature, density, and rotation profile evolution with the quasilinear gyrokinetic transport model QuaLiKiz

Quasilinear turbulent transport models are a successful tool for prediction of core tokamak plasma profiles in many regimes. Their success hinges on the reproduction of local nonlinear gyrokinetic fluxes. We focus on significant progress in the quasilinear gyrokinetic transport model QuaLiKiz [C. Bourdelle et al. 2016 Plasma Phys. Control. Fusion 58 014036], which employs an approximated solution of the mode structures to significantly speed up computation time compared to full linear gyrokinetic solvers. Optimization of the dispersion relation solution algorithm within integrated modelling applications leads to flux calculations $\times10^{6-7}$ faster than local nonlinear simulations. This allows tractable simulation of flux-driven dynamic profile evolution including all transport channels: ion and electron heat, main particles, impurities, and momentum. Furthermore, QuaLiKiz now includes the impact of rotation and temperature anisotropy induced poloidal asymmetry on heavy impurity transport, important for W-transport applications. Application within the JETTO integrated modelling code results in 1s of JET plasma simulation within 10 hours using 10 CPUs. Simultaneous predictions of core density, temperature, and toroidal rotation profiles for both JET hybrid and baseline experiments are presented, covering both ion and electron turbulence scales. The simulations are successfully compared to measured profiles, with agreement mostly in the 5-25% range according to standard figures of merit.

physics.plasm-ph↗

arXiv2017

Interpretation of scrape-off layer profile evolution and first-wall ion flux statistics on JET using a stochastic framework based on filamentary motion

This paper presents the use of a novel modelling technique based around intermittent transport due to filament motion, to interpret experimental profile and fluctuation data in the scrape-off layer (SOL) of JET during the onset and evolution of a density profile shoulder. A baseline case is established, prior to shoulder formation, and the stochastic model is shown to be capable of simultaneously matching the time averaged profile measurement as well as the PDF shape and autocorrelation function from the ion-saturation current time series at the outer wall. Aspects of the stochastic model are then varied with the aim of producing a profile shoulder with statistical measurements consistent with experiment. This is achieved through a strong localised reduction in the density sink acting on the filaments within the model. The required reduction of the density sink occurs over a highly localised region with the timescale of the density sink increased by a factor of 25. This alone is found to be insufficient to model the expansion and flattening of the shoulder region as the density increases, which requires additional changes within the stochastic model. An example is found which includes both a reduction in the density sink and filament acceleration and provides a consistent match to the experimental data as the shoulder expands, though the uniqueness of this solution can not be guaranteed. Within the context of the stochastic model, this implies that the localised reduction in the density sink can trigger shoulder formation, but additional physics is required to explain the subsequent evolution of the profile.

physics.plasm-ph↗

arXiv2017

Deep learning for plasma tomography using the bolometer system at JET

Deep learning is having a profound impact in many fields, especially those that involve some form of image processing. Deep neural networks excel in turning an input image into a set of high-level features. On the other hand, tomography deals with the inverse problem of recreating an image from a number of projections. In plasma diagnostics, tomography aims at reconstructing the cross-section of the plasma from radiation measurements. This reconstruction can be computed with neural networks. However, previous attempts have focused on learning a parametric model of the plasma profile. In this work, we use a deep neural network to produce a full, pixel-by-pixel reconstruction of the plasma profile. For this purpose, we use the overview bolometer system at JET, and we introduce an up-convolutional network that has been trained and tested on a large set of sample tomograms. We show that this network is able to reproduce existing reconstructions with a high level of accuracy, as measured by several metrics.

stat.ML↗

arXiv2016

Universality of the ion flux to the JET outer wall

Universality in the ion flux to the JET outer-wall is observed in outerwall limiter mounted Langmuir probe (OLP) time-series across a large range of plasma current and line-averaged density during Ohmically heated horizontal target L-mode plasmas. The mean, M, and the standard deviation, sigma, of the ion-saturation current measured by the OLP show systematic variation with plasma current and density. Both increase as either plasma current decreases and/or density increases. Upon renormalization, achieved by subtraction of M and rescaling by sigma, the probability distribution functions (PDFs) of each signal collapse approximately onto a single curve. The shape of the curve deviates from a distribution in the tail of the PDF and is better described by a log-normal distribution. The collapse occurs over 4 decades of the ordinate which, given the wide parameter space over which the data spans, is a strong indication of universality.

physics.plasm-ph↗

arXiv2015

The role of MHD in causing impurity peaking in JET Hybrid plasmas

In Hybrid plasma operation in JET with its ITER-like wall (JET-ILW) it is found that n>1 tearing activity can significantly enhance the rate of on-axis peaking of tungsten impurities, which in turn significantly degrades discharge performance. Core n=1 instabilities can be beneficial in removing tungsten impurities from the plasma core (e.g. sawteeth or fishbones), but can conversely also degrade core confinement (particularly in combination with simultaneous n=3 activity). The nature of MHD instabilities in JET Hybrid discharges, with both its previous Carbon wall and subsequent JET-ILW, is surveyed statistically and the character of the instabilities is examined. Possible qualitative models for how the n>1 islands can enhance on-axis tungsten transport accumulation processes are presented.

physics.plasm-ph↗

arXiv2015

Bayesian modelling of the emission spectrum of the JET Li-BES system

A Bayesian model of the emission spectrum of the JET lithium beam has been developed to infer the intensity of the Li I (2p-2s) line radiation and associated uncertainties. The detected spectrum for each channel of the lithium beam emission spectroscopy (Li-BES) system is here modelled by a single Li line modified by an instrumental function, Bremsstrahlung background, instrumental offset, and interference filter curve. Both the instrumental function and the interference filter curve are modelled with non-parametric Gaussian processes. All free parameters of the model, the intensities of the Li line, Bremsstrahlung background, and instrumental offset, are inferred using Bayesian probability theory with a Gaussian likelihood for photon statistics and electronic background noise. The prior distributions of the free parameters are chosen as Gaussians. Given these assumptions, the intensity of the Li line and corresponding uncertainties are analytically available using a Bayesian linear inversion technique. The proposed approach makes it possible to extract the intensity of Li line without doing a separate background subtraction through modulation of the Li beam.

physics.plasm-ph↗

arXiv2015

Experimental validation of a filament transport model in turbulent magnetized plasmas

In a wide variety of natural and laboratory magnetized plasmas, filaments appear as a result of interchange instability. These convective structures substantially enhance transport in the direction perpendicular to the magnetic field. According to filament models, their propagation may follow different regimes depending on the parallel closure of charge conservation. This is of paramount importance in magnetic fusion plasmas, as high collisionality in the scrape-off layer may trigger a regime transition leading to strongly enhanced perpendicular particle fluxes. This work reports for the first time on an experimental verification of this process, linking enhanced transport with a regime transition as predicted by models. Based on these results, a novel scaling for global perpendicular particle transport in reactor relevant tokamaks such as ASDEX-Upgrade and JET is found, leading to important implications for next generation fusion devices.

physics.plasm-ph↗

arXiv2015

The global build-up to intrinsic ELM bursts seen in divertor full flux loops in Jet

A global signature of the build-up to an intrinsic ELM is found in the phase of signals measured in full flux azimuthal loops in the divertor region of JET. Full flux loop signals provide a global measurement proportional to the voltage induced by changes in poloidal magnetic flux; they are electromagnetically induced by the dynamics of spatially integrated current density. We perform direct time-domain analysis of the high time-resolution full flux loop signals VLD2 and VLD3. We analyze plasmas where a steady H-mode is sustained over several seconds, during which all the observed ELMs are intrinsic; there is no deliberate intent to pace the ELMing process by external means. ELM occurrence times are determined from the Be II emission at the divertor. We previously found that the occurrence times of intrinsic ELMs correlate with specific phases of the VLD2 and VLD3 signals. Here, we investigate how the VLD2 and VLD3 phases vary with time in advance of the ELM occurrence time. We identify a build-up to the ELM in which the VLD2 and VLD3 signals progressively align to the phase at which ELMs preferentially occur, on a ~ 2 -5ms timescale. At the same time, the VLD2 and VLD3 signals become phase synchronized with each other, consistent with the emergence of coherent global dynamics in the integrated current density. In a plasma that remains close to a global magnetic equilibrium, this can reflect bulk displacement or motion of the plasma. This build-up signature to an intrinsic ELM can be extracted from a time interval of data that does not extend beyond the ELM occurrence time, so that these full flux loop signals could assist in ELM prediction or mitigation.

physics.plasm-ph↗