Operation at high performance in optimized shear plasmas in JET

Heating during the early part of the current rise phase gives a low or negative magnetic shear (= 0741-3335/40/6/020/img27(dq/dr)) in the centre of JET plasmas. Under these conditions the confinement improves with high additional heating power heating during the current ramp-up phase of the discharge. The reduction in the transport manifests itself as a peaking of the profiles with a large gradient region near 0741-3335/40/6/020/img28 = 0.55. The best discharges have no transport barrier at the edge of the plasma (L-mode). This allows central power deposition by the neutral beams in JET. A control of the plasma pressure, using feedback of the additional heating power in real-time, minimizes the impact of magnetohydrodynamic instabilities. As a result, these discharges achieve the highest D-D neutron rates in JET; 0741-3335/40/6/020/img29, with 0741-3335/40/6/020/img30, 0741-3335/40/6/020/img31 and 0741-3335/40/6/020/img32

Overview of the JET preparation for deuterium-tritium operation with the ITER like-wall

\u3cp\u3eFor the past several years, the JET scientific programme (Pamela et al 2007 Fusion Eng. Des. 82 590) has been engaged in a multi-campaign effort, including experiments in D, H and T, leading up to 2020 and the first experiments with 50%/50% D-T mixtures since 1997 and the first ever D-T plasmas with the ITER mix of plasma-facing component materials. For this purpose, a concerted physics and technology programme was launched with a view to prepare the D-T campaign (DTE2). This paper addresses the key elements developed by the JET programme directly contributing to the D-T preparation. This intense preparation includes the review of the physics basis for the D-T operational scenarios, including the fusion power predictions through first principle and integrated modelling, and the impact of isotopes in the operation and physics of D-T plasmas (thermal and particle transport, high confinement mode (H-mode) access, Be and W erosion, fuel recovery, etc). This effort also requires improving several aspects of plasma operation for DTE2, such as real time control schemes, heat load control, disruption avoidance and a mitigation system (including the installation of a new shattered pellet injector), novel ion cyclotron resonance heating schemes (such as the three-ions scheme), new diagnostics (neutron camera and spectrometer, active Alfven eigenmode antennas, neutral gauges, radiation hard imaging systems...) and the calibration of the JET neutron diagnostics at 14 MeV for accurate fusion power measurement. The active preparation of JET for the 2020 D-T campaign provides an incomparable source of information and a basis for the future D-T operation of ITER, and it is also foreseen that a large number of key physics issues will be addressed in support of burning plasmas.\u3c/p\u3

Efficient generation of energetic ions in multi-ion plasmas by radio-frequency heating

We describe a new technique for the efficient generation of high-energy ions with electromagnetic ion cyclotron waves in multi-ion plasmas. The discussed `three-ion' scenarios are especially suited for strong wave absorption by a very low number of resonant ions. To observe this effect, the plasma composition has to be properly adjusted, as prescribed by theory. We demonstrate the potential of the method on the world-largest plasma magnetic confinement device, JET (Joint European Torus, Culham, UK), and the high-magnetic-field tokamak Alcator C-Mod (Cambridge, USA). The obtained results demonstrate efficient acceleration of 3He ions to high energies in dedicated hydrogen-deuterium mixtures. Simultaneously, effective plasma heating is observed, as a result of the slowing-down of the fast 3He ions. The developed technique is not only limited to laboratory plasmas, but can also be applied to explain observations of energetic ions in space-plasma environments, in particular, 3He-rich solar flares

First principles and integrated modelling achievements towards trustful fusion power predictions for JET and ITER

Predictability of burning plasmas is a key issue for designing and building credible future fusion devices. In this context, an important effort of physics understanding and guidance is being carried out in parallel to JET experimental campaigns in H and D by performing analyses and modelling towards an improvement of the understanding of DT physics for the optimization of the JET-DT neutron yield and fusion born alpha particle physics. Extrapolations to JET-DT from recent experiments using the maximum power available have been performed including some of the most sophisticated codes and a broad selection of models. There is a general agreement that 11-15 MW of fusion power can be expected in DT for the hybrid and baseline scenarios. On the other hand, in high beta, torque and fast ion fraction conditions, isotope effects could be favourable leading to higher fusion yield. It is shown that alpha particles related physics, such as TAE destabilization or fusion power electron heating, could be studied in ITER relevant JET-DT plasmas

Role of fast ion pressure in the isotope effect in JET L-mode plasmas

This paper presents results of JET ITER-like wall L-mode experiments in hydrogen and deuterium (D) plasmas, dedicated to the study of the isotope dependence of ion heat transport by determination of the ion critical gradient and stiffness by varying the ion cyclotron resonance heating power deposition. When no strong role of fast ions in the plasma core is expected, the main difference between the two isotope plasmas is determined by the plasma edge and the core behavior is consistent with a gyro-Bohm scaling. When the heating power (and the fast ion pressure) is increased, in addition to the difference in the edge region, also the plasma core shows substantial changes. The stabilization of ion heat transport by fast ions, clearly visible in D plasmas, appears to be weaker in H plasmas, resulting in a higher ion heat flux in H with apparent anti-gyro-Bohm mass scaling. The difference is found to be caused by the different fast ion pressure between H and D plasmas, related to the heating power settings and to the different fast ion slowing down time, and is completely accounted for in non-linear gyrokinetic simulations. The application of the TGLF quasi-linear model to this set of data is also discussed

A new mechanism for increasing density peaking in tokamaks: improvement of the inward particle pinch with edge E x B shearing

Developing successful tokamak operation scenarios, as well as confident extrapolation of present-day knowledge requires a rigorous understanding of plasma turbulence, which largely determines the quality of the confinement. In particular, accurate particle transport predictions are essential due to the strong dependence of fusion power or bootstrap current on the particle density details. Here, gyrokinetic turbulence simulations are performed with physics inputs taken from a JET power scan, for which a relatively weak degradation of energy confinement and a significant density peaking is obtained with increasing input power. This way physics parameters that lead to such increase in the density peaking shall be elucidated. While well-known candidates, such as the collisionality, previously found in other studies are also recovered in this study, it is furthermore found that edge E x B shearing may adopt a crucial role by enhancing the inward pinch. These results may indicate that a plasma with rotational shear could develop a stronger density peaking as compared to a non-rotating one, because its inward convection is increased compared to the outward diffusive particle flux as long as this rotation has a significant on E x B flow shear stabilization. The possibly significant implications for future devices, which will exhibit much less torque compared to present day experiments, are discussed

Deep neural networks for plasma tomography with applications to JET and COMPASS

Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural networks, can be used for inverse problems such as plasma tomography. In essence, plasma tomography consists in reconstructing the 2D plasma profile on a poloidal cross-section of a fusion device, based on line-integrated measurements from multiple radiation detectors. Since the reconstruction process is computationally intensive, a deconvolutional neural network trained to produce the same results will yield a significant computational speedup, at the expense of a small error which can be assessed using different metrics. In this work, we discuss the design principles behind such networks, including the use of multiple layers, how they can be stacked, and how their dimensions can be tuned according to the number of detectors and the desired tomographic resolution for a given fusion device. We describe the application of such networks at JET and COMPASS, where at JET we use the bolometer system, and at COMPASS we use the soft X-ray diagnostic based on photodiode arrays

Synthetic diagnostic for the JET scintillator probe lost alpha measurements

A synthetic diagnostic has been developed for the JET lost alpha scintillator probe, based on the ASCOT fast ion orbit following code and the AFSI fusion source code. The synthetic diagnostic models the velocity space distribution of lost fusion products in the scintillator probe. Validation with experimental measurements is presented, where the synthetic diagnostic is shown to predict the gyroradius and pitch angle of lost DD protons and tritons. Additionally, the synthetic diagnostic reproduces relative differences in total loss rates in multiple phases of the discharge, which can be used as a basis for total loss rate predictions

Modification of the Alfven wave spectrum by pellet injection

Alfven eigenmodes driven by energetic particles are routinely observed in tokamak plasmas. These modes consist of poloidal harmonics of shear Alfven waves coupled by inhomogeneity in the magnetic field. Further coupling is introduced by 3D inhomogeneities in the ion density during the assimilation of injected pellets. This additional coupling modifies the Alfven continuum and discrete eigenmode spectrum. The frequencies of Alfven eigenmodes drop dramatically when a pellet is injected in JET. From these observations, information about the changes in the ion density caused by a pellet can be inferred. To use Alfven eigenmodes for MHD spectroscopy of pellet injected plasmas, the 3D MILD codes Stellgap and AE3D were generalised to incorporate 3D density profiles. A model for the expansion of the ionised pellet plasmoid along a magnetic field line was derived from the fluid equations. Thereby, the time evolution of the Alfven eigenfrequency is reproduced. By comparing the numerical frequency drop of a toroidal Alfven eigenmode (TAE) to experimental observations, the initial ion density of a cigar-shaped ablation region of length 4cm is estimated to be n(*) = 6.8 x 10(22) m(-3) at the TAE location (r/a approximate to 0.75). The frequency sweeping of an Alfven eigenmode ends when the ion density homogenises poloidally. Modelling suggests that the time for poloidal homogenisation of the ion density at the TAE position is tau(h) = 18 +/- 4 ms for inboard pellet injection, and tau(h) = 26 +/- 2 ms for outboard pellet injection. By reproducing the frequency evolution of the elliptical Alfven eigemnode (EAE), the initial ion density at the EAE location (r/a approximate to 0.9) can be estimated to be n(*) = 4.8 x 10(22) m(-3). Poloidal homogenisation of the ion density takes 2.7 times longer at the EAE location than at the TAE location for both inboard and outboard pellet injection