Progress in thermonuclear fusion energy research based on deuterium plasmas magnetically confi ned in toroidal tokamak devices requires the development of effi cient current drive methods. Previous experiments have shown that plasma current can be driven effectively by externally launched radio frequency power coupled to lower hybrid plasma waves. However, at the high plasma densities required for fusion power plants, the coupled radio frequency power does not penetrate into the plasma core, possibly because of strong wave interactions with the plasma edge. Here we show experiments performed on FTU (Frascati Tokamak Upgrade) based on theoretical predictions that nonlinear interactions diminish when the peripheral plasma electron temperature is high, allowing signifi cant wave penetration at high density. The results show that the coupled radio frequency power can penetrate into high-density plasmas due to weaker plasma edge effects, thus extending the effective range of lower hybrid current drive towards the domain relevant for fusion reactors.

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.

The JET 2019-2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major Neutral Beam Injection (NBI) upgrade providing record power in 2019-2020, and tested the technical & procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle physics in the coming D-T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed Shattered Pellet Injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design & operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D-T benefited from the highest D-D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER.

Research towards a plasma exhaust solution for a fusion power plant aims at validating edge physics models, strengthening predictive capabilities and improving the divertor configuration. The TCV tokamak is extensively used to investigate the extent that geometric configuration modifications can affect plasma exhaust performance. Recent TCV experiments continue previous detachment studies of Ohmically heated L-mode plasmas in standard single-null configurations, benefitting from a range of improved diagnostic capabilities. Studies were extended to nitrogen seeding and an entire suite of alternative magnetic configurations, including flux flaring towards the target (X divertor), increasing the outer target radius (Super-X) and movement of a secondary x-point inside the vessel (X-point target) as well as the entire range of snowflake configurations. Nitrogen seeding into a snowflake minus configuration demonstrated a regime with strong radiation in the large region between the two x-points, confirming EMC3-Eirene simulations, and opening a promising path towards highly radiating regimes with limited adverse effects on core performance.

Plasma Phys. Control. Fusion 58 (2016) 074005 (11pp) q imp mm, thus consolidating the 50 mm width used to optimize the FW panel toroidal shape.

In optimized shear plasmas in the Joint European Torus [P. H. Rebut and B. E. Keen, Fusion Technol. 11, 13 (1987)], safety factor (q) profiles with negative magnetic shear are produced by applying lower hybrid (LH) waves during the plasma current ramp-up phase. These plasmas produce a barrier to the electron energy transport. The radius at which the barrier is located increases with the LH wave power. When heated with high power from ion cyclotron resonance heating and neutral beam injection, they can additionally produce transient internal transport barriers (ITBs) seen on the ion temperature, electron density, and toroidal rotation velocity profiles. Due to recent improvements in coupling, q profile control with LH current drive in ITB plasmas with strong combined heating can be explored. These new experiments have led to ITBs sustained for several seconds by the LH wave. Simulations show that the current driven by the LH waves peaks at the ITB location, indicating that it can act in the region of low magnetic shear.

Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfvénic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfvénic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity.

The use of electrostatic probes as a diagnostic tool of the dust particles in the tokamak edge plasmas is investigated. Probe measurements of electrostatic fluctuations in the scrape-off layer of the Frascati Tokamak Upgrade revealed that some features of the signals can be explained only by a local non-propagating phenomenon. These signal features are shown to be both in qualitative and quantitative agreement with ionization, and consequent extra charge collected by the probes, due to the impact of micrometre-sized dust at a velocity of the order of 10 km s−1. Electron microscope analysis of the probe surface yielded direct support for such an interpretation.