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.

The 2014–2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60 h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L–H power threshold in Deuterium and Hydrogen are given, stressing the importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H  =  1 at βN ~ 1.8 and n/nGW ~ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D–T campaign and 14 MeV neutron calibration strategy are reviewed.

This contribution aims to improve existing scalings of the L-mode power decay length λ q o m p , especially for plasma configurations with strike points at the ITER-relevant location—closed vertical divertor targets. We propose 13 new λ q o m p scalings based on data from the tokamaks JET, EAST, MAST, Alcator C-mod and COMPASS, and validate them against the output of the 2D turbulence code HESEL. The analysis covers 500 divertor heat flux profiles (obtained by probes or IR cameras), measured in L-mode discharges with varying 12 global plasma parameters (all well predictable). We find that the two previously published scalings (Eich 2013 J. Nucl. Mat. 438 S72) and (Scarabosio 2013 J. Nucl. Mat. 438 S426), which were based on outer target data from AUG and JET, describe the JET, C-mod and COMPASS profiles well. This holds not only at the outer horizontal and vertical targets, but surprisingly also at the inner vertical targets. In contrast, EAST, HESEL and especially MAST data are poorly described by these two scalings. We therefore derive 13 new scalings, which account for 85–92 % of the measured λ q o m p variability across all five tokamaks. Although each of the scalings is based on a different parameter combination, their predictions for the ITER and COMPASS-Upgrade tokamaks are very similar. Just before the L-H transition in the ITER baseline scenario, the presented scalings predict values λ q o m p = 3.0 ± 0.5 mm. For the COMPASS-Upgrade tokamak, all the scalings predict λ q o m p = 2.1 ± 0.5 mm with a single exception of the scaling based on the stored plasma energy which predicts only 1.2 mm for both tokamaks. We encourage the reader to use as many of these scalings as possible, depending on available data. In attached plasma and using significant assumptions, our results imply steady-state surface-perpendicular heat flux around 10 MW/m2 for ITER, and 20 MW/m2 for COMPASS-Upgrade.

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.