This paper presents the experimental characterization of pedestal parameters, edge localized mode (ELM) energy, and particle losses from the main plasma and the corresponding ELM energy fluxes on plasma facing components for a series of dedicated experiments in the Joint European Torus (JET). From these experiments, it is demonstrated that the simple hypothesis relating the peeling-ballooning linear instability to ELM energy losses is not valid. Contrary to previous observations at lower triangularities, small energy losses at low collisionality have been obtained in regimes at high plasma triangularity and q95∼4.5, indicating that the edge plasma magnetohydrodynamic stability is linked with the transport mechanisms that lead to the loss of energy by conduction during type I ELMs. Measurements of the ELM energy fluxes on the divertor target show that their time scale is linked to the ion transport along the field and the formation of a high energy sheath, in agreement with kinetic modeling of ELMs. Higher density ELMs, of a convective nature, lead to overall much longer time scales for the ELM energy flux, with more than 80% of the ELM energy flux arriving after the surface divertor temperature has reached its maximum value. On the contrary, for low density ELMs, of a conductive nature, up to 40% of the energy flux arrives at the divertor target before the surface divertor temperature has reached its maximum value. These large and more conductive ELMs may lead to up to ∼50% of the ELM energy reaching the main wall plasma facing components instead of the divertor target. The extrapolation to the International Thermonuclear Experimental Reactor of the obtained results is described and the main uncertainties discussed.

The first experimental evidence showing the connection between blob/hole formation and zonal-flow generation was obtained in the edge plasma of the JET tokamak. Holes as well as blobs are observed to be born in the edge shear layer, where zonal-flows shear off meso-scale coherent structures, leading to disconnection of positive and negative pressure perturbations. The newly formed blobs transport azimuthal momentum up the gradient of the azimuthal flow and drive the zonal-flow shear while moving outwards. During this process energy is transferred from the meso-scale coherent structures to the zonal flows via the turbulent Reynolds stress, resulting in nonlinear saturation of edge turbulence and suppression of meso-scale fluctuations. These findings carry significant implications for the mechanism of structure formation in magnetically confined plasma turbulence.

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.

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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.