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 modelling of a controlled tungsten dust injection experiment in TEXTOR by the dust dynamics code MIGRAINe is reported. The code, in addition to the standard dust–plasma interaction processes, also encompasses major mechanical aspects of dust–surface collisions. The use of analytical expressions for the restitution coefficients as functions of the dust radius and impact velocity allows us to account for the sticking and rebound phenomena that define which parts of the dust size distribution can migrate efficiently. The experiment provided unambiguous evidence of long-distance dust migration; artificially introduced tungsten dust particles were collected 120° toroidally away from the injection point, but also a selectivity in the permissible size of transported grains was observed. The main experimental results are reproduced by modelling.

A power-balance model, with radiation losses from impurities and neutrals, gives a unified description of the density limit (DL) of the stellarator, the L-mode tokamak, and the reversed field pinch (RFP). The model predicts a Sudo-like scaling for the stellarator, a Greenwald-like scaling, , for the RFP and the ohmic tokamak, a mixed scaling, , for the additionally heated L-mode tokamak. In a previous paper (Zanca et al 2017 Nucl. Fusion 57 056010) the model was compared with ohmic tokamak, RFP and stellarator experiments. Here, we address the issue of the DL dependence on heating power in the L-mode tokamak. Experimental data from high-density disrupted L-mode discharges performed at JET, as well as in other machines, are taken as a term of comparison. The model fits the observed maximum densities better than the pure Greenwald limit.

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.

Erosion and deposition were studied in the JET divertor during the first JET ITER-like wall campaign 2011-2012 using marker tiles. An almost complete poloidal section consisting of tiles 0, 1, 3, 4, 6, 7, 8 was studied. The data from divertor tile surfaces were completed by the analysis of samples from remote divertor areas and from the inner wall cladding. The total mass of material deposited in the divertor decreased by a factor of 4-9 compared to the deposition of carbon during all-carbon JET operation before 2010. Deposits in 2011-2012 consist mainly of beryllium with 5-20 at.% of carbon and oxygen, respectively, and small amounts of Ni, Cr, Fe and W. This decrease of material deposition in the divertor is accompanied by a decrease of total deuterium retention inside the JET vessel by a factor of 10-20. The detailed erosion/deposition pattern in the divertor with the ITER-like wall 2 configuration shows rigorous changes compared to the pattern with the all-carbon JET configuration.