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 evolution of the JET high performance hybrid scenario, including central accumulation of the tungsten (W) impurity, is reproduced with predictive multi-channel integrated modelling over multiple confinement times using first-principle based core transport models. 8 transport channels (𝑇 𝑖 , 𝑇 𝑒 , 𝑗, 𝑛 𝐷 , 𝑛 𝐵𝑒 , 𝑛 𝑁𝑖 , 𝑛 𝑊 , 𝜔) are modelled predictively, with self-consistent sources, radiation and magnetic equilibrium, yielding a system with multiple non-linearities: This system can reproduce the observed radiative temperature collapse after several confinement times. W is transported inward by neoclassical convection driven by the main ion density gradients and enhanced by poloidal asymmetries due to centrifugal acceleration. The slow evolution of the bulk density profile sets the timescale for W accumulation. Modelling this phenomenon requires a turbulent transport model capable of accurately predicting particle and momentum transport (QuaLiKiz) and a neoclassical transport model including the effects of poloidal asymmetries (NEO) coupled to an integrated plasma simulator (JINTRAC). The modelling capability is applied to optimise the available actuators to prevent W accumulation, and to extrapolate in power and pulse length. Central NBI heating is preferred for high performance, but gives central deposition of particles and torque which increase the risk of W accumulation by increasing density peaking and poloidal asymmetry. The primary mechanism for ICRH to control W in JET is via its impact through turbulence in reducing main ion density peaking (which drives inward neoclassical convection), increased temperature screening and turbulent W diffusion. The anisotropy from ICRH also reduces poloidal asymmetry, but this effect is negligible in high rotation JET discharges. High power ICRH near the axis can sensitively mitigate against W accumulation, and dominant ion heating (e.g. He-3 minority) is predicted to provide more resilience to W accumulation than dominant electron heating (e.g. H minority) in the JET hybrid scenario. Extrapolation to DT plasmas finds 17.5MW of fusion power and improved confinement compared to DD, due to reduced ion-electron energy exchange, and increased Ti/Te stabilisation of ITG instabilities. The turbulence reduction in DT increases density peaking and accelerates the arrival of W on axis; this may be mitigated by reducing the penetration of the beam particle source with an increased pedestal density.

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.

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.