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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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.

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Observations made in a JET experiment aimed at accelerating deuterons to the MeV range by third harmonic radiofrequency (RF) heating coupled into a deuterium beam are reported. Measurements are based on a set of advanced neutron and gamma-ray spectrometers that, for the first time, observe the plasma simultaneously along vertical and oblique lines of sight. Parameters of the fast ion energy distribution, such as the high energy cut-off of the deuteron distribution function and the RF coupling constant, are determined from data within a uniform analysis framework for neutron and gamma-ray spectroscopy based on an one dimensional model and by a consistency check among the individual measurement techniques. A systematic difference is seen between the two lines of sight and is interpreted to originate from the sensitivity of the oblique detectors to the pitch-angle structure of the distribution around the resonance, which is not correctly portrayed within the adopted one dimensional model. A framework to calculate neutron and gamma-ray emission from a spatially resolved, two dimensional deuteron distribution specified by energy/pitch is thus developed and used for a first comparison with predictions from ab initio models of RF heating at multiple harmonics. The results presented in this paper are of relevance for the development of advanced diagnostic techniques for MeV range ions in high performance fusion plasmas, with applications to the experimental validation of RF heating codes and, more generally, to studies of the energy distribution of ions in the MeV range in high performance deuterium and deuterium-tritium plasmas.