Type-I edge-localized modes (ELMs) have been mitigated at the JET tokamak using a static external n=1 perturbation field generated by four error field correction coils located far from the plasma. During the application of the n=1 field the ELM frequency increased by a factor of 4 and the amplitude of the D(alpha) signal decreased. The energy loss per ELM normalized to the total stored energy, DeltaW/W, dropped to values below 2%. Transport analyses shows no or only a moderate (up to 20%) degradation of energy confinement time during the ELM mitigation phase.

Results from the first measurements of a core plasma poloidal rotation velocity (upsilontheta) across internal transport barriers (ITB) on JET are presented. The spatial and temporal evolution of the ITB can be followed along with the upsilontheta radial profiles, providing a very clear link between the location of the steepest region of the ion temperature gradient and localized spin-up of upsilontheta. The upsilontheta measurements are an order of magnitude higher than the neoclassical predictions for thermal particles in the ITB region, contrary to the close agreement found between the determined and predicted particle and heat transport coefficients [K.-D. Zastrow, Plasma Phys. Controlled Fusion 46, B255 (2004)]. These results have significant implications for the understanding of transport barrier dynamics due to their large impact on the measured radial electric field profile.

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.

Experimental evidence from the JET tokamak is presented supporting the predictions of a recent theory (Graves et al 2009 Phys. Rev. Lett. 102 065005) on sawtooth instability control by toroidally propagating ion cyclotron resonance waves. Novel experimental conditions minimized a possible alternate effect of magnetic shear modification by ion cyclotron current drive, and enabled the dependence of the new energetic ion mechanism to be tested over key variables. The results have favourable implications on sawtooth control by ion cyclotron resonance waves in a fusion reactor.

The operational domain for active control of type-I edge localized modes (ELMs) with an n = 1 external magnetic perturbation field induced by the ex-vessel error field correction coils on JET has been developed towards more ITER-relevant regimes with high plasma triangularity, up to 0.45, high normalized beta, up to 3.0, plasma current up to 2.0 MA and q 95 varied between 3.0 and 4.8. The results of ELM mitigation in high triangularity plasmas show that the frequency of type-I ELMs increased by a factor of 4 during the application of the n = 1 fields, while the energy loss per ELM, W/W , decreased from 6% to below the noise level of the diamagnetic measurement (<2%). No reduction of confinement quality (H 98Y ) during the ELM mitigation phase has been observed. The minimum n = 1 perturbation field amplitude above which the ELMs were mitigated increased with a lower q 95 but always remained below the n = 1 locked mode threshold. The first results of ELM mitigation with n = 2 magnetic perturbations on JET demonstrate that the frequency of ELMs increased from