Nonlinear electromagnetic stabilization by suprathermal pressure gradients found in specific regimes is shown to be a key factor in reducing tokamak microturbulence, augmenting significantly the thermal pressure electromagnetic stabilization. Based on nonlinear gyrokinetic simulations investigating a set of ion heat transport experiments on the JET tokamak, described by Mantica et al. [Phys. Rev. Lett. 107, 135004 (2011)], this result explains the experimentally observed ion heat flux and stiffness reduction. These findings are expected to improve the extrapolation of advanced tokamak scenarios to reactor relevant regimes.

CRONOS is a suite of numerical codes for the predictive/interpretative simulation of a full tokamak discharge. It integrates, in a modular structure, a 1D transport solver with general 2D magnetic equilibria, several heat, particle and impurities transport models, as well as heat, particle and momentum sources. This paper gives a first comprehensive description of the CRONOS suite: overall structure of the code, main available models, details on the simulation workflow and numerical implementation. Some examples of applications to the analysis of experimental discharges and the predictions of ITER scenarios are also given.

The impact of electromagnetic stabilization and flow shear stabilization on ITG turbulence is investigated. Analysis of a low-β JET L-mode discharge illustrates the relation between ITG stabilization, and proximity to the electromagnetic instability threshold. This threshold is reduced by suprathermal pressure gradients, highlighting the effectiveness of fast ions in ITG stabilization. Extensive linear and nonlinear gyrokinetic simulations are then carried out for the high-β JET hybrid discharge 75225, at two separate locations at inner and outer radii. It is found that at the inner radius, nonlinear electromagnetic stabilization is dominant, and is critical for achieving simulated heat fluxes in agreement with the experiment. The enhancement of this effect by suprathermal pressure also remains significant. It is also found that flow shear stabilization is not effective at the inner radii. However, at outer radii the situation is reversed. Electromagnetic stabilization is negligible while the flow shear stabilization is significant. These results constitute the high-β generalization of comparable observations found at low-β at JET. This is encouraging for the extrapolation of electromagnetic ITG stabilization to future devices. An estimation of the impact of this effect on the ITER hybrid scenario leads to a 20% fusion power improvement.

Abstract. The replacement of the JET carbon wall (C-wall) by a Be/W ITER-like wall (ILW) has affected the plasma energy confinement. To investigate this, experiments have been performed with both the C-wall and ILW to vary the heating power over a wide range for plasmas with different shapes. It was found that the power degradation of thermal energy confinement was weak with the ILW; much weaker than the IPB98(y,2) scaling and resulting in an increase in normalised confinement from H 98~0 .9 at  N~1 .5 to H 98~1 .2-1.3 at  N~2 .5-3.0 as the power was increased (where H 98 = E / IPB98(y,2) and  N = T B T /aI P in %T/mMA). This reproduces the general trend in JET of higher normalised confinement in the so-called 'hybrid' domain, where normalised  is typically above 2.5, compared with 'baseline' ELMy H-mode plasmas with  N~1 .5-2.0. This weak power degradation of confinement, which was also seen with the C-wall experiments at low triangularity, is due to both increased edge pedestal pressure and core pressure peaking at high power. By contrast, the high triangularity C-wall plasmas exhibited elevated H 98 over a wide power range with strong, IPB98(y,2)-like, power degradation. This strong power degradation of confinement appears to be linked to an increase in the source of neutral particles from the wall as the power increased, an effect that was not reproduced with the ILW. The reason for the loss of improved confinement domain at low power with the ILW is yet to be clarified, but contributing factors may include changes in the rate of gas injection, wall recycling, plasma composition and radiation. The results presented in this paper show that the choice of wall materials can strongly affect plasma performance, even changing confinement scalings that are relied upon for extrapolation to future devices.

Abstract. Extensive linear and non-linear gyrokinetic simulations and linear MHD analyses performed for JET discharges with improved confinement have shown that the large population of fast ions found in the plasma core under particular heating conditions has a strong impact on core microturbulence and edge MHD by reducing core ion heat fluxes and increasing pedestal pressure in a feedback mechanism. In the case of the ITER Like Wall (ILW), it is shown how this mechanism plays a decisive role for the transition to advanced regimes and it can explain the weak power degradation obtained in dedicated power scans. The mechanism is found to be highly dependent on plasma triangularity as it changes the balance between the improvement in the plasma core and the edge. The feedback mechanism can play a similar role in the ITER hybrid scenario as in the JET discharges analyzed due to its high triangularity plasmas and the large amount of fast ions generated in the core by the heating systems and the alpha power.

In the European fusion roadmap, ITER is followed by a demonstration fusion power reactor (DEMO), for which a conceptual design is under development. This paper reports the first results of a coherent effort to develop the relevant physics knowledge for that (DEMO Physics Basis), carried out by European experts. The program currently includes investigations in the areas of scenario modeling, transport, MHD, heating & current drive, fast particles, plasma wall interaction and disruptions.

Abstract. Integrated simulations are done to establish a physics basis, in conjunction with present tokamak experiments, for the operating modes in ITER. Simulations of the hybrid mode are done using both fixed and free-boundary 1.5D transport evolution codes including CRONOS, ONETWO, TSC/TRANSP, TOPICS, and ASTRA. The hybrid operating mode is simulated using the GLF23 energy transport model. The injected powers are limited to the negative ion neutral beam (NBI), ion cyclotron (ICRF), and electron cyclotron (EC). Several plasma parameters and source parameters are specified for the hybrid cases to provide a comparison among the simulations. Simulations of the steady state operating mode are done with the same 1.5D transport evolution codes cited above. In these cases the energy transport model is more difficult to prescribe, so that energy confinement models will range from theory based to empirically based. The injected powers include the same sources for the hybrid with the possible addition of lower hybrid (LH). These simulations will be presented and compared with particular focus on code to code results when using the same energy transport model, and within the same code when using different energy transport models

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.