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The ramp-up is a critical phase in the operations of a Tokamak, during which engineering and physics aspects must be taken into account to ensure stability, minimize flux consumption and avoid disruptions. Predicting ramp-up phases faces challenges such as nonlinearity, uncertainty on boundary and initial conditions and changes in the magnetic equilibrium. Our work uses the High-Fidelity Pulse Simulator (HFPS), a Python workflow based on JINTRAC. The input and output are in machine and code generic IMAS data format. The HFPS predicts the evolution of the current, temperature, main ion density and impurity density up to the separatrix. The self-consistent prediction of the density during the ramp-up represents the main element of novelty in this work. To this end, a closed feedback loop is set to match experimental line averaged density. QuaLiKiz (Citrin et al 2017 Plasma Phys. Control. Fusion 59 124005), TGLF (Staebler et al 2016 Phys. Plasmas 23 062518) and FRANTIC (Tamor 1981 J. Comput. Phys. 40 104119) are used to calculate turbulent fluxes and the source of neutrals respectively. QuaLiKiz and TGLF predict a transition from Trapped Electron Mode early in the discharge to Ion Temperature Gradient dominated turbulence. The results are compared to higher fidelity simulations with GKW, which show qualitative agreement. Good general agreement is reached between integrated modelling and experimental data, quantified by proposed measures of agreement. A large set of sensitivities to modelling choices and initial and boundary conditions is performed on four different discharges, to assess the robustness of the approach.

Enhanced confinement is observed in EAST low ${q_{95}}$ ( ${q_{95}} < 3.5$ ) plasmas with the temperature ratio ( ${T_i}/{T_e}$ ) increasing. A statistically significant positive correlation between ${H_{98y2}}$ and ${T_i}/{T_e}$ has been established. Increased ${T_i}\,$ triggerd by Neutral Beam Injection in experiments maintaining constant ${T_e}$ leads initially to an improved ${T_i}/{T_e}$ ratio, which subsequently mitigates heat transport in the ion channel. The Trapped Gyro–Landau Fluid transport model was applied to analyse the dependence of the turbulent transport on ${T_i}/{T_e}$ . Simulation results demonstrate that the Ion Temperature Gradient mode is stabilized in high ${T_i}/{T_e}$ plasma, with ion flux results from predictive modelling further validating this effect. These findings corroborate the Weiland model and complement one another. This study contributes to a deeper understanding of how the dimensionless parameter ${T_i}/{T_e}$ influences plasma transport, and helps demonstrate the feasibility of operations under the low ${q_{95}}$ condition required for the ITER-inductive scenario in the new ${T_i}/{T_e}$ regime.

We study numerically the feasibility of achieving the L-H transition in the current EU-DEMO tokamak baseline using uniquely direct electron heating. The ASTRA code coupled to the TGLF turbulent transport model is used to predict steady-state kinetic plasma profiles for diverse numerical scans. Among them, we have varied the separatrix electron density, the total amount of ECRH power, the microwave beam deposition profile and the plasma impurity content. The solutions are then compared to L-H transition scaling laws to assess whether the found plasma state would enter into H-mode. We find the plasma density and impurity content to be the key variables setting the boundaries in parameter space where the L-H transition is feasible. When impurities can be controlled under a certain threshold, given here for a fully shaped DEMO plasma, the L-H transition is achieved in all the studied conditions.

JET experiments using the fuel mixture envisaged for fusion power plants, deuterium and tritium (D–T), provide a unique opportunity to validate existing D–T fusion power prediction capabilities in support of future device design and operation preparation. The 2021 JET D–T experimental campaign has achieved D–T fusion powers sustained over 5 s in ITER-relevant conditions i.e. operation with the baseline or hybrid scenario in the full metallic wall. In preparation of the 2021 JET D–T experimental campaign, extensive D–T predictive modelling was carried out with several assumptions based on D discharges. To improve the validity of ITER D–T predictive modelling in the future, it is important to use the input data measured from 2021 JET D–T discharges in the present core predictive modelling, and to specify the accuracy of the D–T fusion power prediction in comparison with the experiments. This paper reports on the validation of the core integrated modelling with TRANSP, JINTRAC, and ETS coupled with a quasilinear turbulent transport model (Trapped Gyro Landau Fluid or QualLiKiz) against the measured data in 2021 JET D–T discharges. Detailed simulation settings and the heating and transport models used are described. The D–T fusion power calculated with the interpretive TRANSP runs for 38 D–T discharges (12 baseline and 26 hybrid discharges) reproduced the measured values within 20 $\%$ . This indicates the additional uncertainties, that could result from the measurement error bars in kinetic profiles, impurity contents and neutron rates, and also from the beam-thermal fusion reaction modelling, are less than $20\%$ in total. The good statistical agreement confirms that we have the capability to accurately calculate the D–T fusion power if correct kinetic profiles are predicted, and indicates that any larger deviation of the D–T fusion power prediction from the measured fusion power could be attributed to the deviation of the predicted kinetic profiles from the measured kinetic profiles in these plasma scenarios. Without any posterior adjustment of the simulation settings, the ratio of predicted D–T fusion power to the measured fusion power was found as 65%–96% for the D–T baseline and 81%–97% for D–T hybrid discharge. Possible reasons for the lower D–T prediction are discussed and future works to improve the fusion power prediction capability are suggested. The D–T predictive modelling results have also been compared to the predictive modelling of the counterpart D discharges, where the key engineering parameters are similar. Features in the predicted kinetic profiles of D–T discharges such as underprediction of n _e are also found in the prediction results of the counterpart D discharges, and it leads to similar levels of the normalized neutron rate prediction between the modelling results of D–T and the counterpart D discharges. This implies that the credibility of D–T fusion power prediction could be a priori estimated by the prediction quality of the preparatory D discharges, which will be attempted before actual D–T experiments.

This work presents a study of plasma transport at low aspect ratio on the National Spherical Torus Experiment tokamak, where the turbulent and neoclassical energy fluxes calculated by the quasilinear Trapped Gyro Landau Fluid (TGLF) model and the multi species drift-kinetic Neoclassical solver (NEO) are validated against experimental data. The turbulent energy transport of two plasma discharges, one in the L-mode confinement regime and another in the H-mode regime, is dominated by electrostatic drift-wave instabilities, while the ion heat transport has a significant neoclassical contribution. The data analysis workflow is described in detail to understand how the variations of mapping and fitting of experimental data affect the power balance solution and subsequent flux-matching plasma profile predictions with the TGYRO solver. On average, the predicted plasma profiles are consistent with experimental data. However, the solutions are sensitive to various input parameters, including boundary conditions, and the electron-ion coupling. Linear gyrokinetic stability analysis demonstrates close agreement of the real frequencies of unstable modes between TGLF and CGYRO gyrokinetic simulations, but higher growth rates are predicted by TGLF, especially for the H-mode case. Estimates of the low- k modes’ contributions to the total flux are consistent with linear stability analysis and the E × B suppression of turbulence in TGLF simulations with the SAT1 saturation model, while the SAT2 saturation model over-predicts the low- k modes’ contribution in the H-mode case. Moreover, the results with SAT1 model are consistent with power balance analysis, which indicates only neoclassical ion energy fluxes inside ρ