A model for sawtooth oscillations in tokamak experiments is outlined. A threshold criterion for the onset of internal kink modes and a prescription for the relaxed profiles immediately after the sawtooth crash have been implemented in a transport code that evolves the relevant plasma parameters. In this paper, applications of this model to the prediction of the sawtooth period and amplitude in projected ITER discharges are discussed. It is found that sawteeth can be stabilized transiently by the fusion alpha particles in ITER for periods that are long on the energy confinement timescale (). The sawtooth period depends on the amount of reconnected flux at the preceding sawtooth crash. When Kadomtsev's full reconnection model is used, the period can exceed 100 s. The sawtooth mixing radius following long duration sawtooth ramps can easily exceed half the plasma minor radius, raising questions about the desirability of transient sawtooth suppression.

Model for the sawtooth period and amplitude

Nuclear fusion is one of the most attractive alternatives to carbon-dependent energy sources1. Harnessing energy from nuclear fusion in a large reactor scale, however, still presents many scientific challenges despite the many years of research and steady advances in magnetic confinement approaches. State-of-the-art magnetic fusion devices cannot yet achieve a sustainable fusion performance, which requires a high temperature above 100 million kelvin and sufficient control of instabilities to ensure steady-state operation on the order of tens of seconds2,3. Here we report experiments at the Korea Superconducting Tokamak Advanced Research4 device producing a plasma fusion regime that satisfies most of the above requirements: thanks to abundant fast ions stabilizing the core plasma turbulence, we generate plasmas at a temperature of 100 million kelvin lasting up to 20 seconds without plasma edge instabilities or impurity accumulation. A low plasma density combined with a moderate input power for operation is key to establishing this regime by preserving a high fraction of fast ions. This regime is rarely subject to disruption and can be sustained reliably even without a sophisticated control, and thus represents a promising path towards commercial fusion reactors. A magnetic confinement regime established at the Korea Superconducting Tokamak Advanced Research device enables the generation of plasmas over 108 kelvin for 20 seconds with the aid of fast ions without plasma edge instabilities or impurity accumulation. 

/pdf/a-sustained-high-temperature-fusion-plasma-regime-1h0hw989.pdf

A sustained high-temperature fusion plasma regime facilitated by fast ions

In this work, we address a new feedforward control scheme of the normalized beta (βN) in tokamak plasmas, using the deep reinforcement learning (RL) technique. The deep RL algorithm optimizes an artificial decision-making agent that adjusts the discharge scenario to obtain the given target βN, from the state-action-reward sets explored by trials and errors of itself in the virtual tokamak environment. The virtual environment for the RL training is constructed with the LSTM network that imitates the plasma responses by external actuator controls, which is trained from 5-year KSTAR experimental data. Then, the RL agent experiences tons of discharges with different actuator controls in the LSTM simulator, and its internal parameters are optimized in the direction of maximizing the reward. We analyze a series of KSTAR experiments conducted with the RL-determined scenarios to validate the feasibility of the beta control scheme in a real device. We discuss the successes and limitations of the feedforward beta control by RL, and suggest our future works about it.

Feedforward beta control in the KSTAR tokamak by deep reinforcement learning

Abstract Since the last IAEA Fusion Energy Conference in 2018, significant progress of the experimental program of HL-2A has been achieved on developing advanced plasma physics, edge localized mode (ELM) control physics and technology. Optimization of plasma confinement has been performed. In particular, high- β N H-mode plasmas exhibiting an internal transport barrier have been obtained (normalized plasma pressure β N reached up to 3). Injection of impurity improved the plasma confinement. ELM control using resonance magnetic perturbation or impurity injection has been achieved in a wide parameter regime, including types I and III. In addition, impurity seeding with supersonic molecular beam injection or laser blow-off techniques has been successfully applied to actively control the plasma confinement and instabilities, as well as plasma disruption with the aid of disruption prediction. Disruption prediction algorithms based on deep learning are developed. A prediction accuracy of 96.8% can be reached by assembling a convolutional neural network. Furthermore, transport resulting from a wide variety of phenomena such as energetic particles and magnetic islands has been investigated. In parallel with the HL-2A experiments, the HL-2M mega-ampere class tokamak was commissioned in 2020 with its first plasma. Key features and capabilities of HL-2M are briefly presented. 

Progress of HL-2A experiments and HL-2M program

The JET hybrid scenario has been developed from low plasma current carbon wall discharges to the record-breaking Deuterium-Tritium plasmas obtained in 2021 with the ITER-like Be/W wall. The development started in pure Deuterium with refinement of the plasma current, and toroidal magnetic field choices and succeeded in solving the heat load challenges arising from 37 MW of injected power in the ITER like wall environment, keeping the radiation in the edge and core controlled, avoiding MHD instabilities and reaching high neutron rates. The Deuterium hybrid plasmas have been re-run in Tritium and methods have been found to keep the radiation controlled but not at high fusion performance probably due to time constraints. For the first time this scenario has been run in Deuterium-Tritium (50:50). These plasmas were re-optimised to have a radiation-stable H-mode entry phase, good impurity control through edge Ti gradient screening and optimised performance with fusion power exceeding 10 MW for longer than three alpha particle slow down times, 8.3 MW averaged over 5 s and fusion energy of 45.8 MJ.

The JET hybrid scenario in Deuterium, Tritium and Deuterium-Tritium

We report the status of hybrid scenario experiments in Korea Superconducting Tokamak Advanced Research (KSTAR). The hybrid scenario is defined as stationary discharges with B N >= 2.4 and H_89 >= 2.0 at q_95 < 6.5 without or with very mild sawtooth activities in KSTAR. It is being developed towards reactor-relevant conditions. High performance of B N

https://iopscience.iop.org/article/10.1088/1741-4326/ab8b7a/pdf

On hybrid scenarios in KSTAR

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On hybrid scenarios in KSTAR