Disruption prediction and avoidance is a critical need for next-step tokamaks, such as ITER. Disruption Event Characterization and Forecasting (DECAF) research fully automates analysis of tokamak data to determine chains of events that lead to disruptions and to forecast their evolution allowing sufficient time for mitigation or complete avoidance of the disruption. Disruption event chains related to local rotating or global magnetohydrodynamic (MHD) modes and vertical instability are examined with warnings issued for many off-normal physics events, including density limits, plasma dynamics, confinement transitions, and profile variations. Along with Greenwald density limit evaluation, a local radiative island power balance theory is evaluated and compared to the observation of island growth. Automated decomposition and analysis of rotating tearing modes produce physical event chains leading to disruptions. A total MHD state warning model comprised of 15 separate criteria produces a disruption forecast about 180 ms before a standard locked mode detector warning. Single DECAF event analyses have begun on KSTAR, MAST, and NSTX/-U databases with thousands of shot seconds of device operation using from 0.5 to 1 × 106 tested sample times per device. An initial multi-device database comparison illustrates a highly important result that plasma disruptivity does not need to increase as βN increases. Global MHD instabilities, such as resistive wall modes (RWMs), can give the briefest time period of warning before disruption compared to other physics events. In an NSTX database with unstable RWMs, the mode onset, loss of boundary and current control, and disruption event warnings are found in all cases and vertical displacement events are found in 91% of cases. An initial time-dependent reduced physics model of kinetic RWM stabilization created to forecast the disruption chain predicts instability 84% of the time for experimentally unstable cases with a relatively low false positive rate. Instances of the disruption event chain analysis illustrate dynamics including H–L back transitions for rotating MHD and global RWM triggering events. Disruption warnings are issued with sufficient time before the disruption (on transport timescales) to potentially allow active profile control for disruption avoidance, active mode control, or mitigation.

The injection of energetic neutral particles into the plasma of magnetic confinement fusion reactors is a widely-accepted method for heating such plasmas; various types of neutral beam are also used for diagnostic purposes. Accurate atomic data are required to properly model beam penetration into the plasma and to interpret photoemission spectra from both the beam particles themselves (e.g. beam emission spectroscopy) and from plasma impurities with which they interact (e.g. charge exchange recombination spectroscopy). This paper reviews and compares theoretical methods for calculating ionization, excitation and charge exchange cross sections applied to several important processes relevant to neutral hydrogen beams, including H + Be⁴⁺ and H + H⁺. In particular, a new cross section for the proton-impact ionization of H (1s) is recommended which is significantly larger than that previously accepted at fusion-relevant energies. Coefficients for an empirical fit function to this cross section and to that of the first excited states of H are provided and uncertainties estimated. The propagation of uncertainties in this cross section in modeling codes under JET-like conditions has been studied and the newly-recommended values determined to have a significant effect on the predicted beam attenuation. In addition to accurate calculations of collisional atomic data, the use of these data in codes modeling beam penetration and photoemission for fusion-relevant plasma density and temperature profiles is discussed. In particular, the discrepancies in the modeling of impurities are reported. The present paper originates from a Coordinated Research Project (CRP) on the topic of fundamental atomic data for neutral beam modeling that the International Atomic Energy Agency (IAEA) ran from 2017 to 2022; this project brought together ten research groups in the fields of fusion plasma modeling and collisional cross section calculations. Data calculated during the CRP is summarized in an appendix and is available online in the IAEA’s atomic database, CollisionDB.

A tokamak, a torus-shaped nuclear fusion device, needs an electric current in the plasma to produce magnetic field in the poloidal direction for confining fusion plasmas. Plasma current is conventionally generated by electromagnetic induction. However, for a steady-state fusion reactor, minimizing the inductive current is essential to extend the tokamak operating duration. Several non-inductive current drive schemes have been developed for steady-state operations such as radio-frequency waves and neutral beams. However, commercial reactors require minimal use of these external sources to maximize the fusion gain, Q, the ratio of the fusion power to the external power. Apart from these external current drives, a self-generated current, so-called bootstrap current, was predicted theoretically and demonstrated experimentally. Here, we reveal another self-generated current that can exist in a tokamak and this has not yet been discussed by present theories. We report conclusive experimental evidence of this self-generated current observed in the KSTAR tokamak.

The sensitivity of the pitch angle profiles measured by the motional Stark effect (MSE) diagnostic to the evolution of the safety factor, q, profiles during the tokamak sawtooth events has been investigated for Korea Superconducting Tokamak Advanced Research (KSTAR). An analytic relation between the tokamak pitch angle, γ, and q estimates that Δγ ∼ 0.1° is required for detecting Δq ∼ 0.05 near the magnetic axis (not at the magnetic axis, though). The pitch angle becomes less sensitive to the same Δq for the middle and outer regions of the plasma (Δγ ∼ 0.5°). At the magnetic axis, it is not straightforward to directly relate the γ sensitivity to Δq since the gradient of γ(R), where R is the major radius of the tokamak, is involved. Many of the MSE data obtained from the 2015 KSTAR campaign, when calibrated carefully, can meet these requirements with the time integration down to 10 ms. The analysis with the measured data shows that the pitch angle profiles and their gradients near the magnetic axis can resolve the change of the q profiles including the central safety factor, q0, during the sawtooth events.