Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2110.13335

A self-consistent multi-component model of plasma turbulence and kinetic neutral dynamics for the simulation of the tokamak boundary

A. Coroado·P. Ricci
View original source ↗Read source document ↗Export metadata ↓

Abstract

A self-consistent model is presented for the simulation of a multi-component plasma in the tokamak boundary. A deuterium plasma is considered, with the plasma species that include electrons, deuterium atomic ions and deuterium molecular ions, while the deuterium atoms and molecules constitute the neutral species. The plasma and neutral models are coupled via a number of collisional interactions, which include dissociation, ionization, charge-exchange and recombination processes. The derivation of the three-fluid drift-reduced Braginskii equations used to describe the turbulent plasma dynamics is presented, including its boundary conditions. The kinetic advection equations for the neutral species are also derived, and their numerical implementation discussed. The first results of multi-component plasma simulations carried out by using the GBS code are then presented and analyzed, being compared with results obtained with the single-component plasma model.

Explore related subjects

physics.plasm-phphysics.comp-ph

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

A. Coroado, P. Ricci. 2021-10-26. A self-consistent multi-component model of plasma turbulence and kinetic neutral dynamics for the simulation of the tokamak boundary. https://doi.org/10.1088/1741-4326%2Fac47b8

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Runaway electron interactions with whistler waves in tokamak plasmas: energy-dependent transport scaling

Resonant interactions between high energy runaway electrons (REs) and whistler waves are a promising mechanism for RE mitigation in tokamak plasmas. While prior studies have largely relied on quasi-linear diffusion models in simplified geometries, we present a first-principles-informed framework that models RE-whistler interactions in a 3D tokamak equilibrium. This is achieved by coupling AORSA, which computes whistler eigenmodes for a given tokamak plasma equilibrium, and KORC, a kinetic orbit code that tracks full orbit RE trajectories in prescribed wave fields. Our results demonstrate that REs undergo scattering to large pitch angles and exhibit anomalous diffusion in both pitch-angle and kinetic energy space. Crucially, we observe a transition between diffusive, sub-diffusive, and super-diffusive transport regimes as a function of initial RE energy - an effect not captured by existing quasi-linear models. This anomalous transport behavior represents a significant advancement in understanding RE dynamics in the presence of wave - particle interactions. By identifying the conditions under which anomalous diffusion arises, this work lays the theoretical foundation for designing targeted, wave-based mitigation strategies in future tokamak experiments.

physics.plasm-ph↗
arXiv2026

Geodesic Acoustic Modes in pair plasmas confined in tokamak magnetic fields

This paper is devoted to the derivation of the dispersion relation of the Geodesic Acoustic Mode in pair plasmas, i.e. assuming that ions and electrons have the same mass. Geodesic Acoustic Modes are plasma perturbations playing a crucial role in turbulence regulation, and therefore in the determination of the plasma confinement in tokamaks. Experiments with pair plasmas, like electron-positron plasmas, have been proposed with different kinds of confinements, and aim to study fundamental processes in plasma physics and understanding the formation of the early universe.

physics.plasm-ph↗
arXiv2026

Horizon-Aware Early Event Prediction for Tokamak Disruption Alarms

Reliable disruption prediction is essential for the safe operation of future tokamaks. Existing full-distribution survival methods model the complete residual time-to-disruption distribution, whereas operational decisions primarily depend on disruption risk within a finite prediction horizon. This mismatch motivates introducing Early Event Prediction (EEP) objectives into survival-based disruption prediction. We take Deep Survival Machines (DSM) as the full-distribution baseline and propose applying two established EEP methods to tokamak disruption prediction: Temporal Label Smoothing (TLS), which directly predicts disruption probability within a finite horizon, and survTLS, which additionally models the event-time distribution within that horizon. Using a common causal encoder, we compare these methods on DIII-D, Alcator C-Mod, and EAST. We distinguish threshold-free deadline ranking from validation-selected fixed-policy alarm performance and evaluate prediction horizons and encoder architectures. TLS achieves the best mean alarm performance on DIII-D and EAST, whereas all methods perform poorly on Alcator C-Mod. survTLS does not consistently outperform DSM, suggesting that directly learning horizon-level event probability is more effective than modeling detailed within-horizon event-time distributions in the present setting. Finally, the selected prediction horizons and encoder-ablation results vary across devices, reflecting differences in disruption characteristics.

physics.plasm-ph↗