arXiv subjects

Minjun J. Choi

Publications and source records attributed to Minjun J. Choi.

8 recordsLinked to original sources

arXiv2025

Leveraging turbulence data from fusion experiments

Various methods for leveraging turbulent fluctuation measurements from fusion plasma experiments are introduced, along with selected application examples. These can be categorized into spectral methods, statistical methods, and physics informed neural network based methods, and they are most effective for two-dimensional turbulence measurements, which are now widely accessible. Extracting more information from turbulence data would pave the way for a better understanding of plasma turbulence transport in fusion experiments.

physics.plasm-ph↗

arXiv2024

Mesoscopic transport in KSTAR plasmas: avalanches and the $E \times B$ staircase

The self-organization is one of the most interesting phenomena in the non-equilibrium complex system, generating ordered structures of different sizes and durations. In tokamak plasmas, various self-organized phenomena have been reported, and two of them, coexisting in the near-marginal (interaction dominant) regime, are avalanches and the $E \times B$ staircase. Avalanches mean the ballistic flux propagation event through successive interactions as it propagates, and the $E \times B$ staircase means a globally ordered pattern of self-organized zonal flow layers. Various models have been suggested to understand their characteristics and relation, but experimental researches have been mostly limited to the demonstration of their existence. Here we report detailed analyses of their dynamics and statistics and explain their relation. Avalanches influence the formation and the width distribution of the $E \times B$ staircase, while the $E \times B$ staircase confines avalanches within its mesoscopic width until dissipated or penetrated. Our perspective to consider them the self-organization phenomena enhances our fundamental understanding of them as well as links our findings with the self-organization of mesoscopic structures in various complex systems.

physics.plasm-ph↗

arXiv2022

Stochastic fluctuation and transport of tokamak edge plasmas with the resonant magnetic perturbation field

We present that a statistical method known as the Complexity-Entropy analysis is useful to characterize a state of plasma turbulence and flux in the resonant magnetic perturbation (RMP) edge localized mode (ELM) control experiment. The RMP ELM suppression phase with the stochastic pedestal top temperature fluctuation can be distinguished from the natural ELM free phase with the chaotic fluctuation. It is discussed that the stochastic temperature fluctuation localized near the pedestal top can be originated from the narrow layer of the field penetration near the pedestal top. The forced magnetic island can emit the resonant drift wave of comparable sizes (relatively low-k) in the RMP ELM suppression phase, and it can results in the generation of stochastic higher wavenumber fluctuations coupled to tangled fields around the island. The analysis of the ion saturation current measurement around the main outer striking point on the divertor shows that it also becomes more stochastic as the stronger plasma response to the RMP field is expected.

physics.plasm-ph↗

arXiv2022

Machine-Learning enabled analysis of ELM filament dynamics in KSTAR

The emergence and dynamics of filamentary structures associated with edge-localized modes (ELMs) inside tokamak plasmas during high-confinement mode is regularly studied using Electron Cyclotron Emission Imaging (ECEI) diagnostic systems. ECEI allows inference of electron temperature variations, often across a poloidal cross-section. Previously, detailed analyses of filamentary dynamics and classification of the precursors to ELM crashes have been done manually. We present a machine-learning-based model, capable of automatically identifying the position, spatial extent, and amplitude of ELM filaments. The model is a deep convolutional neural network that has been trained and optimized on an extensive set of manually labeled ECEI data from the KSTAR tokamak. Once trained, the model achieves a 93.7% precision and allows to robustly identify plasma filaments in unseen ECEI data. The trained model is used to characterize ELM filament dynamics in a single H-mode plasma shot. We identify quasi-periodic oscillations of the filaments' size, total heat content, and radial velocity. The detailed dynamics of these quantities appear strongly correlated with each other and appear qualitatively different during the pre-crash and ELM crash phases.

physics.plasm-ph↗

arXiv2020

Effects of plasma turbulence on the nonlinear evolution of magnetic island in tokamak

Magnetic islands (MIs), resulting from a magnetic field reconnection, are ubiquitous structures in magnetized plasmas. In tokamak plasmas, recent researches suggested that the interaction between the MI and ambient turbulence can be important for the nonlinear MI evolution, but a lack of detailed experimental observations and analyses has prevented further understanding. Here, we provide comprehensive two-dimensional observations that indicate various effects of the ambient turbulence on the nonlinear MI evolution. It is shown that the modified plasma turbulence around the MI can lead to either destabilization or stabilization of the MI instability in tokamak plasmas. In particular, significantly enhanced turbulence at the X-point of the MI results in a violent disruption through the fast magnetic reconnection and magnetic field stochastization.

physics.plasm-ph↗

arXiv2019

Spectral data analysis methods for the two-dimensional imaging diagnostics

Some spectral data analysis methods that are useful for the two-dimensional imaging diagnostics data are introduced. It is shown that the frequency spectrum, the local dispersion relation, the flow shear, and the nonlinear energy transfer rates can be estimated using the proper analysis methods.

physics.data-an↗

arXiv2019

Experimental evidence of the non-diffusive avalanche-like electron heat transport events and their dynamical interaction with the shear flow structure

We present experimental observations suggesting that the non-diffusive avalanche-like events are a prevalent and universal process of the electron turbulent heat transport in tokamak core plasmas. They are observed in the low confinement mode and the weak internal transport barrier tokamak plasmas in the absence of magnetohydrodynamic instabilities. In addition, the electron temperature profile corrugation, which indicates the existence of the $E \times B$ shear flow layers, is clearly demonstrated as well as their dynamical interaction with the avalanche-like events. The measured width of the profile corrugation is around $45ρ_i$, which implies the mesoscale nature of the structure.

physics.plasm-ph↗

arXiv2018

Distinct stages of radio frequency emission at the onset of pedestal collapse in KSTAR H-mode plasmas

Using a high-speed and broadband radio frequency (RF) (0.1-1 GHz) spectrum analyzer developed on the KSTAR tokamak, it is found that several distinct stages of RF emission appear at the pedestal collapse in high confinement discharges. Comparison with 2-D electron cyclotron emission (ECE) images has revealed that each stage is related to the instantaneous condition at the outboard mid-plane edge. First, high-harmonic ion cyclotron emissions (ICE) are intensified with the appearance of a non-modal filamentary perturbation in the edge within several tens of microseconds before the collapse. Then, the RF emission becomes broad toward high-frequency range (< 500 MHz) at the burst onset of the non-modal filament. During the pedestal collapse initiated by the filament burst, rapid chirping (1-3 μs) appear with additional filament bursts. The strong correlation between the RF spectra and the perturbation structure provides important clues on the stability of edge-localized modes and on the ion dynamics in the plasma boundary.

physics.plasm-ph↗