arXiv subjects

Yong-Su Na

Publications and source records attributed to Yong-Su Na.

13 recordsLinked to original sources

arXiv2026

Mechanism of Ionization Avalanche in Tokamak Microwave Gas Breakdown

Microwave breakdown driven by electron cyclotron (EC) waves provides a non-inductive route to plasma initiation in reactor-scale tokamaks. We introduce a three-dimensional Monte Carlo simulation that, for the first time, self-consistently treats nonlinear wave-particle interactions, atomic collisions, and guiding-center transport. The Monte Carlo simulation unveils the key role of parallel Brownian motion in the ionization avalanche mechanism. The predicted breakdown boundary is validated against KSTAR experiments. This work concludes that microwave gas breakdown will be successful under ITER-relevant conditions at a D$_2$ prefill pressure near 2 mPa with 1 MW of injected EC power.

physics.plasm-ph↗

arXiv2026

Extension of a multi-region free-surface MHD solver beyond the inductionless approximation

Free-surface liquid metal flows are a leading candidate for the plasma-facing components of future fusion reactors, but existing transient, three-dimensional, free-surface MHD solvers rely on the inductionless approximation, in which the induced magnetic field is neglected. This paper extends the open-source solver FreeMHD [B. Wynne et al., Phys. Plasmas 32, 013907 (2025)] beyond that approximation, resolving the induced field self-consistently with a vector-potential formulation that enforces $\nabla\cdot\boldsymbol{B}=0$ by construction while preserving the original multi-region, two-phase framework. It is verified against the analytical Shercliff and Hunt duct flows, against flows driven by a time-varying applied field, and against the deformation of a free liquid metal jet crossing a non-uniform field, and validated against free-surface height measurements from the LMX-U experiment. The experiment validates the overall free-surface solution rather than finite-$R_m$ effects, which the transient-field cases verify. To our knowledge this is the first open-source, fully three-dimensional free-surface liquid metal solver to resolve the evolution of the induced magnetic field, providing a basis for modeling the finite magnetic Reynolds number conditions expected in large-scale, transient fusion events.

physics.comp-ph↗

arXiv2026

Non-thermal electron cyclotron emission during runaway plateau in tokamak disruptions from a highly anisotropic dielectric tensor

During the runaway plateau phase in a tokamak, a cold background electron temperature of O(1 eV) forbids the onset of kinetic instability due to strong collisional damping. Nevertheless, non-thermal ECE anomalies at the level of 100 eV to keV have been observed in this phase without externally injected waves. To explore this, we characterize a highly anisotropic hot plasma medium with a Gaussian pitch-angle distribution. We derive an analytic hot plasma dielectric tensor, yielding direct expressions for the non-thermal emission coefficients and the kinetic instability drive rate. These analytic forms are verified against the KIAT and SYNO codes at small pitch-angle spread and are numerically complemented at large pitch-angle spread. Using the method of images, we define a fictitious global temperature of the entire plasma medium as measured by a horizontal ECE system. Because this representative medium temperature can exceed the keV level, the radiative temperature measured under incomplete wall reflection can be highly non-thermal without invoking any kinetic instability. This interpretation provides a conceptual basis for quantitative validation against experimental ECE measurements under realistic conditions.

physics.plasm-ph↗

arXiv2026

Fast ion effects on the threshold conditions of ion temperature gradient mode and electron temperature gradient mode

We investigate the fast ion effects on the threshold conditions of ion temperature gradient (ITG) mode and electron temperature gradient (ETG) mode both analytically and numerically using gyrokinetic equation. The onset condition for ITG mode shows a strong and monotonic favorable dependence on the fraction of fast ions, and mostly favorable but non-monotonic dependence on the fast ions' normalized temperature $T_f/T_i$ ($T_f$ is the effective temperature of fast ions, $T_i$ is the temperature of thermal ions). Overall favorable parametric trends are consistent with those for the linear growth rate reported in previous papers, as they are largely determined by kinetic wave-particle resonance effects. While general analytic expressions for the critical normalized thermal ion temperature gradient scale length $(R/L_{T_i})_c$ are quite complicated, an explicit compact expression $\left(\frac{R}{L_{T_i}}\right)_c=\left(\frac{4}{3}+\frac{3}{2}\sqrt{\fracπ{2}}\frac{|\hat{s}|}{q}\right)\left(1+\frac{T_i}{Z_i(1-f_h)T_e}\right)$ has been derived for the mode with its perpendicular scale larger than thermal ion gyroradius, but much smaller than the fast ion gyroradius so that finite Larmor radius effects are manifested in opposite asymptotic limits depending on ion species when $T_f\gg T_i$, and weak density gradient. Here, $q$ is safety factor, $\hat{s}$ is magnetic shear, $Z_i$ is thermal ions' charge, and $f_h$ is fast ion charge density fraction. In this limit, only the fast-ion-induced thermal ion dilution effects persist as fast ion density response becomes unmagnetized and negligible. On the other hand, the fast ion effects on ETG-threshold are found to be unfavorable.

physics.plasm-ph↗

arXiv2026

SPRAY: A smoothed particle radiation hydrodynamics code for modeling high intensity laser-plasma interactions

Here we report the development of SPRAY, a massively parallel GPU accelerated, smoothed particle hydrodynamics (SPH)-based, radiation hydrodynamics (RHD) code designed specifically for simulating high intensity laser-plasma interactions. When a target is irradiated by an intense laser, highly complex fluid deformation occurs due to instabilities, which is challenging to study numerically. SPRAY is particle-based, mesh-free, and Lagrangian, which addresses numerical issues that posed difficulties to existing methods. Its SPH formulations for RHD governing equations are tailored toward accurate and reliable simulations of laser-target irradiation phenomena, and are solved via a time-dependent, flux-limited diffusion method. A new laser energy coupling module, which is based on the Wentzel-Kramers-Brillouin (WKB) approximation, is implemented with a totally mesh-free ray-tracing scheme that is applicable for arbitrary geometry and dimensions. The accuracy and reliability of the code are demonstrated with a series of benchmark problems. To the authors' knowledge, this is the first attempt to employ SPH method for simulations of laser-plasma interactions in high energy density physics research. Possible expansions to the code, such as laser beam-beam interaction modeling and more sophisticated multi-group radiation transport are left for future development.

physics.comp-ph↗

arXiv2026

Gyrokinetic simulations on zonal flow-turbulence spreading coupling

Zonal flows and turbulence spreading play important roles in magnetic fusion plasma confinement, yet their coupling mechanisms remain elusive. Using global nonlinear gyrokinetic simulations, we show that turbulence spreading transports zonal flow radially, extending into the linearly stable regions after local nonlinear saturation of turbulence. Theoretical understanding has been gained by analyzing the simulation results in the context of a momentum theorem in toroidal plasmas [T.S. Hahm \textit{et al.}, Phys. Plasmas \textbf{31}, 032310 (2024)] which is an extension of the Charney-Drazin non-acceleration theorem [J.G. Charney and P.G. Drazin, J. Geophys. Res. \textbf{66}, 83 (1961)]. It indicates a direct relation between turbulence-driven enstrophy transport and perpendicular momentum generation.

physics.plasm-ph↗

arXiv2026

PanoMHD: Multimodal Modelling of Plasma Dynamics towards Tokamak Control

Modelling the dynamics of complex physical systems is a fundamental challenge, particularly where nonlinear dynamics and multi-scale interactions render traditional simulations computationally prohibitive. Nuclear fusion plasma represents a complex system where accurately predicting the plasma state, encompassing both performance and stability, is a prerequisite for active control required for sustained energy production. However, existing approaches are limited in providing a comprehensive solution as they largely focus on predicting isolated indicators such as binary stability labels. To overcome this, we present Panoramic MagnetoHydroDynamics (PanoMHD), a self-supervised multimodal framework designed to model plasma dynamics. By utilising a causal Transformer operating on tokenised representations of multimodal physical signals, PanoMHD is able to model the dynamics of high-dimensional magnetic fluctuation signals, which serve as a direct signature of plasma stability. This shifts the prediction paradigm from isolated indicators to multimodal signals. We pioneer the direct prediction of magnetic fluctuation signals for the first time, and demonstrate that this comprehensive representation enables state-of-the-art performance on KSTAR nuclear fusion plant experimental data. Our model outperforms baselines in future plasma performance prediction ($R^2=0.987$ vs. $0.957$) and surpasses dedicated classifiers in the downstream classification of distinct plasma states (L/H mode) with 97.3\% vs. 94.5\% accuracy.

physics.plasm-ph↗

arXiv2025

Collision operator for electron runaway in cold weakly-ionized plasmas

In cold weakly-ionized plasmas, Dreicer generation mechanism can be non-diffusive as demonstrated in [Y. Lee et. al. Phys. Rev. Lett. 133 17 175102 (2024)]. By expanding the previous letter, we present the detailed description of a proper collision operator to precisely account for the non-diffusive electron kinetics. The operator appropriately combines the Fokker-Planck operator and Boltzmann operator where free-bound collision cross sections are valid in low energy region. The proposed operator is envisaged to predict runaway electrons generations in cold weakly-ionized plasmas, particularly to design a runaway-free reactor tokamak startup.

physics.plasm-ph↗

arXiv2024

Multimodal Super-Resolution: Discovering hidden physics and its application to fusion plasmas

A non-linear system governed by multi-spatial and multi-temporal physics scales cannot be fully understood with a single diagnostic, as each provides only a partial view, leading to information loss. Combining multiple diagnostics may also result in incomplete projections of the system's physics. By identifying hidden inter-correlations between diagnostics, we can leverage mutual support to fill in these gaps, but uncovering such correlations analytically is too complex. We introduce a machine learning methodology to address this issue. Unlike traditional methods, our multimodal approach does not rely on the target diagnostic's direct measurements to generate its super-resolution version. Instead, it uses other diagnostics to produce super-resolution data, capturing detailed structural evolution and responses to perturbations previously unobservable. This not only enhances the resolution of a diagnostic for deeper insights but also reconstructs the target diagnostic, providing a valuable tool to mitigate diagnostic failure. This methodology addresses a key challenge in fusion plasmas: the Edge Localized Mode (ELM), a plasma instability that can cause significant erosion of plasma-facing materials. A method to stabilize ELM is using resonant magnetic perturbation (RMP) to trigger magnetic islands. However, limited spatial and temporal resolution restricts analysis of these islands due to their small size, rapid dynamics, and complex plasma interactions. With super-resolution diagnostics, we can experimentally verify theoretical models of magnetic islands for the first time, providing insights into their role in ELM stabilization. This advancement supports the development of effective ELM suppression strategies for future fusion reactors like ITER and has broader applications, potentially revolutionizing diagnostics in fields such as astronomy, astrophysics, and medical imaging.

physics.plasm-ph↗

arXiv2024

Highest Fusion Performance without Harmful Edge Energy Bursts in Tokamak

The path of tokamak fusion and ITER is maintaining high-performance plasma to produce sufficient fusion power. This effort is hindered by the transient energy burst arising from the instabilities at the boundary of high-confinement plasmas. The application of 3D magnetic perturbations is the method in ITER and possibly in future fusion power plants to suppress this instability and avoid energy busts damaging the device. Unfortunately, the conventional use of the 3D field in tokamaks typically leads to degraded fusion performance and an increased risk of other plasma instabilities, two severe issues for reactor implementation. In this work, we present an innovative 3D field optimization, exploiting machine learning, real-time adaptability, and multi-device capabilities to overcome these limitations. This integrated scheme is successfully deployed on DIII-D and KSTAR tokamaks, consistently achieving reactor-relevant core confinement and the highest fusion performance without triggering damaging instabilities or bursts while demonstrating ITER-relevant automated 3D optimization for the first time. This is enabled both by advances in the physics understanding of self-organized transport in the plasma edge and by advances in machine-learning technology, which is used to optimize the 3D field spectrum for automated management of a volatile and complex system. These findings establish real-time adaptive 3D field optimization as a crucial tool for ITER and future reactors to maximize fusion performance while simultaneously minimizing damage to machine components.

physics.plasm-ph↗

arXiv2023

Enhancing Disruption Prediction through Bayesian Neural Network in KSTAR

Disruption in tokamak plasmas, stemming from various instabilities, poses a critical challenge, resulting in detrimental effects on the associated devices. Consequently, the proactive prediction of disruptions to maintain stability emerges as a paramount concern for future fusion reactors. While data-driven methodologies have exhibited notable success in disruption prediction, conventional neural networks within a frequentist approach cannot adequately quantify the uncertainty associated with their predictions, leading to overconfidence. To address this limit, we utilize Bayesian deep probabilistic learning to encompass uncertainty and mitigate false alarms, thereby enhancing the precision of disruption prediction. Leveraging 0D plasma parameters from EFIT and diagnostic data, a Temporal Convolutional Network adept at handling multi-time scale data was utilized. The proposed framework demonstrates proficiency in predicting disruptions, substantiating its effectiveness through successful applications to KSTAR experimental data.

physics.plasm-ph↗

arXiv2023

Moment-Fourier approach to ion parallel fluid closures and transport for a toroidally confined plasma

A general method of solving the drift kinetic equation is developed for an axisymmetric magnetic field. Expanding a distribution function in general moments a set of ordinary differential equations are obtained. Successively expanding the moments and magnetic-field involved quantities in Fourier series, a set of linear algebraic equations is obtained. The set of full (Maxwellian and non-Maxwellian) moment equations is solved to express the density, temperature, and flow velocity perturbations in terms of radial gradients of equilibrium pressure and temperature. Closure relations that connect parallel heat flux density and viscosity to the radial gradients and parallel gradients of temperature and flow velocity, are also obtained by solving the non-Maxwellian moment equations. The closure relations combined with the linearized fluid equations reproduce the same solution obtained directly from the full moment equations. The method can be generalized to derive closures and transport for an electron-ion plasma and a multi-ion plasma in a general magnetic field.

physics.plasm-ph↗

arXiv2019

Electron parallel closures for various ion charge numbers

Electron parallel closures for the ion charge number $Z=1$ [J.-Y. Ji and E. D. Held, Phys. Plasmas \textbf{21}, 122116 (2014)] are extended for $1\le Z\le10$. Parameters are computed for various $Z$ with the same form of the $Z=1$ kernels adopted. The parameters are smoothly varying in $Z$ and hence can be used to interpolate parameters and closures for noninteger, effective ion charge numbers.

physics.plasm-ph↗