Avoiding fusion plasma tearing instability with deep reinforcement learning

J Seo, SK Kim, A Jalalvand, R Conlin, A Rothstein… - Nature, 2024 - nature.com
For stable and efficient fusion energy production using a tokamak reactor, it is essential to
maintain a high-pressure hydrogenic plasma without plasma disruption. Therefore, it is …

Solving real-world optimization tasks using physics-informed neural computing

J Seo - Scientific Reports, 2024 - nature.com
Optimization tasks are essential in modern engineering fields such as chip design,
spacecraft trajectory determination, and reactor scenario development. Recently, machine …

Past rewinding of fluid dynamics from noisy observation via physics-informed neural computing

J Seo - Physical Review E, 2024 - APS
Reconstructing the past of observed fluids has been known as an ill-posed problem due to
both numerical and physical challenges, especially when observations are distorted by …

Effect of coherent edge-localized mode on transition to high-performance hybrid scenarios in KSTAR

Y Lee, SK Kim, JW Kim, B Kim, MS Park… - Nuclear …, 2023 - iopscience.iop.org
This paper deals with one of the origins and trigger mechanisms responsible for the
observed performance enhancements in the hybrid scenario experiments conducted in …

Investigation of performance enhancement by balanced double-null sha** in KSTAR

B Kim, MS Park, YH Lee, SK Kim, CY Lee… - Nuclear …, 2023 - iopscience.iop.org
We report experimental observations on the effect of plasma boundary sha** towards
balanced double-null (DN) configuration on the plasma performance in KSTAR. The …

Nonperturbative theory of the low-to-high confinement transition through stochastic simulations and information geometry: Correlation and causal analyses

EJ Kim, AA Thiruthummal - Physical Review E, 2024 - APS
The low-to-high confinement (LH) transition signifies one of the important plasma
bifurcations occurring in magnetic confinement plasmas, with vital implications for exploring …

[HTML][HTML] Leveraging physics-informed neural computing for transport simulations of nuclear fusion plasmas

J Seo, IH Kim, H Nam - Nuclear Engineering and Technology, 2024 - Elsevier
For decades, plasma transport simulations in tokamaks have used the finite difference
method (FDM), a relatively simple scheme to solve the transport equations, a coupled set of …

Plasma self-driven current in tokamaks with magnetic islands

WX Wang, MG Yoo, EA Startsev, S Kaye, S Ethier… - Nuclear …, 2024 - iopscience.iop.org
Magnetic island perturbations may cause a reduction in plasma self-driven current that is
needed for tokamak operation. A novel effect on tokamak self-driven current revealed by …

Probabilistic theory of the LH transition and causality

E Kim, AA Thiruthummal - Plasma Physics and Controlled Fusion, 2025 - iopscience.iop.org
The low-to-high confinement (LH) transition is critical for understanding plasma bifurcations
and self-organization in high-temperature fusion plasmas. This paper reports a probabilistic …

Avoiding tokamak tearing instability with artificial intelligence

E Kolemen, J Seo, R Conlin, A Rothstein, SK Kim… - 2023 - researchsquare.com
For stable and efficient fusion energy production using a tokamak reactor, maintaining high-
pressure hydrogenic plasma without plasma disruption is essential. Therefore, it is …