11 citations · 45 across the 14 of their papers we have counts for
17 papers
IGNITE Tokamak World Model Architecture
Peter Steiner, Azarakhsh Jalalvand, Nathaniel Chen +4
We introduce IGNITE, a generative world foundation model for fusion plasma behavior simulation trained in a self-supervised manner from over a decade of unlabeled experimental data…
Towards Large-Scale Heterogeneous Data Organization for Scientific Foundation Models: A Nuclear Fusion Case Study
Nathaniel Chen, Kouroche Bouchiat, Peter Steiner +3
Training effective foundation models requires massive and organized datasets, yet scientific domains such as nuclear fusion present unique challenges due to largely heterogeneous a…
Real-time feedback control of ELM frequency using divertor gas puffing and its effects on tungsten-induced radiation and plasma performance in KSTAR
Minseok Kim, Young-Ho Lee, SangKyeun Kim +10
The edge-localized mode (ELM) frequency () was successfully controlled in real time on KSTAR using a proportional-integral (PI) feedback controller, employing a $…
Characterization of ELM Pacing via Vertical Jogs on DIII-D
Kei Yasoda, Dario Panici, Andrew Oak Nelson +3
Edge localized mode (ELM) pacing via vertical plasma oscillations or jogging has been successfully demonstrated on DIII-D. Rapid vertical movement of the plasma toward the X-point…
FPGA-Accelerated Real-Time Diagnostics at DIII-D Using the SLAC Neural Network Library for ML Inference
Abhilasha Dave, Semin Joung, SangKyeun Kim +11
In this work, we demonstrate the deployment of a hardware-accelerated machine learning (ML) inference system integrated into a real-time processing at the DIII-D tokamak fusion rea…
Comparison of plasma response models for RMP effects on the divertor and scrape-off layer in KSTAR
H. Frerichs, J. Van Blarcum, T. Cote +3
Resonant magnetic perturbations (RMPs) are beneficial for control of edge localized modes (ELMs) in tokamaks. Nevertheless, a side effect is the appearance of a helical striations…
FPGA-Accelerated Real-Time Beam Emission Spectroscopy Diagnostics at DIII-D Using the SLAC Neural Network Library for ML Inference
Abhilasha Dave, James Russell, Mudit Mishra +9
Achieving reliable real-time control of tokamak plasmas is essential for sustaining high-performance operation in next-generation fusion reactors. A major challenge is the accurate…
Enabling Integrated AI Control on DIII-D: A Control System Design with State-of-the-art Experiments
Andrew Rothstein, Hiro Joseph Farre-Kaga, Jalal Butt +7
We present the design and application of a general algorithm for Prediction And Control using MAchiNe learning (PACMAN) in DIII-D. Machine learing (ML)-based predictors and control…
Control of pedestal-top electron density using RMP and gas puff at KSTAR
Minseok Kim, S. K. Kim, A. Rothstein +20
We report the experimental results of controlling the pedestal-top electron density by applying resonant magnetic perturbation with the in-vessel control coils and the main gas puf…
Regulation Compliant AI for Fusion: Real-Time Image Analysis-Based Control of Divertor Detachment in Tokamaks
Nathaniel Chen, Cheolsik Byun, Azarakash Jalalvand +7
While artificial intelligence (AI) has been promising for fusion control, its inherent black-box nature will make compliant implementation in regulatory environments a challenge. T…
TorbeamNN: Machine learning based steering of ECH mirrors on KSTAR
Andrew Rothstein, Minseok Kim, Minho Woo +12
We have developed TorbeamNN: a machine learning surrogate model for the TORBEAM ray tracing code to predict electron cyclotron heating and current drive locations in tokamak plasma…
Interpreting AI for Fusion: an application to Plasma Profile Analysis for Tearing Mode Stability
Hiro J Farre-Kaga, Andrew Rothstein, Rohit Sonker +6
AI models have demonstrated strong predictive capabilities for various tokamak instabilities--including tearing modes (TM), ELMs, and disruptive event--but their opaque nature rais…
Gyrokinetic simulations of the effects of magnetic islands on microturbulence in KSTAR
Xishuo Wei, Javier H Nicolau, Gyungjin Choi +8
Gyrokinetic simulations are utilized to study effects of magnetic islands on the ion temperature gradient (ITG) turbulence in the KSTAR tokamak with resonant magnetic perturbations…
Multimodal Super-Resolution: Discovering hidden physics and its application to fusion plasmas
Azarakhsh Jalalvand, SangKyeun Kim, Jaemin Seo +6
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 t…
Operational Space and Plasma Performance with an RMP-ELM Suppressed Edge
C. Paz-Soldan, S. Gu, N. Leuthold +14
The operational space and global performance of plasmas with edge-localized modes (ELMs) suppressed by resonant magnetic perturbations (RMPs) are surveyed by comparing AUG, DIII-D,…
Stochastic fluctuation and transport of tokamak edge plasmas with the resonant magnetic perturbation field
Minjun J. Choi, Jae-Min Kwon, Juhyung Kim +17
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…
Electron parallel closures for various ion charge numbers
Jeong-Young Ji, Sang-Kyeun Kim, Eric D. Held +1
Electron parallel closures for the ion charge number [J.-Y. Ji and E. D. Held, Phys. Plasmas \textbf{21}, 122116 (2014)] are extended for . Parameters are comput…