General Atomics is an American energy and defense corporation headquartered in San Diego, California, specializing in research and technology development. This includes physics research in support of nuclear fission and nuclear fusion energy. The company also provides research and manufacturing services for remotely operated surveillance aircraft, including the Predator drones; airborne sensors; and advanced electric, electronic, wireless, and laser technologies.
This study reports the development of CO_2 laser interferometers for electron density measurements on the large helical device (LHD). Two types of interferometers using approximately 10 μ m are developed. One is an imaging two-color laser interferometer (I-TCI) for measuring density profiles and macroscopic fluctuations of MHD instabilities, and the other is a single channel phase-modulated dispersion interferometer (PMDI) designed for reliable density monitoring. The diagnostic principles, systems, and analysis techniques are outlined, and representative measurement results are presented. The I-TCI system was also designed to operate in the deuterium experiments performed on LHD from 2017 until 2022. Shielding against neutron and γ -ray irradiation was necessary to prevent damage to the I-TCI detection system. Design strategies for neutron and γ -ray shielding are presented in the appendices.
Helicon waves (also known as whistler waves) satisfying the normal wave-particle cyclotron resonance are observed to limit the growth and maximum energy of relativistic electrons (REs) in low-density Ohmic DIII-D tokamak plasmas. Following the application of helicon waves, pitch-angle scattering of high-energy REs causes an increase in both synchrotron and electron-cyclotron emissions. The hard x-ray emission, a proxy for the RE population, ceases to grow. Energy-resolved hard x-ray measurements also show a striking decrease in the number of high-energy REs (above the resonance at approximately 8 MeV) to below the noise floor and an increase in low-energy (∼4 MeV) REs. This occurs despite the toroidal electric field remaining high enough to drive exponential RE growth in the absence of helicon waves. These results open new directions for limiting the maximum energy of RE populations in laboratory and fusion plasmas.
A large-scale database of two-dimensional UEDGE simulations has been developed to study detachment physics in KSTAR and to support surrogate models for control applications. Nearly 70 000 steady-state solutions were generated, systematically scanning upstream density, input power, plasma current, impurity fraction, and anomalous transport coefficients, with magnetic and electric drifts across the magnetic field included. The database identifies robust detachment indicators, with strike-point electron temperature at detachment onset consistently Te,target similar to 3-4 eV, largely insensitive to upstream conditions. Scaling relations reveal weaker impurity sensitivity than one-dimensional models and show that heat flux widths follow Eich's scaling only for uniform, low D and chi. Distinctive in-out divertor asymmetries are observed in KSTAR, differing qualitatively from DIII-D. Complementary time-dependent simulations quantify plasma response to gas puffing, with delays of 5-15 ms at the outer strike point and similar to 40 ms for the low-magnetic-field-side radiation front. These dynamics are well captured by first-order-plus-dead-time models and are consistent with experimentally observed detachment-control behavior in KSTAR (Gupta et al 2025 Plasma Phys. Control. Fusion (submitted)).
The trapped Gyro-Landau Fluid (TGLF) model provides fast, accurate predictions of turbulent transport in tokamaks, but whole device simulations requiring thousands of evaluations remain computationally expensive. Neural network (NN) surrogates offer accelerated inference with fully differentiable approximations that enable gradient-based coupling but typically require large training datasets to capture transport flux variations across plasma conditions, creating significant training burden and limiting applicability to expensive gyrokinetic simulations. We propose TGLF-WINN (Wavenumber-Informed NN) with three key innovations: (1) principled feature engineering that reduces target prediction range, simplifying the learning task; (2) physics-guided wavenumber-resolved regularization to improve generalization under sparse data; and (3) Bayesian active learning (BAL) to strategically select training samples based on model uncertainty, reducing data requirements while maintaining accuracy. TGLF-WINN is engineered for data-efficient and robust surrogate training. Feature tuning and wavenumber regularization together deliver a 12.5% relative RMSLE reduction over TGLF-NN when trained on the complete dataset; more importantly, under sparse, unfiltered training conditions (approximately 1/9 the full dataset size) these two ingredients yield an order-of-magnitude smaller RMSLE degradation than TGLF-NN, a robustness attributable to the wavenumber-informed regularization imposing a physics-guided constraint on per-mode flux contributions. Adding BAL on top, TGLF-WINN matches TGLF-NN's full-data offline accuracy using only 25% of the training data, reaching RMSLE within 2.8% of TGLF-NN's full-data baseline and within 4.3% of our own full-data result. We further demonstrate practicality in a downstream flux-matching workflow: the NN surrogate provides a 45 & times; speedup over TGLF while maintaining comparable reconstruction accuracy.
The high-power helicon wave system in the DIII-D tokamak introduces new plasma–material interaction (PMI) challenges due to rectified RF sheath potentials forming near antenna structures and surrounding tiles. Using the STRIPE modeling framework-which integrates SOLPS-ITER, COMSOL, RustBCA, and GITR/GITRm-we simulate carbon erosion, re-deposition, and global impurity transport in two H-mode discharges with varying antenna–plasma gaps and RF powers. COMSOL predicts rectified sheath potentials of 1-5 kV, localized near the bottom of the antenna where magnetic field lines intersect at grazing angles. Erosion is dominated by carbon self-sputtering, with RF-accelerated D+ ions contributing up to 1
