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DOE OSTI2026

The impact of kinetic and global effects on ideal ballooning 2nd stable pedestals of conventional and low aspect-ratio tokamaks

The EPED model (Snyder et al 2011 Nucl. Fusion 51 103016) has had success in describing the pedestal structure of Type-I ELM and QH-mode plasmas in tokamaks, by combining kinetic ballooning mode (KBM) and peeling–ballooning (PB) constraints. Within EPED, the KBM constraint is often approximated by a technique using calculated ideal ballooning mode (IBM) thresholds, fit to a functional form designed to capture non-local effects. It has been noted that quantitative differences between local ideal MHD and gyro-kinetic (GK) ballooning stability can be larger at low aspect ratio. KBM critical pedestals are consistent with observations in initial studies on conventional and spherical tokamaks. In this work, the application of a reduced model for the calculation of the kinetic ballooning stability boundary is presented based on a novel and newly developed gyro-fluid system (GFS) code (Staebler et al 2023 Phys. Plasmas 30 102501). GFS is observed to capture KBMs in DIII-D as well as the NSTX pedestals, opening a route to integrating this model into EPED. Finally, high but finite $n$ global ballooning modes are observed to limit the access to the local 2nd stability and thus provide a transport mechanism that constrains the pedestal evolution with $β_{p,\textrm{ped}}$. The high $n$ global ballooning stability is approximated by its ideal MHD analog using ELITE. It is shown that nearly-local high $n$ modes with $k_yρ_s$ ~ $0.25 - 0.5$ can provide a proxy for the critical $β_{p,\textrm{ped}}$ when a 2nd stable access exists on DIII-D plasmas. The use of GFS and ELITE scaling in EPED provides improved agreement to EPED1 in an initial comparison with DIII-D pedestal data.

Anastopoulos Tzanis, Michail Savvas [Oak Ridge Nat↗

DOE OSTI2026

Explainable tokamak-agnostic forecasting of fusion plasma instability via megahertz turbulent fluctuations

Scientific applications of artificial intelligence (AI) often remain limited by device-specific training and unexplained “black-box” approaches, creating fundamental barriers to cross-system generalization. This challenge is critical for nuclear fusion, where future reactors will have limited operational data for AI training. Here, we demonstrate that our neural network, trained solely on megahertz-scale turbulence measurements from one machine (DIII-D), forecasts Type-I edge localized mode (ELM) onsets in a different tokamak (KSTAR) through zero-shot weight transfer following physics-consistent preprocessing without device-specific retraining. Through an explainable AI framework combining gradient-weighted class activation mapping with physics validation, we reveal that our network can internalize physics relationships governing the ELM instabilities rather than memorizing device-specific patterns. The network perceives spatiotemporal features that correlate consistently with independently calculated instability growth rates, magnetohydrodynamic stability limits, and pedestal structure dynamics. Statistical analyses of dimensionally-reduced saliency features reveal the identical triangular features between the saliency representations, instability growth rates, and prediction probability across tokamaks, providing evidence that our forecasting system can show tokamak-agnostic generalization. This work contributes to a foundation for explainable scientific AI systems, where cross-system developments are essential for transcending traditional domain-specific constraints.

AI↗

DOE OSTI2026

Effect of controlled magnetic island bifurcation on electron diffusion

Magnetic islands strongly influence cross-field electron transport in magnetized plasmas. In particular, bifurcations of the island topology modify the number and location of O-points, X-points, and separatrix boundaries, thereby altering diffusion pathways. In recent DIII-D experiments, external magnetic perturbations were used to rotate and periodically bifurcate the island on the q = 2 surface, causing a switchback between a q = 2/1-dominated structure and a narrower q = 4/2-dominated structure. To investigate how this topological change affects electron transport, we employ the field line tracing code TRIP3D with an implemented collisional operator. Thermal, tracer electrons launched from O-points, X-points, and outside separatrix boundaries reveal distinct diffusion regimes, including classical, subdiffusive, and superdiffusive behavior, depending on both the dominant island mode and launch location. These results suggest that island bifurcation can alter electron diffusion across rational surfaces, with direct implications for particle confinement. While the present work emphasizes diffusion as a general framework, the findings provide insight into the conditions under which electron trapping into an island or stochastization of the island's separatrix can enable additional mechanisms, such as the generation of energetic electrons.

DIII-D↗

DOE OSTI2026

FullWave — A Full Wave Parallel Code for Modeling RF Fields in Hot Tokamak Plasma

FullWave is a computer code that simulates how radio-frequency (RF) waves travel and deposit energy in the hot plasma inside a fusion reactor. RF waves are used to heat the plasma and drive electrical current, which is essential for sustaining fusion reactions. The code uses a new algorithm that can handle much finer spatial detail than previous codes — more than 100 times finer — while running efficiently on national supercomputers. It incorporates a detailed physics model that captures subtle kinetic effects important for accurate prediction of wave behavior. Under this project, FullWave was extended to cover multiple RF frequency ranges relevant to present and future tokamaks, and validated against experimental parameters from the DIII-D tokamak at General Atomics. Results were published in peer-reviewed journal articles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Vacuum Neutral Transport Model in UEDGE for Tokamak Far Scrape‐Off Layer

A model for neutral transport in the far scrape-off layer (SOL) vacuum region (vacuum neutral model) has been developed and implemented in UEDGE. Free-streaming neutral trajectories between the outermost UEDGE boundary and the vessel wall are preprocessed using DEGAS2 to construct a tele-transport matrix that captures non-local neutral relocation through the vacuum. Here, this matrix is then used in UEDGE as a non-local boundary condition for the neutral equations, preserving the robustness and convergence of the implicit solver without introducing statistical noise. Simulations of a DIII-D lower single-null configuration show that the vacuum neutral model relocates neutrals from the divertor to the upstream region, increasing the outer midplane separatrix density required for detachment onset by about 30%. However, the characteristic target temperature at detachment (T e, osp ~ 3 - 4eV) and the radiation front behavior remain unchanged.

DEGAS2↗

DOE OSTI2026

Uncertainty guided online ensemble for non-stationary data streams in fusion science

Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior with distribution drifts, resulted by both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with such non-stationary data streams. Online learning techniques have been leveraged in other domains, however it has been largely unexplored for fusion applications. In this paper, we investigate online learning for continuous adaptation to drifting data streams in the prediction of Toroidal Field (TF) coils deflection at the DIII-D fusion facility. We further address the short-term performance degradation inherent to standard online learning, which arises because ground truth is unavailable at prediction time. To mitigate this issue, we propose an uncertainty-guided online ensemble framework. The method leverages the Deep Gaussian Process Approximation (DGPA) for calibrated uncertainty estimation and uses these uncertainty measures to guide a meta-algorithm that aggregates predictions from learners trained over different historical horizons. Our results show that online learning reduces prediction error by 80% compared to a static model. The online ensemble and the proposed uncertainty-guided ensemble further reduce error by approximately 6%, and 10% respectively, relative to standard single-model online learning, while also providing calibrated uncertainty estimates to support operational decision-making.

AI↗

DOE OSTI2025

Recrystallization, cracking, and erosion of dispersoid-strengthened tungsten materials during exposure to divertor plasmas

In this study, we investigated the effects of combined intense particle and heat flux exposure on advanced tungsten plasma-facing materials within the DIII-D fusion facility. Our test matrix included two types of dispersoid-strengthened tungsten (containing either 100 nm diameter TiO 2 or Ni particles), along with high-purity polycrystalline tungsten as a reference. This experiment relied on a sample geometry angled at 15° relative to the divertor surface, thereby allowing the surfaces to intercept steady-state perpendicular heat fluxes (q ⟂ ) ranging from 10.1 to 19.6 MW/m 2 . During each shot, the samples were exposed to 42 Hz edge-localized modes (ELMs), allowing us to test the material response to transient heating. We correlated the exposure conditions with extensive post-test surface composition analysis and microscopy to determine how the plasma modified each surface. The angled specimens closest to the strike point received the highest combined heat and particle flux and melted midway through the experiment. EBSD analysis revealed they were completely recrystallized throughout, with an average grain size >100 µm. On the other hand, the specimens that received a lower steady state heat flux survived with more superficial surface damage. Whereas the high-purity polycrystalline tungsten exhibited a higher surface roughness, the dispersoid-strengthened material exhibited more extensive shallow inter-granular cracking. In addition, the surface was depleted of dispersoids following plasma exposure, possibly because of evaporation and/or sputtering. The results described here provide insights into the performance of these materials in a fusion environment which can guide further optimization for use in long-pulse devices.

Kolasinski, Robert D. [Sandia National Laboratorie↗

DOE OSTI2026

Pedestal origin and extrapolation of high-density small edge-localised-modes peak parallel energy fluence in ITER and SPARC

Experimental analysis and simulations with the BOUT++ code show that small edge-localised modes (ELMs) in reactor-relevant high-density regimes originate in a region close to the separatrix and only marginally perturb the pedestal structure. The measured divertor peak parallel energy fluence (ε ∥,peak ) for a database of small ELM scenarios in DIII-D and ASDEX Upgrade can be reproduced, within 40 % accuracy on average, if an ad hoc modification of the Eich peak parallel ELM energy fluence model is applied to account for the small ELM pedestal birth location. This allows for first-order extrapolation of small-ELM divertor ε ∥,peak to ITER and SPARC, resulting in values that satisfy the nominal melting threshold of tungsten monoblocks of 12 MJ m −2 . The findings reported in this study, both via modelling and direct measurements, constitute a step forward in assessing small ELMs in high edge-collisionality scenarios as a viable plasma regime for the operation of next-generation fusion machines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Difference in neoclassical edge flows between strongly negative and positive triangularities in the XGC gyrokinetic simulation

The neoclassical baseline study of a strongly negative triangularity (NT) plasma and the corresponding positive triangularity (PT) plasma is performed using the edge-specialized, total-f gyrokinetic code (X-point Gyrokinetic Code, XGC). A DIII-D-like plasma is used, based on the negative triangularity discharge of DIII-D #193 793. An artificial positive triangularity (PT) equilibrium has been constructed to compare the edge rotation physics at the same triangularity strength but with opposite sign, while keeping the same elongation and other geometric parameters. Carbon(6+) ions are added to the deuterium plasma at an experimentally relevant level. By using the experimental profile of carbon toroidal rotation profile as an input, XGC finds that the deuteron rotation is significantly different from the carbon rotation at the inboard and outboard midplanes, mostly caused by the difference in the Pfirsch–Schlüter rotation. More importantly, a significant difference in the X-point orbit loss physics, thus the rotation source, is found between the positive and negative triangularity equilibrium models. However, it is also found that the agreement between the present neoclassical simulation and the experimental NT data is validated only within the middle of the pedestal slope, indicating the importance of edge turbulence. Finally, this study could establish a baseline for the multiphysics, multiscale studies that include turbulence of negative triangularity plasmas.

Deuterium↗

DOE OSTI2026

Global energy balance simulations of shattered pellet injection

The dynamics of shattered pellet injection (SPI) shutdowns are simulated using a time-dependent global energy balance model, based on a modification of the KPRAD framework. The new SPI particle source in the model calculates the ablation of individual pellet fragments that enter the plasma as a temporally resolved plume, thus capturing the effects of earlier fragments on the ablation of those that follow, which has a significant impact on the overall assimilation. Despite the reduced physics and the global averaging of all quantities, results from a large number of DIII-D, KSTAR, and JET experiments are well reproduced, including the plasma cooling timescales, particle assimilation, and current quench (CQ) rates. Cooling timescales and CQ rates are in good agreement for pellets containing as little as ∼1% neon, while particle assimilations are most accurate for neon fractions above ∼15% by number of atoms. Below this, the assimilation tends to be overestimated due to the lack of radial transport in the particle balance, which becomes important in the low-Z limit. Predictive simulations of mixed-composition dual-SPI shutdowns in ITER are compared against those with the 3D non-linear magnetohydrodynamic code JOREK and are found to reproduce overall trends observed in the higher-fidelity modeling across a range of injection scenarios. The general success of the model points to the critical role of energy balance in determining SPI particle assimilation and the subsequent disruption dynamics and highlights the value of these simulations for experimental interpretation and for optimizing the deployment of computationally expensive, higher-fidelity models.

energy balance model↗

DOE OSTI2026

Interpreting AI for fusion: An application to plasma profile analysis for tearing mode stability

Artificial intelligence models have demonstrated strong predictive capabilities for various instabilities in fusion devices such as Tokamaks, including tearing modes (TM), edge localized modes, and disruptive events, but their opaque nature raises concerns about safety and trustworthiness when applied to fusion power plants. Here, we present a physics-based interpretation framework using a TM prediction model as a demonstration that is validated through a dedicated DIII-D TM avoidance experiment. By applying Shapley analysis, we identify how profiles such as rotation, temperature, and density contribute to the model's prediction of TM stability. Our analysis shows that in our experimental scenario, core electron temperature and rotation peaking play the primary role in TM stability, while density changes have smaller effects on stability. We show that off-axis ion temperature stabilizes TMs, suggesting that off-axis neutral beam heating can further stabilize this scenario. This work presents a generalizable ML-based event prediction methodology, from training to physics-driven interpretation, bridging the gap between physics understanding and opaque ML models.

Farre-Kaga, Hiro J. [Princeton Univ., NJ (United S↗

DOE OSTI2026

Multimachine analysis of intermittent fluctuations in the scrape-off layer of magnetically confined fusion plasmas

Far scrape-off layer fluctuations, also known as blobs/filaments, are compared for the first time across six tokamaks: Alcator C-Mod, DIII-D, TCV, KSTAR, MAST, and MAST-U, under the context of stochastic modeling in Ohmic and low confinement mode scenarios. In this model, which well describes these fluctuations, measurements from Langmuir probes are modeled as a superposition of uncorrelated, two-sided exponential temporal pulses. The key parameters of this model are the mean waiting times between consecutive pulses, the pulse duration times and the mean of the pulse amplitudes. The study examines the influence of line-averaged density, plasma current, magnetic field and aspect ratio. The mean amplitudes and pulse waiting times increase with the line-averaged density across devices, while the pulse duration times remain constant. Whereas the variation in waiting times is gradual across the density scan, the mean amplitudes increase abruptly as the density profile broadens and flattens for Alcator C-Mod. The blob waiting times decrease with increasing plasma current and the toroidal magnetic field, while they increase with aspect ratio for conventional tokamaks. The duration times follow the same trends as the waiting times in these parameters but vary more slowly, resulting in the trends in the waiting times dominating the intermittency level of the fluctuations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Fluid-kinetic modeling of a high power density radio frequency inductively coupled positive hydrogen ion source

High power density radio-frequency (RF) inductively coupled positive ion sources are attractive candidates for next-generation neutral beam injection (NBI) systems, where higher injected power and longer pulse lengths are desired without sacrificing source reliability. Operating at absorbed power densities of order $\gt 1~\mathrm{W\,cm}^{-3}$ places these sources in a regime with stronger gas heating, higher dissociation, and non-Maxwellian electron energy distributions. The Large Uniform Plasma for Ionizing Neutrals (LUPIN) is an RF inductively coupled plasma source designed to explore this high power density regime and to provide guidance for a positive ion source upgrade for the DIII-D NBI system. LUPIN is designed to operate at up to 20 kW of RF power at 2 MHz, coupling energy through a cylindrical quartz vessel to achieve target ion current densities of $2100\,\mathrm{A\,m}^{-2}$ . This paper presents fluid-kinetic modeling of LUPIN using the hybrid plasma equipment model where electrons are treated kinetically, and the simulations reveal that electron energy distribution function transitions from nearly Maxwellian in the core to bi-Maxwellian towards the edge. Parametric simulations investigate the effects of RF power, gas pressure, and frequency on plasma density, ion flux, and uniformity. Parametric sweeps reveal that increasing power shifts the primary ionization channel from molecular to atomic with diminishing flux gains due to skin-depth contraction and gas rarefaction. Higher frequency localizes heating and increases $\mathrm{H}_2^+$ and $\mathrm{H}_3^+$ delivery to the grid, while elevated pressure boosts ionization yet hinders ion transport due to increase in collisionality.

inductively coupled plasma↗

DOE OSTI2026

Multi-machine validation of plasma initiation modelling and prospects for future devices: Predicting plasma initiation using only hardware design and control room input data

This paper reports on the generic prediction capability of full electromagnetic plasma initiation modelling with DYON, which was carried out for the first time in fusion research by the joint modelling of the International Tokamak Physics Activity—Integrating Operation Scenario group. The following devices were included in the experiment database: VEST (spherical torus, copper coils, Stainless steel wall, R/a = 0.3 m/0.2 m, V v = 3.7 m 3 ), MAST-U (spherical torus, copper coils, C wall, R/a = 0.7 m/0.5 m, V v = 55 m 3 ), EAST (conventional tokamak, superconducting coils, metallic wall, R/a = 1.85 m/0.5 m, V v = 38 m 3 ), DIII-D (conventional tokamak, copper coils, C wall, R/a = 1.67 m/0.65 m, V v = 35 m 3 ), and KSTAR (conventional tokamak, superconducting coils, C wall, R/a = 1.8 m/0.5 m, V v = 55 m 3 ). Despite the different hardware features of the devices, the required operating spaces of the loop voltage induction and prefill gas pressure for inductive plasma initiation in each device were successfully reproduced by the predictive simulations with DYON using only the individual hardware design and the control room input data for each discharge. This successful validation across multiple machines demonstrates that the full electromagnetic DYON modelling can capture the essential physics of inductive plasma initiation. The simulation settings commonly employed for all modelling and the modifications necessary to account for the discrepancies between individual devices are reported. Predictions for ITER based on the multi-machine validation indicate that a wide range of prefill gas pressures exists for the Townsend breakdown and the plasma burn-through (0.01–1.5 mPa).

DYON↗

DOE OSTI2026

Real-time avoidance of the L-mode and H-mode density limit via machine-learned stability metrics

Reliable operation of burning plasma tokamaks will require robust control strategies to avoid macroscopic instability limits such as the L-mode and H-mode density limits (LDL, HDL). In this work, we explore closed-loop avoidance of these phenomena at DIII-D using machine-learned risk metrics. Feedback control is implemented via the ‘DL Supervisor’ scheme, which regulates the chosen risk metric by reducing the density target or increasing NBI heating in real-time. Using the LDL 25 risk metric, the LDL is reproducibly suppressed. We also introduce an HDL risk metric in this study, HDL 25 , which reduces the False Positive Rate by 2x compared to the Greenwald fraction. Applying this scaling to a plasma current ramp-down, we successfully avoid an HDL-driven H/L back-transition. These experiments constitute the first demonstration of real-time DL avoidance using machine-learned risk metrics. These instability metrics outline a path to safer high-density operation, more reliable ramp-down scenarios, and improved off-normal control for next-step devices such as ITER and SPARC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Demonstration of tokamak vertical stability control based on non-inductive Faraday-effect polarimetry measurements

Long-pulse or steady-state fusion reactors are envisioned to control vertical stability based on non-inductive measurements, i.e. that do not rely on temporal change of magnetic field. For the first time, vertical stability control using non-inductive Faraday-effect polarimetry measurements has been demonstrated. The Radial Interferometer-Polarimeter system on DIII-D is capable of microsecond resolution and was used to absolutely determine the vertical position of the plasma magnetic axis Z 0 . A vertical stability controller was developed to robustly stabilize diverted plasmas using Faraday-based measurements. The system was able to stabilize against vertical displacement events with growth rates up to 350 s -1 in elongated and elliptical plasma shapes, and instabilities with even higher growth rates are likely to be controllable with further improvements to controller tuning. Tests show that the Faraday-based controller remains effective and is capable of recovering from loss of control even when the plasma vertical position is far from the region where the linear model used to calculate Z 0 is most valid. Faraday control has also been activated during plasma ramp-up, demonstrating the robustness of the technique to larger systematic diagnostic uncertainty at low electron density.

Faraday-effect polarimetry↗

DOE OSTI2026

Permanent magnets for ELM suppression in tokamaks: feasibility and operational compatibility

Permanent magnets can provide static magnetic fields without power supplies or feed lines, offering a simpler alternative to conventional electromagnets in tokamaks. This work examines permanent magnet arrays (PMAs) for edge localized mode (ELM) control in double-null (DN) configurations, where traditional RMP coils exhibit limited effectiveness. Linear plasma response calculations using IPEC assess high-field-side (HFS) permanent magnet placement, benchmarking performance against DIII-D low-field-side (LFS) internal coils (I-coils) while evaluating engineering constraints. Modeling results demonstrate that HFS permanent magnet configurations generate HFS plasma response amplitudes more than 5 times larger than conventional I-coil systems. While other resonant response metrics show comparable or reduced response relative to I-coils, the combination of conventional RMP systems and permanent magnets is expected to provide enhanced performance. Operational impact assessments of persistent magnetic fields, including sideband field effects and startup/ramp-up compatibility, reveal acceptable performance within established operational boundaries. This analysis establishes PMAs as a technically viable approach for DN ELM control with reductions in system complexity, motivating further experimental validation on existing tokamak facilities.

3D magnetic perturbation↗

DOE OSTI2026

First observation of currents induced by Alfven eigenmodes in a magnetic confinement device

Instabilities driven by energetic particles normally reduce fusion power but recent studies find Alfven eigenmode instabilities can drive ``zonal" flows and currents that reduce thermal transport, improving overall performance. Motional Stark effect (MSE) data from the DIII-D tokamak reveal changes in magnetic pitch angle during the phase when Alfven-eigenmode nonlinearity drives zonal flows, suppresses microturbulence, and increases the electron and ion temperatures. Finally, measured changes in safety factor of ∆q/q ≃ 5% occur in roughly 20 ms, consistent with a rough estimate based on the measured zonal flow.

Heidbrink, W. W. [Univ. of California, Irvine, CA ↗