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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Transition in particle transport under resonant magnetic perturbations in a tokamak

Abstract Nonlinear 3D MHD simulations and validations reveal that the hybrid particle-MHD transport is a key process for driving the pump-out in the presence of Resonant Magnetic Perturbations (RMPs) in the KSTAR tokamak. Particle transport and the resulting density pump-out by RMPs are shown to be composed of not only the classical flow convection near magnetic islands due to polarization but also the neoclassical ion diffusion across perturbed magnetic surfaces. The latter is known as the Neoclassical Toroidal Viscosity (NTV) and is integrated into nonlinear MHD simulations here for the first time, revealing that the two-stage pump-outs observed in KSTAR experiments are reproduced only with such integrated nonlinear MHD and transport evolution. Near-resonant responses, which have received less attention than the resonant response, play distinct roles in the pump-out along with the island formation. In addition, this modeling is used to investigate the pump-outs in double-null-like plasmas and numerically capture the effect of the double-null shape on the pump-outs, which may explain the difficulty of Edge Localized Mode (ELM) suppression access in double-like plasmas. This reveals new aspects of the impact toroidal geometry and mode coupling have on 3D physics and reveals the importance of near-resonant components in suppressing ELMs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Impact of breech geometry and propellant flow on the release of large pellets for the ITER disruption mitigation system

Studies have been performed on the release mechanism for large pellets using high pressure gas in a shattered pellet injector. Typically, pellets are dislodged from the cryogenic surface and accelerated down a barrel using high pressure gas delivered by a fast-acting propellant valve. The pellets impact an angled surface which shatters the pellet into many small fragments before entering the plasma. This technique was initially demonstrated on DIII-D (Commaux et al 2016 Nucl. Fusion 56 046007) and is now deployed on JET, KSTAR, ASDEX-Upgrade, and other tokamaks around the world in support of ITER's disruption mitigation system design and physics basis. The large hydrogen, 28.5 mm diameter, 2 length-to-diameter ratio, pellets foreseen for ITER SPI operation have low material strength and low heat of sublimation, which cause the pellets to be fragile and highly reactive to the impact of warm propellant gas. Due to the size of the pellets, significantly more propellant gas is required to dislodge and accelerate them. This creates a potentially significant propellant gas removal issue as 2–6 bar-L of gas is expected to be required for release and speed control. The research presented in this paper is an in-depth exploration of the parameters that are keys to reliable pellet release and speed control. Computational fluid dynamics (CFD) modeling of propellant flows through various breech designs was conducted to determine the force generated on the back surface of a pellet. These simulations assumed the use of the ORNL designed flyer plate valve. CFD modeling combined with experimental measurements provide adequate insight to determine a path to an optimal valve and breech design for ITER SPI pellet release and speed control while minimizing propellant gas usage.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Predictive Integrated Modeling of Heated Tokamak Plasmas (Final Technical Report)

The research carried out by the Lehigh University fusion group during this reporting period: (1) Self-consistent predictive core-pedestal ITER scenario modeling; (2) Microtearing instabilities and electron thermal transport in standard and spherical tokamak discharges; (3) Neural network model of the Multi-Mode anomalous transport module; (4) Anomalous transport in KSTAR, JET, EAST, Alcator C-Mod and DIII-D discharges; (5) Theory for transport in magnetized plasmas; (6) Control-oriented modeling of the q-profile dynamic response in preparation for advanced scenario control in KSTAR and in EAST; (7) Modeling of edge harmonic oscillation in DIII-D QH mode discharges; (8) Elucidating plasma dynamics in Hasegawa-Wakatani turbulence by information geometry; (9) Non-linear Langevin and Fractional Fokker–Planck equations for anomalous diffusion by Levy stable processes; and (10) Investigation of the plasma shaping effects on the H-mode pedestal structure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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 OSTI2025

Extending the operational boundaries of RMP-ELM suppression with optimized 3D field control

The use of 3D magnetic fields is one of the promising approaches to control edge localized modes (ELMs), and ITER has plans to utilize a flexible 3D coil set for ELM suppression using 3D fields. This study focuses on optimizing the 3D field spectrum to expand the operational window for n = 1 resonant magnetic perturbation (RMP) ELM suppression in KSTAR. The optimized n = 1 RMP effectively suppresses ELMs throughout the entire H-mode discharge, including the first ELM crash, while avoiding the onset of disruptive locked modes in low-density L-mode plasmas. The predicted suppression window aligns well with experimental data, highlighting the challenges and solutions of using n = 1 RMP at low densities. Moreover, the optimization successfully achieved n = 1 RMP ELM suppression for the first time in ITER-relevant q 95 and shaping conditions, including cases with q95 as low as 3.6, as well as other q 95 and shape configurations. This highlights the importance and utility of 3D coil optimization while emphasizing the potential of long-wavelength low-n RMP, which will be valuable for ex-vessel coils designed to avoid complications of nuclear degradation.

3D magnetic field control↗
DOE OSTI2025

Bridging the gap: Deploying AI-based Models in Real-Time Fusion Plasma Control Systems

Achieving reliable real-time control in fusion plasma experiments requires strict timing guarantees across entire control algorithms. In earlier work by Abbate et al. (2023), we demonstrated the feasibility of neural-network-based control algorithms on the DIII-D tokamak using the internally developed open-source Keras2C library for model conversion into C (Conlin et al. (2021)). However, the initial implementations relied on data buffering and branching logic outside the neural network code, causing variability in execution times. Subsequent deployments on DIII-D and KSTAR—including the RTCAKENN algorithm for kinetic profile reconstruction—proved that minimizing branching and buffering throughout the pipeline yields consistent millisecond-level cycle times under real experimental conditions (Shousha et al. (2023)). However, keeping pace with rapidly evolving AI frameworks (e.g. PyTorch) is challenging. Finally, we, therefore, propose a community-driven open-source effort to expand the tool, enabling real-time deployment across diverse systems that require strictly bounded execution times.

AI-based models↗
DOE OSTI2024

Initial design concepts for solid boron injection in ITER

As part of ITER’s consideration to change its first wall material from beryllium to tungsten, the ITER Organization has proposed studying the feasibility of real-time solid boron injection (SBI) into the plasma to coat the walls and divertor to supplement glow discharge boronization (GDB). Boron deposits getter oxygen and reduce sputtering of tungsten from plasma facing components (PFCs). Particularly in areas with significant plasma wall interactions, boron coatings are expected to be short-lived under high performance plasma conditions. The proposed SBI system aims to maintain boron layers in these areas to avoid excessive radiation from tungsten in the plasma as a risk mitigation to ensure ITER will be able to reach and sustain Q = 10 conditions. The system will be used sparingly, as redeposition of boron can lead to significant tritium retention, which must be minimized in ITER to comply with nuclear safety concerns. SBI is proposed to limit and precisely control the amount of boron injected in real-time during plasma operation. Here, some of the design requirements and initial concepts for an SBI system in ITER are presented based on previous results carried out with SBI systems on a number of tokamaks and stellarators around the world. Previous results using SBI systems installed by PPPL have injected boron particles from 5 µm–2 mm diameter at calibrated rates of 2–200 mg/s in real-time during plasma operation on AUG, DIII-D, EAST, KSTAR, LHD, TFTR, WEST, and W7-X, leading to improved wall conditions with reduced plasma impurity concentrations and radiated power and improved plasma performance. The boron is ionized in the plasma edge and then deposited on plasma-wetted surfaces. On AUG, EAST and WEST reduced tungsten sputtering sources were observed following several discharges with SBI. Extrapolation of these SBI results are presented to estimate the amount of boron needed for wall conditioning in ITER. Real-time SBI control requirements and plasma operation scenarios for ITER are also described.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Observation of a new type of self-generated current in magnetized plasmas

A tokamak, a torus-shaped nuclear fusion device, needs an electric current in the plasma to produce magnetic field in the poloidal direction for confining fusion plasmas. Plasma current is conventionally generated by electromagnetic induction. However, for a steady-state fusion reactor, minimizing the inductive current is essential to extend the tokamak operating duration. Several non-inductive current drive schemes have been developed for steady-state operations such as radio-frequency waves and neutral beams. However, commercial reactors require minimal use of these external sources to maximize the fusion gain, Q, the ratio of the fusion power to the external power. Apart from these external current drives, a self-generated current, so-called bootstrap current, was predicted theoretically and demonstrated experimentally. Here, we reveal another self-generated current that can exist in a tokamak and this has not yet been discussed by present theories. We report conclusive experimental evidence of this self-generated current observed in the KSTAR tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Tailoring tokamak error fields to control plasma instabilities and transport

A tokamak relies on the axisymmetric magnetic fields to confine fusion plasmas and aims to deliver sustainable and clean energy. However, misalignments arise inevitably in the tokamak construction, leading to small asymmetries in the magnetic field known as error fields (EFs). The EFs have been a major concern in the tokamak approaches because small EFs, even less than 0.1%, can drive a plasma disruption. Meanwhile, the EFs in the tokamak can be favorably used for controlling plasma instabilities, such as edge-localized modes (ELMs). Here we show an optimization that tailors the EFs to maintain an edge 3D response for ELM control with a minimized core 3D response to avoid plasma disruption and unnecessary confinement degradation. We design and demonstrate such an edge-localized 3D response in the KSTAR facility, benefiting from its unique flexibility to change many degrees of freedom in the 3D coil space for the various fusion plasma regimes. This favorable control of the tokamak EF represents a notable advance for designing intrinsically 3D tokamaks to optimize stability and confinement for next-step fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Highest fusion performance without harmful edge energy bursts in tokamak

The path of tokamak fusion and International thermonuclear experimental reactor (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 plasmas. Conventional 3D magnetic perturbations used to suppress these instabilities often degrade fusion performance and increase the risk of other instabilities. This study presents an innovative 3D field optimization approach that leverages machine learning and real-time adaptability to overcome these challenges. Implemented in the DIII-D and KSTAR tokamaks, this method has consistently achieved reactor-relevant core confinement and the highest fusion performance without triggering damaging bursts. This is enabled by advances in the physics understanding of self-organized transport in the plasma edge and machine learning techniques to optimize the 3D field spectrum. The success of automated, real-time adaptive control of such complex systems paves the way for maximizing fusion efficiency in ITER and beyond while minimizing damage to device components.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Disruption event characterization and forecasting in tokamaks

Disruption prediction and avoidance is a critical need for next-step tokamaks, such as ITER. Disruption Event Characterization and Forecasting (DECAF) research fully automates analysis of tokamak data to determine chains of events that lead to disruptions and to forecast their evolution allowing sufficient time for mitigation or complete avoidance of the disruption. Disruption event chains related to local rotating or global magnetohydrodynamic (MHD) modes and vertical instability are examined with warnings issued for many off-normal physics events, including density limits, plasma dynamics, confinement transitions, and profile variations. Along with Greenwald density limit evaluation, a local radiative island power balance theory is evaluated and compared to the observation of island growth. Automated decomposition and analysis of rotating tearing modes produce physical event chains leading to disruptions. A total MHD state warning model comprised of 15 separate criteria produces a disruption forecast about 180 ms before a standard locked mode detector warning. Single DECAF event analyses have begun on KSTAR, MAST, and NSTX/-U databases with thousands of shot seconds of device operation using from 0.5 to 1 × 10 6 tested sample times per device. An initial multi-device database comparison illustrates a highly important result that plasma disruptivity does not need to increase as βN increases. Global MHD instabilities, such as resistive wall modes (RWMs), can give the briefest time period of warning before disruption compared to other physics events. In an NSTX database with unstable RWMs, the mode onset, loss of boundary and current control, and disruption event warnings are found in all cases and vertical displacement events are found in 91% of cases. An initial time-dependent reduced physics model of kinetic RWM stabilization created to forecast the disruption chain predicts instability 84% of the time for experimentally unstable cases with a relatively low false positive rate. Instances of the disruption event chain analysis illustrate dynamics including H–L back transitions for rotating MHD and global RWM triggering events. Furthermore, disruption warnings are issued with sufficient time before the disruption (on transport timescales) to potentially allow active profile control for disruption avoidance, active mode control, or mitigation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Thermal energy mitigation and toroidal peaking effects in JET disruptions

Previous investigations on JET suggest half or less of plasma stored thermal energy W th is radiated (f rad,th ≲ 0.5) using either massive gas injection (MGI) or shattered pellet injection (SPI) disruption mitigation. We investigate whether the apparent incomplete f rad,th is explained by radiation peaking near the injection plume. High toroidal peaking throughout the pre-thermal quench is found in argon–deuterium MGI on JET, with typically >3× higher radiation near the injector than toroidally distant. Previously unexplained toroidal bolometry measurements in neon–deuterium SPI are reproduced with similar peaking using the Emis3D radiation analysis code. These observations align with results from Alcator C-Mod and KSTAR. This peaking is not captured by previous JET studies that found poor thermal mitigation. Two sets of neon–deuterium SPI and two sets of argon–deuterium MGI are analyzed using Emis3D. In SPI, f rad,th rises from no-plume estimates of 0.31 and 0.66 to lower bounds of 0.84 and 0.92, respectively, and f rad,th ∼ 1 is possible. In MGI, the toroidal spread of the peaking feature is poorly constrained. f rad,th up to 0.85 and 0.65 are possible using the largest possible spread, increasing from 0.42 and 0.28, although f rad,th ∼ 1 does not appear to be reached. Revised mitigation estimates on JET suggest a lower melt risk to the divertor in mitigated disruptions on ITER and SPARC than previously thought. However, peaking near injectors could increase flash melting risk on nearby plasma facing components.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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 OSTI2022

Near real-time streaming analysis of big fusion data

Experiments on fusion plasmas produce high-dimensional data time series with ever-increasing magnitude and velocity, but turn-around times for analysis of this data have not kept up. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article, we introduce the Delta framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, Delta allows computationally expensive data analysis tasks to be performed in between plasma pulses. This article describes the modular and expandable software architecture of Delta and presents performance benchmarks of individual components as well as of an example workflow. Focusing on a streaming analysis workflow where electron cyclotron emission imaging (ECEi) data is measured at KSTAR on the National Energy Research Scientific Computing Center's (NERSC's) supercomputer we routinely observe data transfer rates of about 4 Gigabit per second. In NERSC, a demanding turbulence analysis workflow effectively utilizes multiple nodes and graphical processing units and executes them in under 5 min. We further discuss how Delta uses modern database systems and container orchestration services to provide web-based real-time data visualization. For the case of ECEi data we demonstrate how data visualizations can be augmented with outputs from machine learning models. Here, by providing session leaders and physics operators, results of higher-order data analysis using live visualizations may make more informed decisions on how to configure the machine for the next shot.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Vertical instability forecasting and controllability assessment of multi-device tokamak plasmas in DECAF with data-driven optimization

Abstract Reliable vertical position control will be an essential element of any future tokamak-based fusion power plant in order to reduce disruptions and maximize performance. We investigate methods to improve vertical controllability boundary determination in plasma operational space and demonstrate a data-driven approach based on direct pseudoinversion of operational space data that is rigorously quantitative, applicable in real-time plasma control systems, and physically intuitive to interpret. Applied to historical shot data from entire run campaigns on the MAST-U, KSTAR, and NSTX tokamaks, this approach, implemented in DECAF, improves vertical displacement event identification accuracy to 98.9%–100%. Further, we explore the application of a physics-based vertical stability metric as an early warning forecaster for vertical displacement events. The development of a linear surrogate model for the plasma current density profile, with a coefficient of determination of 0.992 on the training dataset, enables potential employment of this forecaster in real-time. The application of this approach on historical data from the MAST-U MU02 campaign yields a forecaster with 62.6% accuracy, indicating promise for this method when further refined and potentially coupled with other stability metrics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
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 OSTI2019

Controlled neoclassical tearing mode (NTM) healing by fueling pellets and its impact on electron cyclotron current drive requirements for complete NTM stabilization

Controlled partial stabilization of core m/n – 2/1 Neoclassical Tearing Modes (NTMs) by fueling deuterium pellets is reported in DIII-D and KSTAR H-mode plasmas (m=n are the poloidal/toroidal mode numbers). Analyses of DIII-D data exploring possible physics origins show that an explanation is offered by NTM-turbulence multi-scale interaction, triggered by a sudden increase of local gradients near q–2 caused by the pellet. Pellet injection from the high-field side allows deep fueling which reaches the island region. In turn, low-k turbulent density fluctuations (ñ) increase by 30% in the island region. This ñ can drive transport across the island separatrices, reducing the pressure at spot at the O-point and diminishing the NTM drive. The Mirnov probe array detects the reduction of the 2/1 magnetic amplitude by up to 20%. Causality between elevated gradients outside of the island, turbulence spreading into the island and reduced NTM drive is qualitatively supported by non-linear gyrokinetic turbulence simulations. These demonstrate increased penetration of ion-scale ñ from the background plasma to the O-point region when the background gradient is increased. This interaction has potentially far reaching consequences as it can can lead to a reduction of the required electron cyclotron current density (j ECCD ) for NTM suppression by 70%, as predicted by the modified Rutherford equation. Furthermore, this beneicial effect of fueling pellets can be important as j ECCD is the anticipated active NTM control technique for the International Thermonuclear Experimental Reactor (ITER), but its efficiency will be lowered by third harmonic absorption in Pre-Fusion Power Operation-1 (PFPO-1) at half magnetic field.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Recent progress in shattered pellet injection technology in support of the ITER disruption mitigation system*

Shattered pellet injection (SPI) has been selected as the baseline technology for the disruption mitigation (DM) system for ITER. Typical SPI utilizes cryogenic cooling to desublimate low pressure (<100 mbar) gases onto a cold zone within a pipe gun barrel, forming a cylindrical pellet. Pellets are dislodged from the barrel and accelerated using either a gas driven mechanical punch or high-pressure light-gas delivered by a fast-opening valve. SPI technology developed at Oak Ridge National Laboratory is currently deployed and operational on DIII-D, JET, and KSTAR. These SPI systems are used in experiments for physics scaling to ITER thermal mitigation and runaway electron dissipation/avoidance. The pellet sizes used for these machines are in the range of 4 to 12.5 mm in diameter with length to diameter ratios (L/D) of ~1.5. The current plan for ITER SPI is to utilize pellets that are 28.5 mm in diameter with an L/D of ~2. Furthermore, the large pellet sizes, high steady-state magnetic fields, and limitations of operating in a radiation environment render much of the current technology unusable. In addition to technology improvements, a deeper understanding of pellet material properties, formation, and release is being developed for implementation in future SPI designs, specifically ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗