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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 361 records · Page 20
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DOE OSTI2024

Automated experimental design of safe rampdowns via probabilistic machine learning

Abstract Typically the rampdown phase of a shot consists of a decrease in current and injected power and optionally a change in shape, but there is considerable flexibility in the rate, sequencing, and duration of these changes. On the next generation of tokamaks it is essential that this is done safely as the device could be damaged by the stored thermal and electromagnetic energy present in the plasma. This works presents a procedure for automatically choosing experimental rampdown designs to rapidly converge to an effective rampdown trajectory. This procedure uses probabilistic machine learning methods paired with acquisition functions taken from Bayesian optimization. In a set of 2022 experiments at DIII-D, the rampdown designs produced by our method maintained plasma control down to substantially lower current and energy levels than are typically observed. The actions predicted by the model significantly improved as the model was able to explore over the course of the experimental campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Shadow masks predictions in SPARC tokamak plasma-facing components using HEAT code and machine learning methods

Here, this work uses machine learning (ML) to complement HEAT (Heat flux Engineering Analysis Toolkit) by developing 3-D footprint surrogate models for fast and accurate heat load calculations in the divertor of the SPARC tokamak. The focus is on shadowed regions, or magnetic shadows, caused by the 3-D geometry of plasma-facing components (PFCs). ML classifiers are employed to create a surrogate model for HEAT generated shadow masks, predicting these shadow masks and divertor heat flux profiles based on a diverse range of equilibria and only the plasma current, safety factor(q95) at the edge, and magnetic flux angles as input parameters. The ultimate goal is to integrate the model for real-time control and future operational decisions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Probabilistic locked mode predictor in the presence of a resistive wall and finite island saturation in tokamaks

We present a framework for estimating the probability of locking to an error field in a rotating tokamak plasma. This leverages machine learning methods trained on data from a mode-locking model, including an error field, resistive magnetohydrodynamics modeling of the plasma, a resistive wall, and an external vacuum region, leading to a fifth-order ordinary differential equation (ODE) system. It is an extension of the model without a resistive wall introduced by Akçay et al. [Phys. Plasmas 28, 082106 (2021)]. Tearing mode saturation by a finite island width is also modeled. We vary three pairs of control parameters in our studies: the momentum source plus either the error field, the tearing stability index, or the island saturation term. The order parameters are the time-asymptotic values of the five ODE variables. Normalization of them reduces the system to 2D and facilitates the classification into locked (L) or unlocked (U) states, as illustrated by Akçay et al., [Phys. Plasmas 28, 082106 (2021)]. This classification splits the control space into three regions: L̂, with only L states; Û, with only U states; and a hysteresis (hysteretic) region Ĥ, with both L and U states. In regions L̂ and Û, the cubic equation of torque balance yields one real root. Region Ĥ has three roots, allowing bifurcations between the L and U states. The classification of the ODE solutions into L/U is used to estimate the locking probability, conditional on the pair of the control parameters, using a neural network. We also explore estimating the locking probability for a sparse dataset, using a transfer learning method based on a dense model dataset.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Bifurcation from L-mode to internal transport barrier triggered by a magnetic island in tokamak plasmas

Magnetic islands are believed to be responsible for triggering the internal transport barrier (ITB) around the rational surface and hence improves confinement in magnetic confinement fusion plasma, for more than two decades. Although some recent theoretical or modelling works support this hypothesis, the direct experimental demonstration on the ITB triggered by a magnetic island is still missing. Here, we report the first experimental observation that the increase in the magnetic island width triggers the bifurcation of the plasma transport state from a low confinement mode (L-mode) to an ITB mode in tokamak plasma. At medium island widths, the bifurcation appears with a dithering phase, i.e. plasma transitions from L-mode to ITB or vice versa quasi-periodically. As the island width further increases, the dithering ITB transitions into a steady ITB. The electron temperature gradient inside the ITB increases with island width. The trigger of the ITB and further enhancement of the ITB performance are also demonstrated by locking the island via applying a resonant magnetic perturbation field. The reduction of density fluctuations in the ITB region is observed and indicates turbulence suppression during ITB formation. These findings offer new insights for understanding ITB formation and robust ITB control.

internal transport barrier↗
DOE OSTI2025

Assessing time-dependent temperature profile predictions using reduced transport models for high performing NSTX plasmas

Time-dependent, predictive simulations were performed with the 1.5D tokamak integrated modeling code TRANSP on a large set of well-analyzed, high performing discharges from the National Spherical Torus Experiment (NSTX) in order to evaluate how well modern reduced transport models can reproduce experimentally observed temperature profiles in spherical tokamaks. Overall, it is found that simulations using the Multi-Mode Model (MMM) more consistently agree with the NSTX observations than those using the Trapped Gyro-Landau Fluid (TGLF) model, despite TGLF requiring orders of magnitude greater computational cost. When considering all examined discharges, MMM has median overpredictions of electron temperature (T e ) and ion temperature (T i ) profiles of 28% and 27%, respectively, relative to the experiment. TGLF overpredicts T e by 46%, with much larger variance than MMM, and underpredicts T i by 25%. As the ratio of kinetic to magnetic field pressure (β) is increased across NSTX discharges, TGLF predicts lower T e and significant flattening of the T i profile, conflicting with NSTX observations. When using an electrostatic version of TGLF, both T e and T i are substantially overpredicted, underscoring the importance of electromagnetic turbulence in the high β spherical tokamak regime. Additionally, calculations with neural net surrogate models for TGLF were performed outside of TRANSP with a time slice flux matching transport solver, finding better agreement with experiment than the TRANSP simulations, highlighting the impact of different transport solvers and simulation techniques. Furthermore, the reasonable agreement with experiment of temperature profiles predicted by MMM motivates a more detailed examination of the sensitivities of the TRANSP simulations with MMM to different NSTX plasma regimes in a companion paper (Lestz et al Plasma Phys. Control. Fusion 67 105030), in preparation for self-consistent, time-dependent predictive modeling of NSTX-U scenarios.

Lestz, J. B. [General Atomics, San Diego, CA (Unit↗
DOE OSTI2025

Similarity for downscaled kinetic simulations of electrostatic plasmas: Reconciling the large system size with small Debye length

A simple similarity has been proposed for kinetic (e.g., particle-in-cell) simulations of plasma transport that can effectively address the long-standing challenge of reconciling the tiny Debye length with the vast system size. This applies to both transport in unmagnetized plasma and parallel transport in magnetized plasmas, where the characteristics length scales are given by the Debye length, collisional mean free paths, and the system or gradient lengths. The controlled scaled variables are the configuration space, x/L, and an artificial Coulomb Logarithm, L ln Λ, for collisions, while the scaled time, t/L, and electric field, LE, are automatic outcomes. The similarity properties are examined, demonstrating that the macroscopic transport physics is preserved through a similarity transformation while keeping the microscopic physics at its original scale of Debye length. To showcase the utility of this approach, two examples of 1D plasma transport problems were simulated using the VPIC code: the plasma thermal quench in tokamaks [Li et al., Nuclear Fusion 63, 066030 (2023)] and the plasma sheath in the high-recycling regime [Li et al., Physics of Plasmas 30, 063505 (2023)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Observation of stationary filaments with resonant magnetic perturbations in NSTX

The application of resonant magnetic perturbations (RMPs) induces striated heat fluxes on the divertor plate in tokamaks. These striated heat fluxes were previously considered strike point splitting by the intersection between the divertor and predicted magnetic lobe structures. Recently, the existence of stationary 3D filaments has been observed for the first time in National Spherical Torus Experiment (NSTX) plasmas with toroidal mode number n = 3 RMPs. Magnetic field line tracing of these filaments from the midplane to the divertor is consistent with the quantity and the radial and toroidal location of striated heat fluxes observed on the divertor. This study suggests that divertor striated heat flux patterns are linked to these stationary filaments rather than to strike point splitting or magnetic lobe structures for NSTX. This finding will help guide future efforts to understand the heat flux striations in NSTX with RMPs in order to control and reduce the divertor peak heat flux.

RMPs↗
DOE OSTI2026

Interpretation of high-harmonic fast-wave propagation in the scrape-off layer of NSTX-U as a geometrically bounded-waveguide mode

This paper revisits the onset of high-harmonic fast-wave (HHFW) propagation in the scrape-off layer (SOL) plasma of the NSTX/NSTX-U spherical tokamak, motivated by past HHFW heating and current drive experiments and modelling. Previously, the fast-wave propagation in the SOL was correlated with the opening (suppression) of the fast-wave right-hand cutoff layer in front of the antenna. In this work, the SOL propagation is interpreted as a geometric waveguide mode guided by the SOL geometry, whose radial width can be comparable to the wave’s perpendicular wavelength in the HHFW regime. A two-dimensional circular model is first employed using full-wave solvers to characterise the poloidal eigenmode structures and to clarify their relationship to annulus resonance. By progressively adding a tokamak-like magnetic-field configuration, starting from a uniform axial field, the effects of magnetic-field gradients and pitch on the SOL waveguide mode are characterised. The poloidal mode numbers supported by the SOL plasma agree well with analytic estimates, indicating that an anisotropic plasma in a bounded geometry selectively supports and amplifies the resonant poloidal mode number. Additionally, two-dimensional axisymmetric NSTX-U simulations demonstrate that the SOL eigenmode features identified in the circular model persist in the experimentally relevant configurations. A control approach based on lengthening the wave perpendicular wavelength relative to the SOL width, including a higher magnetic (B)-field operation, is discussed. The analysis here shows the key role of a bounded geometry in interpreting HHFW eigenmode coupling and propagation in the NSTX-U SOL plasma.

plasma heating↗
DOE OSTI2021

Observation of fully detached divertor integrated with improved core confinement for tokamak fusion plasmas

Integration of divertor detachment with a high-performance (β N ~ 3, β p > 2, H 98 ~ 1.5) core plasma has been demonstrated in DIII-D high-β p (poloidal beta) plasmas associated with a sustained core internal transport barrier (ITB) and an H-mode edge transport barrier (ETB). Such good core-edge integration has been achieved for both neon and nitrogen seeding, for both favorable and unfavorable B-field directions, independently from the impurity puffing locations, though these variations play important roles on divertor characteristics. Compared to the standard H-mode plasmas, the high-β p plasma exhibits a much wider window of detachment compatible with high confinement core. Fully detached divertor plasmas with low plasma temperature (Te < 5 eV), low particle flux, and low heat flux across the entire divertor target plate were obtained by using nitrogen seeding. This detached high-β p plasma is compatible with a newly developed detachment control system which can help optimize the nitrogen gas flow rate. Several features, i.e., the high edge safety factor in the high-β p scenario, impurity injection, closed divertor and reduced heating power requirement due to the high confinement, facilitate the achievement of full divertor detachment at lower density. Instead of degrading global performance, the divertor detachment facilitates the access to an even stronger ITB at large radius with a relatively weak ETB through self-organized synergy between ITB and ETB, leading to sustained high confinement. The strengthening of the large-radius ITB compensates for the ETB degradation associated with divertor detachment. In addition, a weak ETB naturally has smaller edge localized modes (ELMs). In particular, with neon injection, a long-period no-ELM H-mode phase has been achieved simultaneously with high-performance core and partially detached divertor plasmas. Furthermore, these results demonstrate the possibility of integrating excellent core plasma performance with an effective divertor solution, an essential step toward steady-state operation of reactor-grade plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Chaos as the cause of randomness in tearing mode onset times in DIII-D ITER baseline scenario plasmas

The first evidence of widespread chaotic plasma dynamics relevant to the onset of disruptive tearing modes is found in DIII-D tokamak discharges. This evidence is obtained by calculating positive maximal Lyapunov exponents from Mirnov signals using the Rosenstein algorithm, implying the chaotic growth and/or rotation of magnetohydrodynamic modes in DIII-D [Luxon, Nucl. Fusion 42, 614 (2002)] plasmas. Such chaotic dynamics offer an explanation for the random tearing mode onset times previously observed in ITER baseline scenario discharges. Further, the Lyapunov timescales associated with this chaos could inhibit reliable prediction of tearing mode onset beyond the angular momentum confinement timescale; this constraint should inform the design of plasma control systems on ITER.

Chaotic dynamics↗
DOE OSTI2022

Validation of the strike point position estimation with the local expansion method for MAST upgrade on the DIII-D tokamak

A local expansion method has been proposed for estimating the strike point position for the advanced divertor configuration on the MAST Upgrade tokamak. The paper discusses the application and assesses the performance of the technique on a long-legged divertor plasma configuration on an operating device - the DIII-D tokamak. A comparison of the spatial location of the outer strike point estimated with the local expansion method against the plasma boundary reconstruction and divertor diagnostics on the DIII-D tokamak is reported. A good agreement with the equilibrium reconstruction and diagnostic data is achieved with respect to estimation of the spatial location of the outer strike point for the long-legged divertor plasma discharge.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Overview of results from the 2023 DIII-D negative triangularity campaign

Negative triangularity (NT) is a potentially transformative configuration for tokamak-based fusion energy with its high-performance core, edge localized mode (ELM)-free edge, and low-field-side divertors that could readily scale to an integrated reactor solution. Previous NT work on the TCV and DIII-D tokamaks motivated the installation of graphite-tile armor on the low-field-side lower outer wall of DIII-D. A dedicated multiple-week experimental campaign was conducted to qualify the NT scenario for future reactors. During the DIII-D NT campaign, high confinement ($H_\mathrm{98y,2}\gtrsim$ 1), high current ($q_\mathrm{95} \lt$ 3), and high normalized pressure plasmas ($\beta_\mathrm{N} \gt$ 2.5) were simultaneously attained in strongly NT-shaped discharges with average triangularity $\delta_\mathrm{avg}$ = −0.5 that were stably controlled. Experiments covered a wide range of DIII-D operational space (plasma current, toroidal field, electron density and pressure) and did not trigger an ELM in a single discharge as long as sufficiently strong NT was maintained; in contrast, to other high-performance ELM-suppression scenarios that have narrower operating windows. These strong NT plasmas had a lower outer divertor X-point shape and maintained a non-ELMing edge with an electron temperature pedestal, exceeding that of typical L-mode plasmas. Also, the following was achieved during the campaign: high normalized density ($n_\mathrm{e}$/$n_\mathrm{GW}$ of at least 1.7), particle confinement comparable to energy confinement with $Z_\mathrm{eff}\sim2$ , a detached divertor without impurity seeding, and a mantle radiation scenario using extrinsic impurities. These results are promising for a NT fusion pilot plant but further questions on confinement extrapolation and core-edge integration remain, which motivate future NT studies on DIII-D and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches

Abstract A real-time capable core Ion Cyclotron Range of Frequencies (ICRF) heating model on NSTX and WEST is developed. The model is based on two nonlinear regression algorithms, the random forest ensemble of decision trees and the multilayer perceptron neural network. The algorithms are trained on TORIC ICRF spectrum solver simulations of the expected flat-top operation scenarios in NSTX and WEST assuming Maxwellian plasmas. The surrogate models are shown to successfully capture the multi-species core ICRF power absorption predicted by the original model for the high harmonic fast wave and the ion cyclotron minority heating schemes while reducing the computational time by six orders of magnitude. Although these models can be expanded, the achieved regression scoring, computational efficiency and increased model robustness suggest these strategies can be implemented into integrated modeling frameworks for real-time control applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Deuterium and tritium anomalous transport in the generalized Hasegawa–Wakatani resistive drift wave turbulence model with finite ion Larmor radius

Anomalous transport of mixed deuterium–tritium plasma in the edge of magnetic fusion reactors is investigated using numerical solutions of resistive drift wave turbulence model equations, including finite Larmor radius effects, that are derived within the generalized Hasegawa–Wakatani framework. The anomalous cross field diffusivities of deuterium and tritium are compared in turbulence regimes with different values of the electron adiabaticity parameter controlling the existence of zonal flow. The dependence of the tritium-to-deuterium diffusivity ratio on the deuterium and tritium densities and the logarithmic density gradients is analyzed, and a scaling relation is obtained.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

EFIT-Prime: Probabilistic and physics-constrained reduced-order neural network model for equilibrium reconstruction in DIII-D

We introduce EFIT-Prime, a novel machine learning surrogate model for EFIT (Equilibrium FIT) that integrates probabilistic and physics-informed methodologies to overcome typical limitations associated with deterministic and ad hoc neural network architectures. EFIT-Prime utilizes a neural architecture search-based deep ensemble for robust uncertainty quantification, providing scalable and efficient neural architectures that comprehensively quantify both data and model uncertainties. Physically informed by the Grad–Shafranov equation, EFIT-Prime applies a constraint on the current density J tor and a smoothness constraint on the first derivative of the poloidal flux, ensuring physically plausible solutions. Furthermore, the spatial location of the diagnostics is explicitly incorporated in the inputs to account for their spatial correlation. Extensive evaluations demonstrate EFIT-Prime's accuracy and robustness across diverse scenarios, most notably showing good generalization on negative-triangularity discharges that were excluded from training. Timing studies indicate an ensemble inference time of 15 ms for predicting a new equilibrium, offering the possibility of plasma control in real-time, if the model is optimized for speed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Investigation of core impurity transport in DIII-D diverted negative triangularity plasmas

Abstract Tokamak operation at negative triangularity has been shown to offer high energy confinement without the typical disadvantages of edge pedestals (Marinoni et al 2021 Nucl. Fusion 61 116010). In this paper, we examine impurity transport in DIII-D diverted negative triangularity experiments. Analysis of charge exchange recombination spectroscopy reveals flat or hollow carbon density profiles in the core, and impurity confinement times consistently shorter than energy confinement times. Bayesian inferences of impurity transport coefficients based on laser blow-off injections and forward modeling via the Aurora package (Sciortino et al 2021 Plasma Phys. Control. Fusion 63 112001) show core cross-field diffusion to be higher in L-mode than in H-mode. Impurity profile shapes remain flat or hollow in all cases. Inferred radial profiles of diffusion and convection are compared to neoclassical, quasilinear gyrofluid, and nonlinear gyrokinetic simulations. Heat transport is observed to be better captured by reduced turbulence models with respect to particle transport. State-of-the-art gyrokinetic modeling compares favorably with measurements across multiple transport channels. Overall, these results suggest that diverted negative triangularity discharges may offer a path to a highly-radiative L-mode scenario with high core performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Time-Dependent Boundary Modeling to Inform Design of SPARC Diagnostic and Actuators

The purpose of this work was to inform the design of diagnostic and actuator systems for a new experimental facility for Commonwealth Fusion Systems (CFS), called SPARC [Creely2020], using time-dependent plasma boundary simulations with the Scrape Off Layer Plasma Simulator (SOLPS) code [Wiesen2015]. The SPARC tokamak is a device that aims to demonstrate fusion energy production and high-field plasma operating scenarios. The developed technologies will be incorporated into a net-electricity pilot that will demonstrate approximately 200MW of electric power. A major difference from other private industry fusion companies is the use of a standard aspect ratio, but at a high magnetic field strength, which provides a well-established physics basis and a modest extrapolation to reactor operation. Time-dependent simulations were used to inform the design of main-chamber plasma facing components, which are protected by feedback control of the heat and particle loads during high power operation. The simulations provide the timescales and magnitudes of plasma and neutral particle response useful for determining the position and operation of diagnostics and actuators that will enable control. The plasma response and phase-space diagrams also provide input into advanced model-based control schemes, which are envisioned for later SPARC operation. Model-based control can reduce the risk of component failure, which would require expensive in-situ repairs and the associated delays, by predicting the system response to actuators over a short time-horizon.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗