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At least 199 records · Page 11

Capturing Secondary Kinetic Instabilities in Three‐Dimensional Dayside Reconnection Using an Improved Gradient‐Based Closure

Magnetic reconnection is a highly dynamic process that excites a wide variety of kinetic waves and instabilities. Transverse current sheet instabilities such as the lower-hybrid drift and secondary drift-kink instabilities in particular have been shown by kinetic simulations to modify the reconnection and introduce significant turbulence and mixing to the reconnection layer. Past studies using the ten-moment fluid model to capture important kinetic physics such as the electron inertia and full representation of the pressure tensor proved advantageous to a two-fluid representation of reconnection, but the model struggled when using a local relaxation closure for the heat flux to replicate the current sheet instabilities and subsequent mixing seen in kinetic simulations. This work uses the Gkeyll software framework to perform simulations of asymmetric reconnection based on the 16 October 2015 MMS crossing of a diffusion region, the Burch event. An improved gradient-based heat flux closure is implemented, showing significant improvement in secondary kinetic instabilities that grow in the current sheet. These instabilities generate turbulence which leads to growth of secondary magnetic islands and flux ropes.

Bradshaw, K. [Princeton University, NJ (United Sta↗

Multimodal super-resolution: discovering hidden physics and its application to fusion plasmas

Understanding complex physical systems often requires integrating data from multiple diagnostics, each with limited resolution or coverage. We present a machine learning framework that reconstructs synthetic high-temporal-resolution data for a target diagnostic using information from other diagnostics, without direct target measurements during the inference. This multimodal super-resolution technique improves diagnostic robustness and enables monitoring even in case of measurement failures or degradation. Applied to fusion plasmas, our method targets edge-localized modes (ELMs), which can damage plasma-facing materials. By reconstructing super-resolution Thomson Scattering data from complementary diagnostics, we uncover fine-scale plasma dynamics and validate the role of resonant magnetic perturbations (RMPs) in ELM suppression through magnetic island formation. The approach provides new observation supporting the plasma profile flattening due to these islands. Our results demonstrate the framework’s ability to generate high-fidelity synthetic diagnostics, offering a powerful tool for ELM control development in future reactors like ITER. The approach is broadly transferable to other domains facing sparse, incomplete, or degraded diagnostic data, opening new avenues for discovery.

Jalalvand, Azarakhsh [Princeton Univ., NJ (United ↗

Full-wave modeling of RF waves in fusion plasmas with finite element method: Progress in past decades and its future role

This paper reviews the progress in computing radio frequency (RF) wave fields in fusion plasmas, specifically focusing on simulations utilizing the finite element method (FEM) over the past few decades. Computing RF wave fields in fusion plasmas presents unique challenges due to large simulation domains, complex antenna structures, non-local dielectric properties, and wide ranges of spatial scales. It highlights key developments and outlines future directions, primarily addressing waves in the ion cyclotron (IC) to lower hybrid (LH) frequency range. We begin with briefly revisiting earlier developments before the widespread availability of modern computer-aided engineering (CAE) software based on FEM. This historical perspective illuminates early progress and the physics difficulties that motivated ongoing work within the community. Modern wave simulations for RF antennas based on FEM are characterized by the use of detailed 3D antenna model geometry generated from engineering CAD software and localized wave dielectric model. Significant advancements have also been made in improving physics models to include phenomena such as RF sheath rectification and wave scattering. FEM-based RF simulations have also been applied to compute wave propagation in the core region, where the inclusion of non-local dielectric response is crucial. This is a challenging goal, and several promising approaches have been proposed in this area. Additionally, RF simulation development initiatives based on open-source libraries have gained popularity, demonstrating scalability and flexibility in extending physics models. This paper will discuss the advantages and disadvantages of using such a publicly available FEM library.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Automated ICRF heating surrogate modeling via machine learning

This work introduces automated machine learning workflows that address critical bottlenecks in surrogate model development for Ion Cyclotron Range of Frequencies (ICRF) heating applications. The automated framework includes data analysis tools that transform raw datasets into actionable insights in seconds, replacing weeks of manual exploratory effort and ensuring consistent, reproducible dataset characterization. By integrating advanced hyperparameter optimization (HPO) methods including Bayesian optimization via BoTorch and Tree-structured Parzen Estimators (TPE), the framework significantly reduces model development time from weeks to hours, decreasing computational cost and required expertise, while enabling high-accuracy surrogate models. Compared to traditional hyperparameter scanning (HPS) techniques such as methodical, randomized, and grid searches, HPO methods achieve superior convergence and predictive performance, even when compared to already well-tuned reference models. On NSTX High Harmonic Fast Wave (HHFW) heating datasets, both Random Forest Regressor (RFR) and neural network surrogates demonstrate improved accuracy, achieving R 2 values beyond 0.97 and 0.98, respectively. The results show that while HPO gains are modest for robust architectures like RFR, they become essential for more sensitive models such as neural networks, highlighting the trade-offs across optimization strategies. Through automated workflows that eliminate manual hyperparameter tuning and require minimal ML expertise, this work enables widespread adoption of high-fidelity surrogate models across the fusion community for real-time plasma control, uncertainty quantification, rapid experimental scenario development, and integrated system optimization.

Sanchez-Villar, Alvaro [Princeton Plasma Physics L↗

Performance characterization of x-ray crystal spectroscopy highly oriented pyrolytic graphite reflectors based on x-ray diffractometry experiments

The use of Highly Oriented Pyrolytic Graphite (HOPG) reflectors is often proposed in the design of X-ray Crystal Spectroscopy (XCS) diagnostic systems for the next-generation tokamak devices, including the ITER project. Here, this study introduces an experimental study based on the X-Ray Diffractometry (XRD) method to evaluate the performance of HOPG reflectors. The experimental method provides both the angular responses and the reflectivities of the HOPG reflectors. A demonstrative XRD experiment is conducted, and the details of the experiment are introduced. This method enables precise studies on HOPG reflectors, facilitating the design of XCS diagnostic systems for future tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

FreeMHD: Validation and verification of the open-source, multi-domain, multi-phase solver for electrically conductive flows

The extreme heat fluxes in the divertor region of tokamaks may require an alternative to solid plasma-facing components, for the extraction of heat and the protection of the surrounding walls. Flowing liquid metals are proposed as an alternative, but raise additional challenges that require investigation and numerical simulations. Free surface designs are desirable for plasma-facing components, but steady flow profiles and surface stability must be ensured to limit undesirable interactions with the plasma. Previous studies have mainly used steady-state, 2D, or simplified models for internal flows and have not been able to adequately model free-surface liquid metal (LM) experiments. Therefore, FreeMHD has been recently developed as an open-source magnetohydrodynamics (MHD) solver for free-surface electrically conductive flows subject to a strong external magnetic field. The FreeMHD solver computes incompressible free-surface flows with multi-region coupling for the investigation of MHD phenomena involving fluid and solid domains. The model utilizes the finite-volume OpenFOAM framework under the low magnetic Reynolds number approximation. FreeMHD is validated using analytical solutions for the velocity profiles of closed channel flows with various Hartmann numbers and wall conductance ratios. Next, experimental measurements are then used to verify FreeMHD, through a series of cases involving dam breaking, 3D magnetic fields, and free-surface LM flows. These results demonstrate that FreeMHD is a reliable tool for the design of LM systems under free surface conditions at the reactor scale. Furthermore, it is flexible, computationally inexpensive, and can be used to solve fully 3D transient MHD flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Mode transitions and spoke structures in E × B Penning discharge

Two-dimensional particle-in-cell simulations in the (radial-azimuthal) plane perpendicular to the axial direction of a cylindrical $E$ x $B$ Penning discharge are presented. The low-pressure discharge is self-consistently supported by plasma ionization from the electron beam injected axially, along the direction of the external magnetic field. It is shown that with the increasing strength of the external magnetic field, the discharge undergoes a sequence of transitions between several azimuthal modes. Azimuthal m > 1 spiral arm structures are excited at low magnetic field values as plasma confinement improves and the radial density profile becomes peaked. With a larger field, spiral arms with m > 1 are replaced by the m = 1 spoke mode, most clearly seen in plasma density. A transition from spiral arms to the spoke regime occurs when the plasma potential in the center changes from weakly positive (or zero) to negative. Further increase in the magnetic field results in a well-developed m = 1 spoke mode with additional small-scale higher-frequency m > 1 structures inside and around the spoke. It is shown that while ionization and collisions affect some characteristics of the observed fluctuations, the basic features of the spoke and m > 1 spiral structure remained similar without ionization. The role of energy conservation in small-scale high-frequency modes and spoke dynamics is discussed. It is demonstrated that in regimes with the m = 1 spoke mode, additional m = 4 harmonics of the ion and electron fluxes to the wall appear due to the square boundary. The frequency of the m = 1 mode is weakly affected by the geometry of the boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Machine learning enhanced predictions of ICRF heating: Overcoming numerical limitations via data curation

In this work, we present the development of robust surrogate models for Ion Cyclotron Range of Frequencies (ICRF) and High-Harmonic Fast Wave (HHFW) heating predictions in fusion plasmas. Building upon our previous efforts to achieve real-time capable models, we identify the cause of the outliers found using TORIC in certain HHFW heating scenarios. The outliers are observed to be spurious ion Bernstein wave (IBW)-like modes caused by a wavelength control algorithm designed to address challenging scenarios with high perpendicular wavenumbers. The effect arises from the modulation in the perpendicular susceptibility, which can induce sign reversal and IBW-like propagation for scenarios featuring normalized ion Larmor radius λ i ≫ 1. We use TORIC with this algorithm disabled to generate a novel HHFW-NSTX database that is free of outliers. Surrogate models trained on this database, including Random Forest Regressor (RFR), Multi-Layer Perceptrons, and Gaussian Process Regressors (GPR), demonstrate the ability to accurately predict HHFW heating profiles, with regression scores of R 2 ∈[0.93−0.99]. Additionally we demonstrate that it is possible to generalize predictions beyond training data by the use of both RFR and GPR models, enabling the prediction of scenarios previously limited to the original model. GPR models also provide uncertainty quantification, offering insights into model confidence. This work introduces a comprehensive Verification, Validation, and Uncertainty Quantification methodology for surrogate modeling, applicable not only to ICRF heating but also to other RF heating challenges and fusion physics problems. Beyond accelerated inference, these models show effective extrapolation capabilities, providing an alternative for addressing numerical challenges.

Artificial neural networks↗

Periodic Korteweg–de Vries soliton potentials generate quasisymmetric magnetic field strength in a finite plasma- β equilibrium

Quasisymmetry (QS) is a hidden symmetry of the magnetic field strength, B , that enables effective confinement of charged particles in a fully three-dimensional (3D) toroidal plasma equilibrium. Such equilibria are typically modeled by the ideal magnetohydrostatic (MHS) equations. The nonlinear, overdetermined nature of the QS MHS equations severely complicates our understanding of the interplay between 3D shaping, equilibrium properties such as pressure and rotational transform, and B . Progress has been made through expansions near the magnetic axis; however, a more comprehensive theory is desirable. Using a combination of analysis and regression on a large dataset of numerically optimized quasisymmetric stellarators, we demonstrate that there is a hidden lower dimensionality of B on a magnetic flux surface with connections to the theory of periodic solitons. We show that B on a flux surface is determined by three or at most four flux functions, each of which determines a critical value of the derivative of B along the field line. While being consistent with the near-axis models, our results are global and hold even on the last closed flux surface.

Differential geometry↗

Accelerating kinetic plasma simulations with machine-learning-generated initial conditions

Computational models of plasma technologies often solve for the system operating conditions by time-stepping an initial value problem to a quasi-steady solution. However, the strongly nonlinear and multi-timescale nature of plasma dynamics often necessitate millions, or even hundreds of millions, of steps to reach convergence, reducing the effectiveness of these simulations for computer-aided engineering. We consider acceleration of kinetic plasma simulations via data-driven machine-learning-generated initial conditions, which initialize the simulations close to their final quasi-steady-state, thereby reducing the number of steps to reach convergence. Three machine-learning models are developed to predict the density and ion kinetic profiles of capacitively coupled plasma discharges relevant to the microelectronics industry. The models are trained on kinetic simulations over a range of device operating frequencies and pressures. Best performance was observed when simulations were initialized with ion kinetic profiles generated by a convolutional neural network, reducing the mean number of steps to reach convergence by 17.1× when compared to initialization with a zero-dimensional global model. We also outline a workflow for continuous data-driven model improvement and simulation speedup, with the aim of generating sufficient data for full device digital twins.

Artificial neural networks↗

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↗

Measurements of the electron energy distribution function in partially magnetized low temperature plasmas

While Langmuir probes (LPs) are relatively simple and inexpensive plasma diagnostics for the electron density, temperature, and the electron energy distribution function (EEDF), the interpretation of the measured current–voltage (I–V) characteristic is complicated considerably by the presence of a magnetic field. In regimes where the electron gyroradius is comparable to the probe radius, the electron flux to the probe surface is retarded by reduced mobility across field lines and can no longer be described by a thermal model. Predicting the current collected by the probe in these regimes requires accurate estimates of the plasma diffusion coefficients, which are usually difficult to obtain. In this work, we measure electron energy distribution functions in E×B plasmas with magnetized electrons and non-magnetized ions in argon and krypton gases, using both a LP and laser Thomson scattering (LTS) at various magnetic fields. Using the LTS measurements to provide a robust benchmark for comparison, we compare existing theories describing the flux to the probe under magnetized conditions. We find that even when the electron gyroradius associated with the effective electron temperature is small compared to the probe radius, the EEDF computed using classical probe theory is still robust at energies higher than the energy at which the gyroradius becomes larger than the probe size. For plasmas that are not strongly non-Maxwellian, we formulate a method to extract robust density and temperature measurements using physics-informed fitting techniques to analyze EEDFs computed using classical theory.

Devin, E. G. [Princeton Plasma Physics Laboratory ↗

Implications of a two-fluid heat diffusion model for RF condensation effects in magnetic islands

Theoretical calculations have predicted an “RF condensation” effect through which the temperature perturbation and current drive may be nonlinearly enhanced in electron cyclotron (EC) heated magnetic islands. Previously, two-fluid effects had been neglected in the OCCAMI code used to model RF condensation. For realistic experimental conditions, we show that two-fluid effects in an EC heated plasma may have a major impact on RF condensation. Less collisional plasmas, where electron and ion temperatures are decoupled, exhibit an enhanced linear temperature perturbation in the island, and an even stronger nonlinear enhancement of the perturbed temperature. This can occur even when nonlinear effects are small in the single-fluid limit. We also calculate corresponding hysteresis effects. Finally, we demonstrate that other physical effects, including the rotation of the magnetic island and the Gaussian spread of the beam from a gyrotron, can significantly decrease the predicted observable RF condensation effect.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Advancing Fusion Research and Development at TAE Technologies Through INFUSE Program

The U.S. Department of Energy’s Innovation Network for Fusion Energy (INFUSE) program serves as a crucial catalyst by fostering public-private partnership that accelerates technological innovation for fusion energy research and development (R&D) in the private sector. Further, this article provides a comprehensive overview of the technical goals and accomplishments of projects awarded to TAE Technologies through the INFUSE program since 2019. We offer high-level perspectives on how these projects have contributed to fusion energy R&D, and we address key challenges encountered during these collaborations.

field-reversed configuration↗

Simulation of metal nanoparticles growth in methane atmosphere of arc discharge: comparison to experiment

A direct current arc discharge in a methane atmosphere is a scalable and sustainable method to produce metal-carbon core–shell nanoparticles and single-walled carbon nanotubes, where a metal catalyst can be continuously supplied through evaporation of an anode made from the catalyst material. The size of catalyst particles is of critical importance as it can affect the synthesis yield and properties of nanotubes and core–shell nanoparticles. This study presents a numerical model describing the formation and growth of metal particles for the conditions representative of the arc discharge with an evaporating iron anode at near-atmospheric pressure of a methane-rich atmosphere. The model incorporates carbon adsorption to the metal surface and explains the limiting effect of carbon coverage on the size of metal nanoparticles. The predicted particle sizes are compared with experimental observations. The model also predicts higher concentrations of metal particles with the increasing partial pressure of methane.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

In situ studies of a molten metal anode ablation in a nearly atmospheric pressure DC arc

A DC arc with a meltable metal anode in a near-atmospheric pressure hydrocarbon gas is an emerging method for producing single-walled carbon nanotubes (SWCNTs). In these systems, evaporation of the molten metal anode determines the formation of catalyst seed particles needed for SWCNT growth, and therefore, should be monitored, controlled, and optimized. Evaluating the anode ablation rate by weighing the anode before and after a synthesis run is unfeasible due to anode carburization in the hydrocarbon atmosphere. To overcome this, we implemented a high-speed, 2D, 2-color pyrometry for reliable temperature measurements of the molten anode in a DC arc. The obtained temperature fields were used to calculate the anode ablation rates. Results showed the importance of resolving the arc and molten pool dynamics, as well as addressing the issue of reflections. Furthermore, significant changes in ablation rates were revealed upon addition of CH 4 , which must be considered when scaling up the production of SWCNTs.

Marangoni↗

Studies of laser stimulated photodetachment from nanoparticles for particle charge measurements

Determining nanoparticle charge is more challenging than that for microparticles due to change in the particle size during the synthesis substantial plasma property variations, and difficulties in visualizing individual particles, rendering conventional microparticle charge diagnostics ineffective in dusty plasma. In this work, we utilized laser-stimulated photodetachment (LSPD) to deduce the mean charge of nanoparticles. Nanoparticles were grown in an Ar/C 2 H 2 mixture using a capacitively coupled RF discharge and the LSPD induced changes in the electron current monitored by a cylindrical Langmuir probe. LSPD signals were obtained and analyzed across different dust growth phases. The prolonged decay of electron current pulses was attributed to the presence of residual negative ions, caused by the effective electrostatic trapping of these ions and the potential post—LSPD re-formation of new ones. The particle charge was estimated by combining the laser-stimulated photodetachment signal from the probe with the dust density obtained from laser-light extinction using the measured nanoparticle size distribution. For a nanoparticles size range of approximately 100–250 nm and mean diameter of $d$ p ∼154.37 nm, the effective mean charge was estimated to be $\langle$$Q$$\rangle$ d $≈$ 37 elementary charge units. The measured charge values are lower than those predicted by orbital motion limited theory, which may be attributed to significant electron depletion in the nanodusty plasma. LSPD results in Ar/C 2 H 2 nano-dusty plasma confirm the applicability of this method for estimating individual nanoparticle charges. However, it has also been demonstrated that electron detachment from residual background negative ions can influence the detachment current decay and must be carefully considered.

dust particle charge↗

Tungsten control in long pulse operation: feedback from WEST to ITER

The full W environment that is now foreseen for ITER puts strong emphasis on experimental results obtained in present devices in similar conditions. In this context, the WEST tokamak is well equipped to bring key contributions to the preparation of ITER operation, thanks to its capability to perform long pulses in dominant electron heating, torque-free scheme based on RF systems, and its ITER-grade actively cooled divertor. Recent results of interest cover the understanding of tungsten contamination and the evaluation of conditioning methods, the feedback on the current ramp-up phase, and the ageing of the ITER divertor components in L-mode attached condition. Further, new directions are being explored, in particular low divertor temperature operation that should be the normal operating regime of ITER. We also report on tungsten peaking physics, and the role of light impurity content.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗