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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

First snowflake divertor experiments in MAST-U tokamak

First snowflake (SF) divertor experiments in the MAST-U tokamak demonstrated steady-state snowflake-plus divertor configurations in 450 kA ohmic L-mode plasmas. The SF divertor configuration features a second poloidal field (PF) null in the divertor region close by or overlapping with the main X-point. The resulting low PF region and two additional divertor legs (strike points) may lead to additional power and particle flux sharing via a hypothesized convective cell, and increased plasma-wetted area and radiation. The free-boundary Grad–Shafranov equilibrium code FIESTA was used to design SF configurations with several inter-null distances and orientations. In the experiment, the SF configurations with inter-null distances 0.13–0.20 m and lasting 0.2–0.3 s were obtained. Parallel connection lengths between the midplane and the outer strike point in the SF configurations (evaluated at field lines 1–2 mm from the separatrix in the midplane) were 25–30 m, higher than in the standard divertor (20–25 m) or the Super-X divertor (25 m). Diagnostic measurements highlighted salient SF features. The infra-red video bolometer diagnostic showed that the radiated power peaking in the PF null region was not as pronounces as in the standard divertor. Divertor ion fluxes measured by target Langmuir probes showed increased ion flux in the plate region where a secondary SF strike point landed, concomitantly with the SF formation. These measurements may suggest that some particle and heat redistribution was taking place in the convective SF zone. The first SF experiments provide a basis for future SF studies in MAST-U tokamak with higher input power, improved plasma control and diagnostic measurements, to be compared with the modeling predictions of plasma convective SF mixing and lower density strike point detachment threshold.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Unraveling Spatio-Temporal Chemistry Evolution in Laser Ablation Plumes and Its Relation to Initial Plasma Conditions

The chemistry evolution in a laser ablation plume depends strongly on its initial physical conditions. In this article, we investigate the impact of plasma generation conditions on the interrelated phenomena of expansion dynamics, plasma chemistry, and physical conditions. Plasmas are produced from a uranium metal target in air using nanosecond, femtosecond, and femtosecond filament-assisted laser ablation. Time-resolved two-dimensional spectral imaging was performed for evaluating the spatio-temporal evolu-tion of atoms, diatoms, polyatomic molecules, and nanoparticles in situ. Emission spectral features reveal that molecular formation occurs at early times in both femtosecond and filament ablation plumes, although with different temporal decay. In contrast, mo-lecular formation is found to occur at much later times in nanosecond plasma evolution. Spectral modeling is used to infer tem-poral behavior of plasma excitation temperature, and results highlighted that nanosecond plume temperatures decay rapidly while plumes generated by filament ablation show slowest decay. In this work, we find U atoms and UO molecules co-exist in ultrafast laser produced plasmas even at early times after plasma onset owing to favorable temperatures for molecular formation. Regardless of irradiation conditions, plume emission features showed presence of higher oxides (i.e. UxOy), although with different temporal histories. Our study provides insight into the impact of plasma generation conditions on chemistry evolution in plasmas produced from traditional focused femtosecond, nanosecond, and filament-assisted laser ablation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Machine Learning for Memory Reduction in the Implicit Monte Carlo Simulations of Thermal Radiative Transfer [Slides]

Project Goal: Use parametric Machine Learning methods in order to reduce memory requirements at checkpointing & restarting in the IMC simulations of Thermal Radiative Transfer using: Expectation Maximization and Weighted Gaussian Mixture Model-based approach for `particle-data compression', introduced in Plasma Physics to model Maxwellian particle distributions by Luis Chacon and Guangye Chen; Expectation Maximization with Weighted Hyper-Erlang Model in order to compress isotropic IMC particle data in the frequency domain; and Expectation Maximization and von Mises-Fisher Mixture Model for compression of anisotropic IMC particle data in the angular domain (work-in-progress).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Dust and Ions: Self Organization and Stability (Final Report)

This project explores the stability and structure of systems with non-reciprocal interactions, challenging the traditional understanding based on Newton's third law, which states that every action has an equal and opposite reaction. Reciprocal forces are fundamental to the stability of systems ranging in size from atomic nuclei to galactic clusters. Our research investigates what happens when the forces between two objects are not equal and opposite. We used dusty plasmas as a model system to study non-reciprocal interactions. In a plasma chamber, micron-sized dust particles acquire a negative charge and form 2D planar "dust crystals" when levitated by the electric field present in the plasma sheath at the interface between the plasma and the lower surface of the chamber. This electric field also drives a vertical ion flow, creating a positively charged "plasma wake" downstream of the dust grains. While horizontally aligned dust grains interact reciprocally, a slight vertical displacement causes non-reciprocal interactions due to the attraction of the lower dust grain to the upper dust grain’s ion wake. Our experiments investigated the range of plasma conditions (gas pressure and system power) where stable dusty plasma structures are able to self-organize, aided by the ion wake. We studied systems ranging from pairs of dust particles to large 2D crystals, providing insights into the conditions that lead to stable or unstable structures. We used numerical simulations to investigate how ion wakes changed in response to changes in the operating conditions as well as how the wakes of separate grains interact when dust grains are in close proximity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Hermes-3: Multi-component plasma simulations with BOUT++

A new open source tool for fluid simulation of multi-component plasmas is presented, based on a flexible software design that is applicable to scientific simulations in a wide range of fields. Hermes-3 is built on plasma simulation framework BOUT++, consolidating earlier SD1D and Hermes models into a single code that can be configured at run-time to solve plasma models in 1D, 2D or 3D, either for transport (steady-state) or turbulent (time-evolving) problems, with an arbitrary number of ion and neutral species. Here, we describe the improved numerical algorithms and software design that have been implemented in Hermes-3. To demonstrate the capabilities of this tool, applications relevant to the boundary of tokamak plasmas are presented: 1D simulations of diveror plasmas evolving equations for all charge states of neon and deuterium; 2D transport simulations of tokamak equilibria in single-null X-point geometry with plasma ion and neutral atom species; and simulations of the time-dependent propagation of plasma filaments (blobs). Hermes-3 is publicly available on Github under the GPL-3 open source license. The repository includes documentation and a suite of unit, integrated and convergence tests.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Control of core–shell nanoparticles properties through plasma synthesis: a computational study

The improved properties of core–shell nanoparticles (CSNPs) over homogeneous nanoparticles (NPs) have expanded and diversified the applications of these nanomaterials. However, controlling the properties of CSNPs can be a challenging task. Low temperature plasmas have proven to be an effective method of producing NPs with uniform size and morphology, and high yield. That said, NP transport and growth dynamics are sensitive to LTP properties. We report on a computational investigation of the evolution of Ge–Si CSNP properties as a function of operating conditions through the modeling of a flowing, two-zone inductively coupled plasma (ICP) reactor. Ar/GeH 4 and Ar/SiH 4 gas mixtures were supplied to separate plasma zones at a pressure of 1 Torr to promote growth of Ge cores and Si shells. The negatively charged CSNPs are trapped electrostatically in the vicinity of the antennas where the plasma is generated and where the majority of particle growth occurs. Particles that grow to a critical size are then de-trapped by fluid drag due to neutral gas flow. A two-dimensional hybrid plasma model coupled with a three-dimensional kinetic NP transport model were utilized to resolve plasma chemistry and NP growth processes that take place on distinct timescales. The trends in CSNP properties and trapping mechanisms associated with flow rate, applied ICP power and inlet precursor fraction are discussed. While the spatial distribution of plasma produced radical species can have significant impact on the NP growth process, the NP transport dynamics are what ultimately dictates the growth environment that is unique to each particle and so determines their final dimension and composition. The key to optimizing reactor conditions involves controlling the spatial density of growth species and plasma profile as a means to tailor particle trapping dynamics suitable to produce CSNPs for a specific application.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Filamentation and focusing of electron beams due to interactions with plasma waves

Results of numerical modeling of the interaction of an electron beam propagating across relativistic plasma waves indicate that electron beam filamentation and focusing may occur under certain conditions. The model is based on solving the relativistic equation of motion in three dimensions for the individual electrons in a tenuous Gaussian beam, as they pass through a relativistic plasma wave. Several electron beam and plasma wave parameters were varied, and the results are summarized. One of the results is that the spacing of the electron beam filaments correlates with the wavelength of the plasma wave. The electron beam filaments appear as vertical slabs after the beam exits the plasma waves. The electron beam also compresses to a focus after it exits the plasma, and the focal distance depends on several parameters including the electron beam energy and phase velocity of the relativistic plasma wave. It is suggested that these focusing and filamentation phenomena may be the basis for diagnostics schemes for laser plasma interactions. The parameters used in the model were electron beam energies in the 5–50 keV range and plasma wave properties typical for the beat-wave produced by CO2 lasers, which correspond to the facilities available in our laboratory. The limitations of these results to lower energy density beam and plasma regimes and to higher energy density regimes will be discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Autoregressive long-horizon prediction of plasma edge dynamics *

Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes such as SOLPS-ITER capture SOL physics with high accuracy, but their computational cost limits broad parameter scans and long transient studies. We present transformer-based, autoregressive surrogates for efficient prediction of 2D, time-dependent plasma edge state fields. Trained on SOLPS-ITER spatiotemporal data for the KSTAR tokamak, the surrogates forecast electron temperature, electron density, and radiated power over extended horizons. We evaluate model variants trained with increasing autoregressive horizons (1–100 steps) on short- and long-horizon prediction tasks. Longer-horizon training systematically improves rollout stability and mitigates error accumulation, enabling stable predictions over hundreds to thousands of steps and reproducing key dynamical features such as the motion of high-radiation regions. Measured end-to-end wall-clock times show the surrogate is orders of magnitude faster than SOLPS-ITER, enabling rapid parameter exploration. Prediction accuracy degrades when the surrogate enters physical regimes not represented in the training dataset, motivating future work on data enrichment and physics-informed constraints. Overall, this approach provides a fast, accurate surrogate for computationally intensive plasma edge simulations, supporting rapid scenario exploration, control-oriented studies, and progress toward real-time applications in fusion devices.

autoregressive deep learning↗
DOE OSTI2022

QLBT: a linear Boltzmann transport model for heavy quarks in a quark-gluon plasma of quasi-particles

Abstract We develop a new heavy quark transport model, QLBT, to simulate the dynamical propagation of heavy quarks inside the quark-gluon plasma (QGP) created in relativistic heavy-ion collisions. Our QLBT model is based on the linear Boltzmann transport (LBT) model with the ideal QGP replaced by a collection of quasi-particles to account for the non-perturbative interactions among quarks and gluons of the hot QGP. The thermal masses of quasi-particles are fitted to the equation of state from lattice QCD simulations using the Bayesian statistical analysis method. Combining QLBT with our advanced hybrid fragmentation-coalescence hadronization approach, we calculate the nuclear modification factor $$R_\mathrm {AA}$$ R AA and the elliptic flow $$v_2$$ v 2 of D mesons at the Relativistic Heavy-Ion Collider and the Large Hadron Collider. By comparing our QLBT calculation to the experimental data on the D meson $$R_\mathrm {AA}$$ R AA and $$v_2$$ v 2 , we extract the heavy quark transport parameter $$\hat{q}$$ q ^ and diffusion coefficient $$D_\mathrm {s}$$ D s in the temperature range of $$1-4~T_\mathrm {c}$$ 1 - 4 T c , and compare them with the lattice QCD results and other phenomenological studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Continued Validation Studies using the MOOSE Framework for Plasma Simulation with Electromagnetics

Resources and tools for the modeling and simulation of low-temperature plasma (LTP) discharges are increasingly vital to progress in the field in order to properly characterize and study complex source designs and plasma chemistries beyond the scope of traditional diagnostics. Open-source software provides powerful platforms for this work and can enable community-driven LTP R&D. Within the Multiphysics Object-Oriented Simulation Environment (MOOSE) open-source framework [1], capabilities have been demonstrated in the areas of plasma fluids (Zapdos [2]), plasma chemistry (CRANE [3]), and general electromagnetic wave theory (Electromagnetic Library for Kinetics & fluids [ELK] [4]). ELK has since been coupled to Zapdos/CRANE to enable fully coupled electromagnetic plasma simulations. This talk will detail the continued validation efforts and discuss Zapdos-ELK-CRANE code coupling with various-low temperature plasma sources. The impact of fully coupled electromagnetics on process parameters (e.g., temperature and electron/ion energy) versus an electrostatic description will also be discussed. [1] Permann et al., SoftwareX, 11 (2020) 100430. [2] Lindsay et al., J. Phys. D: Appl. Phys. 49 (2016) 235204. [3] Keniley et al., Talk, GEC Session DT3.00002 (2019). [4] Icenhour et al., Talk, GEC Session RR1.00006 (2019). Acknowledgements: INL Graduate Fellowship Program, NSF SI2 Grant 1740300, U.S. Dept. of Energy Office of Science Graduate Student Research Program

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Results from a synthetic model of the ITER XRCS-Core diagnostic based on high-fidelity x-ray ray tracing

A high-fidelity synthetic diagnostic has been developed for the ITER core x-ray crystal spectrometer diagnostic based on x-ray ray tracing. This synthetic diagnostic has been used to model expected performance of the diagnostic, to aid in diagnostic design, and to develop engineering tolerances. The synthetic model is based on x-ray ray tracing using the recently developed xicsrt ray tracing code and includes a fully three-dimensional representation of the diagnostic based on the computer aided design. The modeled components are: plasma geometry and emission profiles, highly oriented pyrolytic graphite pre-reflectors, spherically bent crystals, and pixelated x-ray detectors. Plasma emission profiles have been calculated for Xe 44+ , Xe 47+ , and Xe 51+ , based on an ITER operational scenario available through the Integrated Modelling & Analysis Suite database, and modeled within the ray tracing code as a volumetric x-ray source; the shape of the plasma source is determined by equilibrium geometry and an appropriate wavelength distribution to match the expected ion temperature profile. All individual components of the x-ray optical system have been modeled with high-fidelity producing a synthetic detector image that is expected to closely match what will be seen in the final as-built system. Particular care is taken to maintain preservation of photon statistics throughout the ray tracing allowing for quantitative estimates of diagnostic performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Effects of plasma squareness on RMP response in MAST-U

The effect of the squareness of the plasma boundary shape on the plasma response to the applied n = 2 (n is the toroidal mode number) resonant magnetic perturbation, and consequently on controlling the edge-localized mode (ELM) in MAST-U in the double-null configuration, is numerically systematically investigated. The modeling is performed utilizing three different plasma response models: the single-fluid model, the two-fluid model and the magnetohydrodynamic-kinetic hybrid model. The effect of the plasma squareness on ELM control is found to depend on the equilbrium kinetic profiles. Fixing the equilibrium radial profiles to that from a recent MAST-U discharge, the experimental plasma shape is found to be close to optimal for ELM control in terms of squareness. The optimal coil phasing does not significantly vary with varying plasma squareness. These findings robustly hold with (i) two figures of merit (FoMs) defined for predicting the ELM control feasibility, and (ii) three plasma response models employed for evaluating these FoMs.

MAST-U↗
DOE OSTI2026

Development of an ab initio learned model of electron deposition range in deuterium-tritium plasmas through time-dependent density functional theory calculations and machine learning

Accurate hydrodynamic modeling for laser-direct-drive (LDD) inertial-confinement-fusion (ICF) relies on precise calculations of the electron thermal conduction in all target materials. The nonlocal stopping range of electrons in ICF plasmas directly influences thermal conduction; yet, no first principles model exists for the electron mean free path in the conduction-zone regime. This work utilized time-dependent stochastic density-functional theory (TD-sDFT) to calculate the electron stopping power in deuterium-tritium (DT) plasmas at (ρ, T) conditions relevant to the conduction zone and the compressed shell in ICF. Using a combination of our TD-sDFT data and already established analytical models, we developed and trained an artificial neural network to create a global model for the nonlocal electron deposition range, λ E . We compared our machine-learning (ML) based model for λ E to the currently-used modified-Lee-More model in LDD radiation-hydrodynamic codes, such as lilac, and saw an overall decrease in the deposition range. To understand the effects of λ E on LDD ICF implosion dynamics, we implemented the ML-based model into lilac; specifically, we looked at designs consistent with a current experiment on the OMEGA laser and for a newly designed LDD-ICF target for the future OMEGA-Next facility. In both cases, we saw an overall drop in predicted ablation pressure, peak areal density, and neutron yield due to the reduced thermal conduction (smaller λ E ) in DT plasmas. Comparisons with the experiment on OMEGA are also made.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Efficient Optimization of Plasma Radiation Detector Configurations using Imperfect Inference Models

The configurations of instruments fielded on an experiment affect the amount of information captured and the quality of subsequent inference. Here, we investigate the problem of optimizing plasma x-ray radiation detectors in a magneto-inertial fusion experiment at Sandia National Laboratories. It is impossible to directly measure properties such as the temperature of the thermonuclear fusion plasma produced in these experiments because of the extreme environment and destructive nature of the experiment. Among other diagnostics, several detectors are placed with significant standoff from the fusion target to capture the x-rays emitted by the fusion plasma, which can be used to infer some of its properties. To optimize the configuration of these detectors, a high-fidelity model (HFM) is used for simulating outputs and a low-fidelity model (LFM) is used for inference. We develop methods based on A- and L-optimality criteria that are efficient to compute while explicitly accounting for the discrepancy between the HFM and the LFM. The method allows us to find detector configurations that perform similarly to or better than the configuration obtained using an existing sampling-based optimization method while decreasing computational time by a factor of 50. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Bayesian optimization↗
DOE OSTI2022

Independent-hot-spot approach to multibeam laser-plasma instabilities

The independent-hot-spot model is used to develop an analytic formulation for multibeam laser-plasma instabilities in inhomogeneous plasmas. The model is applied to the absolute two-plasmon-decay instability and shows good agreement with simulations and experiments. Furthermore, the success of the model indicates the emergence of single-speckle behavior for sufficiently large speckles sizes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A lumped particle direct simulation Monte-Carlo method combined with the collisional-radiative model for simulations of non-equilibrium laser-induced plasma plumes

Collisional plasma plumes induced by laser irradiation of material targets exhibit large variations in local density as well as ionization and excitation states, making purely hydrodynamic or kinetic simulations inaccurate or infeasible. To address this challenge and capture non-equilibrium effects in laser-induced plasma plumes at arbitrary degrees of ionization, we develop a hybrid computational approach that combines the kinetic direct simulation Monte Carlo (DSMC) method with a collisional-radiative model (CRM). This ℓDSMC-CRM approach utilizes a lumped particle method to represent minor fractions of excited ions in particle-based simulations and a special coarse-graining technique for atomic spectra and photoionization rates, ensuring numerical convergence at reduced computational cost. The hybrid approach is applied to simulate spatially homogeneous relaxation as well as one- and two-dimensional expansions of plasma plumes induced by irradiation of a copper target by a nanosecond laser pulse in a vacuum or background gas. The comparison with an equilibrium model, where local Saha-Boltzmann equilibrium is enforced, shows that the non-equilibrium effects play a dominant role. The equilibrium model can fail to predict the flow structure and strongly underestimate the degree of absorption of laser radiation by the plume. The ℓDSMC-CRM approach is validated against experimental data demonstrating reasonable agreement with the experimental electron density and temperature, while the equilibrium model is found to dramatically underestimate electron density and temperature. The flexibility of the ℓDSMC-CRM approach allows for its seamless integration into existing DSMC frameworks, making it a valuable tool for high-fidelity plasma modeling in laser-material interactions, laser-based manufacturing, and beyond.

97 MATHEMATICS AND COMPUTING↗