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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Laboratory Study of Collisionless Magnetic Reconnection

A concise review is given on the past two decades’ results from laboratory experiments on collisionless magnetic reconnection in direct relation with space measurements, especially by the Magnetospheric Multiscale (MMS) mission. Highlights include spatial structures of electromagnetic fields in ion and electron diffusion regions as a function of upstream symmetry and guide field strength, energy conversion and partitioning from magnetic field to ions and electrons including particle acceleration, electrostatic and electromagnetic kinetic plasma waves with various wavelengths, and plasmoid-mediated multiscale reconnection. Combined with the progress in theoretical, numerical, and observational studies, the physics foundation of fast reconnection in collisionless plasmas has been largely established, at least within the parameter ranges and spatial scales that were studied. Immediate and long-term future opportunities based on multiscale experiments and space missions supported by exascale computation are discussed, including dissipation by kinetic plasma waves, particle heating and acceleration, and multiscale physics across fluid and kinetic scales.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Modeling and verification of dynamic field ionization for laser-target interactions

Integrating field ionization models into kinetic plasma simulations is required for a variety of applications, especially when field strengths vary from low to high regimes, such as in laser-target interactions. The introduction of new physics models into kinetic codes requires a rigorous verification of their accuracy through well-defined verification problems. In this work, the field ionization model that has been included in the kinetic plasma code VPIC is presented, along with the detailed approach adopted for its integration. This model includes a comprehensive range of field ionization mechanisms: multiphoton ionization, tunneling ionization, and barrier suppression ionization. New verification problems employed to evaluate the ionization model's fidelity are outlined, and the simulation parameters that affect the accuracy of simulation results are explored. Additionally, this work addresses the impact of field ionization on computational performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Second-Phase Hepatitis C Plasma Viral Kinetics Directly Reflects Reduced Intrahepatic Burden of Hepatitis C Virus

Mathematical models explain how antivirals control viral infections. Hepatitis C virus (HCV) treatment results in at least 2 phases of decline in viremia. Here, the first phase reflects clearance of rapidly produced virions. The second phase is hypothesized to derive from loss of infected cells but has been challenging to prove. Using single-cell methods, we quantified the number of hepatitis C virus (HCV)-infected hepatocytes in liver biopsies taken before and within 7 days of initiating direct-acting antivirals (DAAs) in a double-blinded randomized controlled trial testing 2 (sofosbuvir-velpatasvir) versus 3 (sofosbuvir-velpatasvir-voxilaprevir) DAAs. We employed thousands of intrahepatic measurements in 10 persons with chronic genotype 1a HCV infection: median proportion of infected hepatocytes declined from 11.3% (range, 1.3%–59%) to 0.6% (range, <0.3%–5.8%), a loss of 75%–95% infected hepatocytes. Plasma viremia correlated with numbers of HCV-infected hepatocytes (r = 0.77; P < .0001). Second-phase plasma dynamics and changes in infected hepatocytes were indistinct (P = .16), demonstrating that second-phase viral dynamics derive from loss of infected cells. DAAs led to a decline in intracellular HCV RNA and interferon-stimulated gene expression (P < .05 for both). We proved that second-phase viral dynamics reflect decay of intrahepatic burden of HCV, partly due to clearance of HCV RNA from hepatocytes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Novel use of Direct Simulation Monte-Carlo to Model Dynamics of COVID-19 Pandemic Spread

In this report, we evaluate a novel method for modeling the spread of COVID-19 pandemic. In this new approach we leverage methods and algorithms developed for fully-kinetic plasma physics simulations using Particle-In-Cell (PIC) Direct Simulation Monte-Carlo (DSMC) models. This approach then leverages Sandia-unique simulation capabilities, and High-Performance Computer (HPC) resources and expertise in particle-particle interactions using stochastic processes. Our hypothesis is that this approach would provide a more efficient platform with assumptions based on physical data that would then enable the user to assess the impact of mitigation strategies and forecast different phases of infection. This work addresses key scientific questions related to the assumptions this new approach must make to model the interactions of people using algorithms typically used for modeling particle interactions in physics codes (kinetic plasma, gas dynamics). The model developed uses rational/physical inputs while also providing critical insight; the results could serve as inputs to, or alternatives for, existing models. The model work presented was developed over a four-week time frame, thus far showing promising results and many ways in which this model/approach could be improved. This work is aimed at providing a proof-of-concept for this new pandemic modeling approach, which could have an immediate impact on the COVID-19 pandemic modeling, while laying a basis to model future pandemic scenarios in a manner that is timely and efficient. Additionally, this new approach provides new visualization tools to help epidemiologists comprehend and articulate the spread of this and other pandemics as well as a more general tool to determine key parameters needed in order to better predict pandemic modeling in the future. In the report we describe our model for pandemic modeling, apply this model to COVID-19 data for New York City (NYC), assess model sensitivities to different inputs and parameters and , finally, propagate the model forward under different conditions to assess the effects of mitigation and associated timing. Finally, our approach will help understand the role of asymptomatic cases, and could be extended to elucidate the role of recovered individuals in the second round of the infection, which is currently being ignored.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Sensitivities of time-dependent temperature profile predictions for NSTX with the multi-mode model

The Multi-Mode Model (MMM) for turbulent transport was applied to a large set of well-analyzed discharges from the National Spherical Torus Experiment (NSTX) in order to evaluate its sensitivities to a wide range of plasma conditions. MMM calculations were performed for hundreds of milliseconds in each discharge by performing time-dependent predictive simulations with the 1.5D tokamak integrated modeling code TRANSP. A closely related study (Lestz et al 2025 Plasma Phys. Control. Fusion 67 105029) concluded that MMM predicted electron and ion temperature profiles that were in reasonable agreement with NSTX observations, generally outperforming a different reduced transport model, TGLF. This finding motivates the more thorough investigation of the characteristics of the MMM predictions conducted in this work. The simulations with MMM have electron energy transport dominated by electron temperature gradient modes in the examined discharges with relatively low plasma β (ratio of kinetic plasma pressure to magnetic field pressure) and high collisionality, transitioning to a mixture of different modes for higher β and lower collisionality. The thermal ion diffusivity predicted by MMM is much smaller than the neoclassical contribution, in line with previous experimental analysis of NSTX. Nonetheless, the electron and ion temperature profiles are coupled via collisional energy exchange and thus sensitive to which transport channels are predicted. The time-dependent simulations with MMM are robust to the simulation start time, converging to remarkably similar temperature profiles later during the discharge. MMM typically overpredicts confinement relative to NSTX observations, leading to the prediction of overly steep temperature profiles. Plasmas with spatially broader temperature profiles, higher plasma β, and longer energy confinement times tend to be predicted by MMM with better agreement with the experiment. As a result, these findings provide useful context for understanding the regime-dependent tendencies of MMM in anticipation of self-consistent, time-dependent predictive simulations of NSTX-U discharges with these same modeling tools.

MMM↗
DOE OSTI2021

ZrN Phase Formation, Hardening and Nitrogen Diffusion Kinetics in Plasma Nitrided Zircaloy-4

Plasma nitridation was conducted to modify the surfaces of Zircaloy-4. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), and Raman analysis were used to characterize microstructures and phases. Surface indentation and cross-sectional indentation were performed to evaluate mechanical property changes. Nitridation forms a thin layer of ZrN phase, followed by a much deeper layer affected by nitrogen diffusion. The ZrN phase is confirmed by both TEM and Raman characterization. The Raman peaks of ZrN phase show a temperature dependence. The intensity increases with increasing nitridation temperatures, reaches a maximum at 700 °C, and then decreases at higher temperatures. The ZrN layer appears as continuous small columnar grains. The surface polycrystalline ZrN phase is harder than the bulk by a factor of ~8, and the nitrogen diffusion layer is harder by a factor of ~2–5. The activation energy of nitrogen diffusion was measured to be 2.88 eV. The thickness of the nitrogen-hardened layer is controllable by changing the nitridation temperature and duration.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A deterministic verification strategy for electrostatic particle-in-cell algorithms in arbitrary spatial dimensions using the method of manufactured solutions

As simulations of kinetic plasmas continue to increase in scope and complexity, a rigorous and straightforward method for verifying particle-in-cell (PIC) implementations is necessary to ensure their correctness. Here, in this paper, we present a deterministic method for the rigorous verification of multidimensional, multispecies, electrostatic particle-in-cell codes based on the method of manufactured solutions. Specifically, we prove that rigorous verification is possible through the exclusive examination of errors of grid quantities (i.e., moments and/or fields), allowing for a very light-weight and non-intrusive implementation in existing PIC codes. This is a marked improvement over earlier PIC verification approaches (only demonstrated with one species in 1D-1V), which rely on the comparison of cumulative distribution functions, and are invasive on the code base, introduce additional stochastic noise, are significantly more computationally expensive, and lack rigorous convergence properties. Interestingly, we show that different grid quantities feature different rates of convergence with the number of particles and mesh size, impacting the verification process. These theoretical results are confirmed numerically with a multi-species 2D-2V particle-in-cell code, including the ability of the method to detect order reduction due to an incorrect implementation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Multi-Scale Modeling for Plasma-Enhanced Ammonia Decomposition over Carbides and Nitrides

Ammonia is a carbon-free hydrogen carrier, but its decomposition typically requires high temperatures over costly Ru-based catalysts due to the large barrier for N≡N bond formation. We develop a multiscale framework combining density functional theory, zero-dimensional plasma kinetics, and microkinetic modeling to elucidate how non-thermal plasma (NTP) enables low-temperature NH 3 decomposition over Co-based carbides and nitrides, benchmarked against Ru and Co. Under thermal conditions, all catalysts are limited by N≡N bond formation, with Co 3 C(001) most active owing to its negatively charged surface, strong N* binding, and low activation barriers of N≡N bond formation. Plasma-induced vibrational excitation of NH 3 and its reactive radicals promotes a radical-driven •NH 2 –N* coupling pathway that dominates on Co 3 C(001) and Co 3 N(001), shifting the rate-limiting step to NH 3 (v1) dissociation, increasing turnover frequencies by up to 6 orders of magnitude, and reducing the temperature needed to reach a turnover frequency of 5 s –1 from >680 °C (Ru and Co under thermal condition) to 267 °C (Co 3 C) and 415 °C (Co 3 N). These results identify Co-based carbides and nitrides as promising plasma-active catalysts for energy-efficient hydrogen production from ammonia.

ammonia decomposition↗
DOE OSTI2023

Plasma-based global pathway analysis to understand the chemical kinetics of plasma-assisted combustion and fuel reforming

The Global Pathway Analysis (GPA) algorithm helps analyze the chemical kinetics of complex combustion systems by identifying important global reaction pathways connecting a source species to a sink species through various important intermediate species (i.e., hub species). Here, the present work aims to extend GPA algorithm to plasma-assisted combustion and fuel reforming systems to identify the dominant global pathways in such systems at various conditions. In addition, the present study extends the ability of GPA algorithm to identify reaction cycles involving the excitation of high-concentration species (e.g., O 2 , N 2 , and fuel) to their vibrational and electronic states and the subsequent de excitation to their ground state, based on their significance on the reactivity of plasma-assisted systems in terms of gas heating and radical production. Provisions are made in the GPA algorithm to evaluate the reactivity of identified re action pathways and cycles based on the element-flux transfer (i.e., dominance), heat release, and radical production rate. The newly developed Plasma-based Global Pathway Analysis (PGPA) algorithm is then used to analyze the plasma assisted combustion of ammonia and reforming of methane. The PGPA analyses elucidated the significance of vibrational-translational cycles on the reactivity of NH 3 /air mixtures. Further, analyses on the production of NO ascribed the early reforming of NH 3 to N 2 and H 2 in impeding the production of NO during plasma-assisted NH 3 ignition. Lastly, the enhanced reforming of CH 4 /N 2 mixtures using plasma has been attributed to electron impact dissociation of CH 4 when compared to thermal reforming. In contrast, conventional path-Flux analysis (PFA) was found to require significant manual effort and pre-analysis intuitions from expert knowledge, making it arduous to provide valuable in sights into plasma chemistry. The user-friendly and automated nature of PGPA thus provides a valuable tool for assessing the kinetics of plasma-assisted systems helpful in analyzing and, further, a foundation in reducing plasma-assisted chemistry, without the needs of expert knowledge.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

A Study on Particle Trajectory Error in Finite-Element Particle-in-Cell Algorithms

Particle-in-cell (PIC) algorithms are widely used for the simulation of kinetic plasmas. PIC algorithms account for the interaction between charged particles in a plasma and the electromagnetic field in ambient space, including self-field interactions. The objective of this article is to study the error in charged particle trajectories present in finite-element (FE)-based PIC algorithms on unstructured meshes. We study how the trajectory error behaves according to the FE mesh resolution and the matrix solver employed in the FE algorithm. The study is performed by considering a trajectory established by a parabolic electric potential and an axial magnetic force acting on the charged particle. Under a proper choice combination of electric and magnetic field parameters, the 2-D particle trajectories comprise closed orbits. Numerical errors cause small perturbations on the trajectories, with cumulative effects. As a result, the resulting orbital trajectories exhibit distortions including spurious apsidal precession. These distortions provide a clear imprint of the numerical error. Here, we also study the numerical error in a quantitative fashion by computing the distance norm between the trajectories obtained by the exact fields and numerical fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

An unstructured body-of-revolution electromagnetic particle-in-cell algorithm with radial perfectly matched layers and dual polarizations

A novel electromagnetic particle-in-cell algorithm has been developed for fully kinetic plasma simulations on unstructured (irregular) meshes in complex body-of-revolution geometries. The algorithm, implemented in the BORPIC++ code, utilizes a set of field scalings and a coordinate mapping, reducing the Maxwell field problem in a cylindrical system to a Cartesian finite element Maxwell solver in the meridian plane. The latter obviates the cylindrical coordinate singularity in the symmetry axis. The choice of an unstructured finite element discretization enhances the geometrical flexibility of the BORPIC++ solver compared to the more traditional finite difference solvers. Symmetries in Maxwell’s equations are explored to decompose the problem into two dual polarization states with isomorphic representations that enable code reuse. The particle-in-cell scatter and gather steps preserve charge conservation at the discrete level. Our previous algorithm (BORPIC+) discretized the E and B field components of TE Φ and TM Φ polarizations on the finite element (primal) mesh. Here, we employ a new field-update scheme. Using the same finite element (primal) mesh, this scheme advances two sets of field components independently: (1) E and B of TE Φ polarized fields, (E z , E ρ , B Φ ) and (2) D and H of TM Φ polarized fields, (D Φ , H z , H ρ ). Since these field updates are not explicitly coupled, the new field solver obviates the coordinate singularity, which otherwise arises at the cylindrical symmetric axis, ρ = 0 when defining the discrete Hodge matrices (generalized finite element mass matrices). Here, a cylindrical perfectly matched layer is implemented as a boundary condition in the radial direction to simulate open space problems, with periodic boundary conditions in the axial direction. We investigate effects of charged particles moving next to the cylindrical perfectly matched layer. We model azimuthal currents arising from rotational motion of charged rings, which produce TMΦ polarized fields. Several numerical examples are provided to illustrate the first application of the algorithm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Temporally-consistent koopman autoencoders for forecasting dynamical systems

Absence of sufficiently high-quality data often poses a key challenge in data-driven modeling of high-dimensional spatio-temporal dynamical systems. Koopman Autoencoders (KAEs) harness the expressivity of deep neural networks (DNNs), the dimension reduction capabilities of autoencoders, and the spectral properties of the Koopman operator to learn a reduced-order feature space with simpler, linear dynamics. However, the effectiveness of KAEs is hindered by limited and noisy training datasets, leading to poor generalizability. To address this, we introduce the Temporally-Consistent Koopman Autoencoder (tcKAE), designed to generate accurate long-term predictions even with limited and noisy training data. This is achieved through a consistency regularization term that enforces prediction coherence across different time steps, thus enhancing the robustness and generalizability of tcKAE over existing models. We provide analytical justification for this approach based on Koopman spectral theory and empirically demonstrate tcKAE’s superior performance over state-of-the-art KAE models across a variety of test cases, including simple pendulum oscillations, kinetic plasma, and fluid flow data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Electron-scale temperature gradients in kinetic equilibrium: MMS observations and Vlasov–Maxwell solutions

For an ideal gas, the notion of thermodynamic equilibrium requires that the system’s temperature be spatially uniform. We demonstrate that for a collisionless plasma, kinetic equilibrium can be achieved even in the presence of a temperature gradient. Motivated by recent MMS magnetopause observations of thin current layers exhibiting electron-scale temperature gradients, here we present an exact solution to the Vlasov-Maxwell system which accounts for the observed electron temperature gradient and reproduces much of the plasma’s spatial variation along one dimension. Furthermore, the current layer in the Vlasov-Maxwell model is self-consistently supported by a prominent crescent shaped electron velocity distribution that naturally arises due to the temperature transition, which agrees with the electron distribution structures measured by MMS during two asymmetric current layers encountered at the magnetopause.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Reconstruction and interpretation of ionization asymmetry in magnetic confinement via synthetic diagnostics

Abstract Strong poloidal refueling asymmetry in the DIII-D tokamak is inferred from line radiation measurements. Synthetic diagnostics in neutral transport modeling coupled to gyrokinetic simulations illuminate implications for the plasma flow profile in the scrape-off layer of single-null beam-driven discharges. Recycling occurs primarily either on the inner or outer divertor legs, depending on the toroidal magnetic field direction. By reversing the toroidal magnetic field, the observed line radiation asymmetry is nearly eliminated or reversed. It is determined that, while relatively simple physics can describe the observed ionization asymmetry, predicting the overall brightness of the hydrogenic Lyman- α signal requires detailed simulation of the plasma and resulting turbulence. To this end, kinetic plasma simulations fully coupled to comprehensive neutral transport calculations—a novel capability—provide first-principles reproduction of Lyman- α observations on DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗