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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Role of electrostatic perturbation on kinetic resistive wall mode with application to spherical tokamak

Abstract A more complete non-perturbative magnetohydrodynamic (MHD)-kinetic hybrid formulation is developed by including the perturbed electrostatic potential δφ in the particle Lagrangian. The fluid-like counter-parts of the hybrid equations, in the Chew-Goldberger-Low high-frequency limit, are also derived and utilized to test the new toroidal implementation in the MARS-K code. Application of the updated non-perturbative hybrid model for a high- β spherical tokamak plasma in MAST finds that the perturbed electrostatic potential generally plays a minor role in the n = 1 ( n is the toroidal mode number) resistive wall mode instability. The effect of δφ is largely destabilizing, with the growth rate of the instability increased by several (up to 20) percent as compared to the case without including δφ . A similar relative change is also obtained for the kinetic-induced resonant field amplification effect at high- β in the MAST plasma considered. The updated capability of the MARS-K code allows quantitative exploration of drift kinetic effects on various MHD instabilities and the antenna-driven plasma response where the electrostatic perturbation, coupled to magnetic perturbations, may play important roles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Plasma Mirrors For High Power Lasers: A new approach for high repetition rates combined with realistic PIC simulations

We describe a research program to develop high quality plasma mirrors for use with high repetition rate, high power laser facilities to greatly facilitate experiments in high energy density physics, particularly when using solid density targets. A system delivering ultrathin, free standing liquid crystal films that could handle PW class laser pulses was developed that preserved the laser beam image quality and improved pulse contrast by over two orders of magnitude. The pulse contrast improvement was measured using a high dynamic range cross-correlation. The system operated at a repetition rate of several PMs formed in situ per minute. Extension to 1 Hz repetition rates should be possible. As a practical application, a PM system was used to separate laser accelerated electrons from the ultrashort pulse drive laser so that the electron beam emittance could be directly measured. The 20 nm thick PMs did not contribute significantly to emittance degradation. It was also demonstrated that the films could operate in the difficult plasma and laser environment present for GeV laser based electron acceleration. PM operation is still not well understood and much work with PMs is done empirically. Accordingly, we also demonstrated a particle-in-cell based simulation technique that would model PM operation, tracking the PM operation from cold, neutral atoms to a hot dense plasma by accounting for multiphoton ionization, plasma collisionality, and the dynamically changing index of refraction. Simulations in 3D were compared to a 2D based approach that was comparable. Finally, we developed a simpler model that can predict the intensity at which a plasma mirror will have its peak reflectivity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Thinking Bayesian for plasma physicists

Bayesian statistics offers a powerful technique for plasma physicists to infer knowledge from the heterogeneous data types encountered. To explain this power, a simple example, Gaussian Process Regression, and the application of Bayesian statistics to inverse problems are explained. The likelihood is the key distribution because it contains the data model, or theoretic predictions, of the desired quantities. By using prior knowledge, the distribution of the inferred quantities of interest based on the data given can be inferred. Because it is a distribution of inferred quantities given the data and not a single prediction, uncertainty quantification is a natural consequence of Bayesian statistics. The benefits of machine learning in developing surrogate models for solving inverse problems are discussed, as well as progress in quantitatively understanding the errors that such a model introduces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Multiscale modeling and laser diagnostics to reveal non-equilibrium reaction chemistry at a plasma-liquid interface

Low-temperature, atmospheric-pressure plasmas in contact with liquid are at the core of a wide range of applications including water treatment, medicine, materials synthesis, and chemical transformation. In general, plasma-liquid processes are scientifically compelling because reactivity can be produced without a catalyst, in relatively inert molecules, such as air or nitrogen and liquid water, in their native states at ambient conditions. However, reactions at a plasma-liquid interface are extremely complex, occurring at a multiphase, gas-liquid boundary where excited or dissociate gaseous species dissolve and react with solution-phase species, and unique reaction pathways are induced by non-equilibrium chemistry. In particular, detailed knowledge of the physical and chemical processes, including what species are produced in the gas phase and how these species are subsequently transported across and react near the interfacial region, remains largely unanswered. In this project, modeling of the non-equilibrium reaction chemistry at the interface of low-temperature, atmospheric-pressure plasmas and liquid water is developed, supported by advanced laser diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Application of machine learning for optical emission spectroscopy data in NAGDIS-II

In this study, we applied machine learning to optical emission spectroscopy (OES) data and device parameters from the linear plasma device NAGDIS-II to explore the potential application of machine learning for predicting electron density, $n$ e , and temperature, $T$ e . The covered ranges of $n$ e and $T$ e , which were measured by an electrostatic probe, are 3.6 × 10 17 –2.4 × 10 19 m -3 and 0.3–7.1 eV, respectively. A three hidden layer neural network (NN) is introduced to model the relationship between $n$ e /$T$ e and the combination of line intensities, radial position, and device parameters. It is shown that the errors in $n$ e and $T$ e become 18.0 and 18.8%, respectively, which were almost the same level for the electrostatic probe, using all available data. Lasso regression and greedy algorithm are used to select the necessary line emissions. In conclusion, it is shown that four- or five-line intensities are sufficient to obtain almost the same quality as the one with all the other lines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Low-divergence femtosecond X-ray pulses from a passive plasma lens

Electron and X-ray beams originating from compact laser-wakefield accelerators have very small source sizes that are typically on the micrometre scale. Therefore, the beam divergences are relatively high, which makes it difficult to preserve their high quality during transport to applications. To improve on this, tremendous efforts have been invested in controlling the divergence of the electron beams, but no mechanism for generating collimated X-ray beams has yet been demonstrated experimentally. Here we propose and realize a scheme where electron bunches undergoing focusing in a dense, passive plasma lens can emit X-ray pulses with divergences approaching the incoherent limit. Furthermore, compared with conventional betatron emission, the divergence of this so-called plasma lens radiation is reduced by more than an order of magnitude in solid angle, while maintaining a similar number of emitted photons per electron. This X-ray source offers the possibility of producing brilliant and collimated few-femtosecond X-ray pulses for ultra-fast science, in particular for studies based on X-ray diffraction and absorption spectroscopy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Stable electron beam propagation in a plasma column

The stability of plasma-based accelerators against transverse misalignments and asymmetries of the drive beam is crucial for their applicability. Without stabilizing mechanisms, even small initial offsets of the drive beam centroid can couple coherently to the plasma wake, grow, and ultimately lead to emittance degradation or beam loss for a trailing witness beam. In this work, we demonstrate the intrinsic stability of a beam propagating in a plasma column. This result is relevant in the context of plasma-based positron acceleration, where a wakefield suitable for the transport and acceleration of a positron witness beam is generated in a plasma column by means of an electron drive beam. The stable propagation of the drive beam is a necessary condition for the experimental implementation of this scheme. The differences and similarities of stabilizing mechanisms in a plasma column compared to a homogeneous plasma are identified via theory and particle-in-cell simulations. Experimental tolerances are given, demonstrating the experimental feasibility of the scheme.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Oxidation of lithium plasma facing components and its effect on plasma performance in the lithium tokamak experiment-β

The characteristics of lithium-coated plasma-facing components (PFCs) have been correlated with plasma performance on the lithium tokamak experiment-β (LTX-β). Previous experiments on LTX showed that the application of lithium to PFCs was needed to achieve higher performance discharges with flat electron temperature profiles and high edge temperatures. Samples that match the LTX-β PFCs were exposed to plasmas before and after PFCs were coated with lithium and transferred under vacuum to a surface analysis station. Measurements using x-ray photoelectron spectroscopy (XPS) revealed that the primary surface constituent was lithium oxide. Earlier XPS analysis of lithium-coated PFCs on LTX was only able to show the presence of surface oxygen. The new XPS data from LTX-β have sufficient resolution to clearly identify lithium compounds for the first time, and enable them to be correlated with how lithium-coated PFCs can reduce impurities and retain hydrogen to reduce recycling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Modular Design of High Temperature and Pressure Heat Exchangers Using 3D Printing

Functionally graded material (FGM), leveraged by latest additive manufacturing (AM) technologies, can add significant values to high temperature applications such as the HTR in supercritical sCO2 Brayton cycles. The project was focused on fabricating FGMs with complex geometries such as flow channels using DED and L-PBF technologies to support the modular design concept in achieving high-performance and low-cost high temperature recuperators for the sCO2 Brayton cycle. Samples printed from the base materials including both SS 316 and Inconel 625 have mostly met the material standards. L-PBF samples have achieved the fine feature sizes with good geometrical accuracy. In addition, DED has demonstrated its printability on LPBF part with both direct transition and using 50/50 mixed powders. Despite various challenging, the project helped advance the current state-of-the-art of DED technology in terms of printing fine geometries.

14 SOLAR ENERGY↗
DOE OSTI2020

Evaluating turbulence models at high energy densities

The RESHOCK campaign at Lawrence Livermore National Laboratory has been working on increasing our understanding of the evolution of turbulent, unstable plasma interfaces which are applicable in various HED applications including ICF implosions. A common approach to model such interfaces involves the use of Renolds-Averaged-Navier-Stokes (RANS) models whose parameters have been constrained by theory and experiments. These parameter sets are not unique and the applicability of one set of tuned model parameters to systems with differing shock strengths or material densities has not been well tested. Our new NIF experiments, along with related studies of turbulent shear flows, provide data and model validation for plasma interfaces in the HED regime. Our experiments measure mixing-layer width at an unstable interface in the plasma regime and are specifically designed to challenge mix models of the Reynolds-Averaged-Navier-Stokes (RANS) type where turbulence is assumed to be fully developed, i.e. the flow exhibits a broad spectrum of length scales without memory of the initial condition.4 We utilize precise control of the initial interface conditions (densities on both sides of the interface, an initial rippled perturbation pattern consisting of equally weighted wavelengths between 10 and 20 microns, and initial material compositions) along with a repeatable drive history

36 MATERIALS SCIENCE↗
DOE OSTI2022

Path Integral Monte Carlo Simulations of Iron Plasmas (Final Technical Report)

This documents is the final technical report for our grant entitled "Path Integral Monte Carlo Simulations of Iron Plasmas" that focused on developing path integral Monte Carlo (PIMC) computer simulations. This techniques will be developed to study plasmas composed of heavier elements including iron and other third row elements. Equations of state (EOS) and transport properties will be derived in the regime of warm dense matter (WDM) and dense plasmas where existing first-principles methods cannot be applied. While standard density functional theory (DFT) has been used to accurately predict the structure of many solids and liquids up to temperatures on the order of 100,000 K, this method is not applicable at much higher temperature because the number of partially occupied electronic orbitals reaches intractably large numbers or the use of finite-temperature free energy functionals in orbital-free DFT introduces an uncontrolled approximation. Here we focus on PIMC methods that become more and more efficient with increasing temperatures and still include all electronic correlation effects. In this approach, electronic excitations increase the efficiency rather than reduce it. While it had commonly been assumed this method could only be applied to elements without core electrons, we showed that PIMC with free-particle nodes works well for first-row elements (PRL 108 (2012) 115502). Most recently, we extended the applicability range of all-electron PIMC to second-row elements by adopting localized nodal surfaces (PRL 115 (2015) 176403). To simulate third-row elements efficiently under WDM conditions, we propose a new method to remove core electrons by introducing pseudo-nodes. We explain our approach step by step and present preliminary results. We focus our method development on getting PIMC simulations of iron to work because of its fundamental importance for WDM and astrophysics. Then we move on to krypton and copper-doped beryllium, a ICF ablator material. We plan to continue working on key second-row material such as Na, Mg, MgO, Al, silica, and silicon-doped plastic ablators. Our collaborators at LLNL, will use our PIMC EOS data both as comparisons to existing semi-empirical, EOS-generating schemes, and as input for continuum radiation hydrodynamics simulations. We will establish an efficient pipeline from PIMC to macroscopic continuum studies of materials response. An emphasis will be placed on benchmarking such methods for plasmas of heavy elements at the very high temperatures (~100 eV) and low densities that are generated when Hohlraum radiation heats the ablator material in indirect drive laser experiments. Results from changes to the EOS will be of immeasurable importance to the designers at the National Ignition Facility (NIF) and at other facilities. Starting with our EOS of Cu-doped Be, our second collaborator at LLE, will perform real-time simulations of laser fusion experiments at the Omega laser and at the NIF to determine how sensitive the compression path depends on the ablator EOS. Since our collaborator also has experience in performing orbital-free DFT calculations, we propose to compare predictions from this method with PIMC results. In joint publications, we plan to analyze the accuracy of different free-energy functionals in order to understand why existing orbital-free DFT calculations do not predict compression peaks along the shock Hugoniot curve that we see with PIMC. The peaks are caused by the ionization of various electron shells. Their accurate characterization is important to compare with experimental results. We will break new ground by developing PIMC techniques that can simulate iron and all other third row elements in the plasma and WDM regimes. We introduce the concept of pseudo-nodes for the efficient treatment of the core-electrons. The EOS and transport properties will be derived and published online in the form of a new WDM database. Our PIMC EOS calculations will benchmark and possibly replace semi-analytical EOS tables like QEOS or SESAME, which will impact the hydrocode simulation community and will affect the design of NIF targets. Our PIMC results will help to improve the accuracy of orbital-free DFT simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Improvement in the spatial resolution of heavy ion beam probe measurements through application of ion optics

A technique for more accurately modeling and improving the spatial resolution of heavy ion beam probe measurements is described. We use a set of particle trajectories to numerically determine the focusing properties of a complicated three-dimensional magnetic field and characterize those properties with a transfer matrix. We then modify the transfer matrix approach of traditional ion optics to include a parameter that describes the ionization location of the detected ions. The ion optics model calculated using this technique enables a more accurate description of the particle trajectories than previously feasible. The model also allows one to easily determine an initial beam focus that could be used during experimental operation to optimize the spatial resolution of measurements. The technique has been applied to the design of a heavy ion beam probe diagnostic for the Wendelstein 7-X stellarator and improvements in the modeled spatial resolution by a factor of about 2 over previous estimates are possible. As a result, the improved spatial resolution will enable measurements of plasma fluctuations with smaller wavelengths than would otherwise be possible.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Accuracy of the explicit energy-conserving particle-in-cell method for under-resolved simulations of capacitively coupled plasma discharges

The traditional explicit electrostatic momentum-conserving particle-in-cell algorithm requires strict resolution of the electron Debye length to deliver numerical stability and accuracy. The explicit electrostatic energy-conserving particle-in-cell algorithm alleviates this constraint with minimal modification to the traditional algorithm, retaining its simplicity, ease of parallelization, and acceleration on modern supercomputing architectures. In this article, we apply the algorithm to model a one-dimensional radio frequency capacitively coupled plasma discharge relevant to industrial applications. The energy-conserving approach closely matches the results from the momentum-conserving algorithm and retains accuracy even for cell sizes up to 8 times the electron Debye length. For even larger cells, the algorithm loses accuracy due to poor resolution of steep gradients within the radio frequency sheath. Accuracy can be recovered by adopting a non-uniform grid, which resolves the sheath and allows for cell sizes up to 32 times the electron Debye length in the quasi-neutral bulk of the discharge. The effect is an up to 8 times reduction in the number of required simulation cells, an improvement that can compound in higher-dimensional simulations. We therefore consider the explicit energy-conserving algorithm as a promising approach to significantly reduce the computational cost of full-scale device simulations and a pathway to delivering kinetic simulation capabilities of use to industry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Symplectic neural network and its application to charged particle dynamics in electromagnetic fields

Recently, machine learning models have shown many successes in various applications in science and technology. In this work, we focus on the charged particle dynamics, with the development of a class of symplectic neural networks, including a linear version, SympMat, and a nonlinear version, HénonNet. Both are designed to preserve the structure of Hamiltonian systems. We show that they can be used to model relevant Hamiltonian systems of interest in plasma physics and astrophysics, for linear and nonlinear charged particle dynamics, with the potential to bridge multi-scale simulations. These symplectic neural networks are adapted to the applications in plasma simulations and particle-wave interaction with parametric dependence and periodicity, where we have investigated their performance and accuracy. In particular, SympMat is shown to outperform the traditional Boris particle pusher down to the sub-gyroperiod scale in the case of charged particles in uniform magnetic fields. HénonNet successfully predicts the hot electron distribution, which is validated against theoretical results. These results highlight the potential of symplectic neural networks as a trajectory integrator for particle-in-cell simulations or a fast surrogate to replace conventional numerical schemes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Efficient Integration of Algebraic Constraint for Exponential Time Integration

This work is a continuation of a previous project where the high efficiency of exponential integration methods for DRMHD systems was demonstrated. Often algebraic constraints must also be enforced for DRMHD systems of interest. Straightforward application of exponential methods to DRMHD equations with constraints leads to prohibitively computationally expensive methods. In this work, we propose new exponential schemes that allow the constraints to be removed from evaluation of exponential matrix functions which drastically reduces computational complexity by eliminating the need to perform computations enforcing constraints in exponential calculations while still preserving a high order of accuracy and allowing for a large time step even when the problem is stiff. This idea is similar to the W-methods and is achieved by carefully designing a method with the desired order of accuracy, even with an incomplete Jacobian matrix used as an argument of exponential-like functions. The constraints are accounted for by including them in the evaluation of the right-hand-side forcing function of the spatially discretized system. We study performance of the new methods on test problems and outline future research directions that this work opens.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses

Scientific computations are expected to be increasingly distributed across wide-area networks, and Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. Application-level measurements of MPI operations reflect the connection Round-Trip Time (RTT) and loss rate, and machine learning methods have been previously developed to estimate them under deterministic periodic losses. In this paper, we consider more complex, random losses with unform, Poisson and Gaussian distributions. We study five disparate machine leaning methods, with linear and non-linear, and smooth and non-smooth properties, to estimate RTT and loss rate over 10Gbps connections with 0-366ms RTT. The diversity and complexity of these estimators combined with the randomness of losses and TCP’s non-linear response together rule out the selection of a single best among them; instead, we fuse them to retain their design diversity. Overall, the results show that accurate estimates can be generated at low loss rates but become inaccurate at loss rates 10% and higher, thereby illustrating both their strengths and limitations.

Generalization Bounds↗
DOE OSTI2023

Charge decay in the spatial afterglow of plasmas and its impact on diffusion regimes

Abstract The spatial afterglow is a region at the boundary of a non-equilibrium plasma where charged species relax into ambient equilibrium. In many applications, the spatial afterglow is the part of the plasma that interacts with surfaces, such as suspended particles or a material substrate. However, compared to the bulk plasma, there has been little effort devoted to studying the properties of the spatial afterglow, and a fundamental analysis has not yet been developed. Here, we apply double Langmuir probe measurements and develop an advection-diffusion-recombination model to provide a detailed description of charged species in the spatial afterglow over a wide range of pressures, temperatures, plasma dimensions, and flow rates. We find that the density of charged species in the spatial afterglow decays by orders of magnitude, which leads to a transition from ambipolar to free diffusion. These insights can be used to explain or predict experimental observations of phenomena, such as the charging of dust grains and the dose of charged species to a biomaterial.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

MeV x-ray production from a petawatt laser in the regime of a relativistically transparent preplasma, with applications to radiography

Bright sources of mega-electron volt (MeV) x-rays have many unique applications, including nuclear physics, radiation oncology, and imaging high areal density systems. High intensity lasers (>1018 W cm−2) incident on mm-thick metal targets can deliver MeV x-rays via the bremsstrahlung process, providing sources with ultrashort duration (∼ps) and small source size (∼100 μm). Here, we report on a reproducible regime of laser-driven MeV x-ray sources, where the x-ray dose can be further increased by 60% by coating the metal target with micrometers of plastic. High fidelity numerical simulations indicate that the interaction is a result of relativistic transparency in the preplasma. Though relativistic transparency is present in both cases, the greater sound speed and smaller ion inertia of the plastic target allow the laser to more deeply penetrate and couple more efficiently to electrons. Radiography with this system demonstrates a resolving power < 300 μm, important for imaging applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗