Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Generators”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Generation of ultrafast electron bunch trains via trapping into multiple periods of plasma wakefields

We demonstrate a novel approach to the generation of femtosecond electron bunch trains via laser-driven wakefield acceleration. We use two independent high-intensity laser pulses, a drive, and an injector, each creating their own plasma wakes. The interaction of the laser pulses and their wakes results in a periodic injection of free electrons in the drive plasma wake via several mechanisms, including ponderomotive drift, wake-wake interference, and pre-acceleration of electrons directly by strong laser fields. Electron trains were generated with up to four quasi-monoenergetic bunches, each separated in time by a plasma period. In conclusion, the time profile of the generated trains is deduced from an analysis of beam loading and confirmed using 2D particle-in-cell simulations

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Deep potential generation scheme and simulation protocol for the Li 10 GeP 2 S 12 -type superionic conductors

We report solid-state electrolyte materials with superior lithium ionic conductivities are vital to the next-generation Li-ion batteries. Molecular dynamics could provide atomic scale information to understand the diffusion process of Li-ion in these superionic conductor materials. Here, we implement the deep potential generator to set up an efficient protocol to automatically generate interatomic potentials for Li 10 GeP 2 S 12 -type solid-state electrolyte materials (Li 10 GeP 2 S 12 , Li 10 SiP 2 S 12 , and Li 10 SnP 2 S 12 ). The reliability and accuracy of the fast interatomic potentials are validated. With the potentials, we extend the simulation of the diffusion process to a wide temperature range (300 K–1000 K) and systems with large size (~1000 atoms). Important technical aspects such as the statistical error and size effect are carefully investigated, and benchmark tests including the effect of density functional, thermal expansion, and configurational disorder are performed. The computed data that consider these factors agree well with the experimental results, and we find that the three structures show different behaviors with respect to configurational disorder. Our work paves the way for further research on computation screening of solid-state electrolyte materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Generation of strong magnetic fields for magnetized plasma experiments at the 1-MA pulsed power machine

Pulsed power technology provides a platform for investigating plasmas in strong magnetic fields using a university-scale machine. Presented here are methods for generating and measuring the 1–4-MG magnetic fields developed for the 1-MA Zebra pulsed power generator at the University of Nevada, Reno. A laser coupled with the Zebra generator produces a magnetized plasma, and experiments investigate how a megagauss magnetic field affects the two-plasmon decay and the expansion of the laser-produced plasma in both transverse and longitudinal magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Load dynamics of double planar foil liners and double planar wire arrays on the UM MAIZE LTD generator

In previous studies using the University of Nevada, Reno's (UNR's) high-impedance Zebra Marx generator (1.9 Ω, 1.7 MA, 100 ns), Double Planar Wire Arrays (DPWAs) proved to be excellent radiators, and Double Planar Foil Liners (DPFLs) proved useful for future inertial confinement fusion applications. This article presents the results of joint UNR/UM (University of Michigan) experiments with aluminum (Al) DPWAs, Al DPFLs, and tungsten (W) DPWAs using UM's Michigan Accelerator for Inductive Z-Pinch Experiments (MAIZE) generator, a low-impedance Linear Transformer Driver (LTD) (0.1 Ω, 0.5–1 MA, and 100–250 ns). The main goals of this study were twofold: the first was a pioneering effort to test whether a relatively heavy Al DPFL could successfully be imploded on a low-impedance university-scale LTD like the MAIZE generator, and, if so, to analyze the results and make comparisons to the optimized, lighter DPWA configurations that have been previously studied. The DPWAs consisted of two planes of micrometer-scale diameter Al or W wires, while the DPFLs consisted of two planes of micrometer-scale thickness Al foils. Diagnostics include filtered Si-diodes, an absolutely calibrated filtered PCD, x-ray pinhole cameras, spectrometers, and gated optical self-emission imaging. The implosion dynamics and radiative properties of Al DPWAs and DPFLs and W DPWAs on the MAIZE LTD are discussed and compared. Time-dependent load inductance calculations derived from measurements of the load current and a MAIZE circuit model provide a relative measurement of pinch strength. In experiments on MAIZE, W planar wire arrays exhibited a higher peak load inductance throughout the pinch than Al DPWAs and DPFLs, while x-ray pulses from Al DPFLs had the longest emission duration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Multiple electron beam generation with different energies and comparable currents from a single cathode potential for high power traveling wave tubes (TWTs)

We present a technique for generating multiple electron beams with different energies and comparable currents from a single cathode stalk at a single potential using nested magnetically insulated coaxial diodes (MICDs). The application is for a multi-stream traveling wave tube. Particle-in-cell simulations are performed for an experimental parameter-based geometry where two thin-walled intense relativistic electron beams immersed in a strong uniform magnetic field propagate through a cylindrical vacuum channel. The analytically derived results are obtained by extending Fedosov’s solution for generating a hollow electron beam from an MICD on a cathode stalk in an infinite magnetic field. Two electron beams are generated and accelerated downstream assuming zero initial kinetic energy of the electrons from the cathodes. Results show both electron beam currents ranging from 66 to 2.8 kA with an energy difference ranging from 6% to 27% depending on voltages applied from 100 to 600 kV and the geometry of the two MICDs. An optimal geometry is a crucial factor in achieving the maximum energy difference between the electron beams for comparable currents. The analytical and numerical simulation results show good agreement. We are currently in the process of planning experiments using the electron beam accelerator (SINUS-6 at UNM) to validate the analytical and simulation results.

Islam, K. N. (ORCID:0000000214397710)↗
DOE OSTI2022

Bias-free terahertz generation from a silicon-compatible photoconductive emitter operating at telecommunication wavelengths

Here, we present a telecommunication-compatible bias-free photoconductive terahertz emitter composed of a bilayer InAs structure directly grown on a high-resistivity silicon substrate. The bilayer InAs structure includes p + -doped and undoped InAs layers, inducing a strong built-in electric field that enables terahertz generation without requiring any external bias voltage. A large-area plasmonic nanoantenna array is used to enhance and confine optical generation inside the photoconductive region with the highest built-in electric field, leading to the generation of a strong ultrafast photocurrent and broadband terahertz radiation. Thanks to a higher terahertz transmission through the silicon substrate and a shorter carrier lifetime in the InAs layers grown on silicon, higher signal-to-noise ratios are achieved at high terahertz frequencies compared with previously demonstrated bias-free terahertz emitters realized on GaAs. In addition to compatibility with silicon integrated optoelectronic platforms, the presented bias-free photoconductive emitter provides more than a 6 THz radiation bandwidth with more than 100 dB dynamic range when used in a terahertz time-domain spectroscopy system.

42 ENGINEERING↗
DOE OSTI2022

Investigation of resistive magnetic field generation by intense proton beams in dense plasmas

Current and future applications of intense proton sources abound, including radiography, cancer therapy, warm dense matter generation, and inertial confinement fusion. With increasingly efficient acceleration and focusing mechanisms, proton current densities may soon approach and exceed 10 10 A/cm 2 , e.g., via intense laser drivers. Simulations have previously shown that in this current density regime, beam-induced field generation plays a significant role in beam transport through dense plasmas. Here, we present a theoretical model for the generation of resistive magnetic fields by intense proton beam transport through solid density plasmas. The theoretical evolution of the magnetic field profile is calculated using an analytic model for aluminum resistivity, heat capacity, and stopping power, applicable from cold matter to hot plasma. The effects of various beam and material parameters on the field are investigated and explained for both monoenergetic and Maxwellian proton beams. For a proton beam with Maxwellian temperature 5 MeV and total energy 10 J, the model calculates resistive magnetic fields up to 150 T in aluminum. In conclusion, the calculated field profiles from several beam cases are compared with 2D hybrid particle-in-cell simulations, with good agreement found in magnitude and time scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Quantum water desalination: Water generation through separate pathways for protons and hydroxide ions in membranes

Much of the water desalination strategies has focused on designing pores and membranes that transport water and reject ions and other molecules at a high rate. In this paper, we discuss an approach where protons (H+) and hydroxide (OH−) ions are transported via different mechanisms through a porous membrane, and subsequently, once they have been transported through the membrane, they recombine to generate water. 2D materials such as graphene and MoS2 have generated significant interest for applications such as desalination. Here, we explore the applicability of one such 2D material—a cubic Ti2C MXene membrane—in desalination by creating a OH− ion selective pore, which significantly suppresses protons but allows OH− ions and water to go through. The catalytic properties of MXenes enable the dissociation of water on the surface, and the dissociated protons translocate through the membrane via quantum-dominated phenomena such as hopping from interstitial-to-interstitial. OH− ions translocate through a positively charged pore and recombine with protons on the other side of the membrane to form water. Our results indicate that water molecules generated via quantum processes can significantly enhance the overall transport of water across the membrane.

Physics↗
DOE OSTI2023

DC electric field generation and distribution in magnetized plasmas

Very large DC and AC electric fields cannot be sustained between conducting electrodes because of volume gas breakdown and/or surface field emission. However, very large potential fields are now routinely generated in plasma structures, such as laser generated wake in unmagnetized plasmas. In magnetized plasmas, large DC fields can also be sustained and controlled perpendicular to the magnetic field, but the metallic end plates limiting the plasma, terminating the magnetic field lines, and usually providing the voltage drop feed between the field lines impose severe restrictions on the maximum field. However, it is shown that very large radial DC voltage drops can be sustained by injecting waves of predetermined frequencies and wave vectors, traveling along the azimuthal direction of an axially magnetized plasma cylinder, or by injecting fast neutral particles beams along this azimuthal direction. The large conductivity along the magnetic field lines and the small conductivity between the field lines then distribute this voltage drop. Furthermore, the global power balance and control parameters of wave and beam generated large DC electric fields in magnetized plasmas are identified, described, and analyzed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Nonlocal suppression of Biermann battery magnetic-field generation for arbitrary atomic numbers and magnetization

The Biermann battery term of magnetohydrodynamics (MHD) generates a magnetic field where electron density gradients and electron temperature gradients are perpendicular to one another. Kinetic simulations and experiments have shown that the rate of magnetic-field generation is lower than Biermann when the electron mean free path becomes comparable to or greater than the temperature gradient scale length, known as the nonlocal regime. We investigate the nonlocal suppression of the Biermann term using simplified Fokker–Planck simulations covering a wide range of parameters. We provide the first fit for nonlocal Biermann suppression that has physically accurate behavior for small and large values of a suitable nonlocality parameter, valid for an arbitrary atomic number, and that includes the effect of magnetization on nonlocality. Lastly, the fit is intended to provide an approximate method to account for reduced magnetic-field generation in MHD codes and theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Second harmonic generation for estimating state of charge of lithium-ion batteries

This study applied the nonlinear ultrasonic method, second harmonic generation, to precisely estimate the state of charge (SoC) in lithium-ion batteries. The second harmonic of the longitudinal wave is generated on a pouch cell battery at 5 MHz with a through-transmission setup. The relative nonlinear parameter β' is determined by analyzing the amplitudes at the fundamental and second harmonic frequencies. To enhance the nonlinear parameter's measurement accuracy, multiple excitation amplitudes are employed. Two separate charge/discharge tests (four-cycle and eight-cycle) are conducted on the battery at a rate of C/10. The nonlinear parameter is measured periodically during the charge/discharge process, and temperature compensation is applied to the measurement. The correlation curves between the nonlinear parameter and the actual SoC align well for the four-cycle and eight-cycle tests, and a robust linear relationship is observed for both correlation curves. A linear model and a second-order polynomial model are applied to fit the correlation using all data points from both tests. The two models are employed to validate the SoC prediction on a second battery by using a four-cycle test. Furthermore, the results indicate that both models can predict the SoC with an accuracy of approximately 3%, whereas the polynomial model demonstrates smaller errors in the regions near 0% and 100% SoC. Therefore, the nonlinear parameter β', measured through the second harmonic generation, can effectively predict lithium-ion battery SoC with an accuracy of less than 3%.

25 ENERGY STORAGE↗
DOE OSTI2025

A generative artificial intelligence framework for long-time plasma turbulence simulations

Generative deep learning techniques are employed in a novel framework for the construction of surrogate models capturing the spatiotemporal dynamics of 2D plasma turbulence. The proposed Generative Artificial Intelligence Turbulence (GAIT) framework enables the acceleration of turbulence simulations for long-time transport studies. GAIT leverages a convolutional variational auto-encoder and a recurrent neural network to generate new turbulence data from existing simulations, extending the time horizon of transport studies with minimal computational cost. The application of the GAIT framework to plasma turbulence using the Hasegawa–Wakatani (HW) model is presented, evaluating its performance via various analyses. Very good agreement is found between the GAIT and the HW models in the spatiotemporal Fourier and Proper Orthogonal Decomposition spectra, the flow topology characterized by the Okubo–Weiss parameter, and the time autocorrelation function of turbulent fluctuations. Excellent agreement has also been obtained in the probability distribution function of particle displacements and the effective turbulent diffusivity. In-depth analyses of the latent space of turbulent states, choice of hyperparameters and alternative deep learning models for the time prediction are presented. Our results highlight the potential of Artificial Intelligence-based surrogate models to overcome the computational challenges in turbulence simulation, which can be extended to other situations such as geophysical fluid dynamics.

Artificial intelligence↗
DOE OSTI2025

Record magnetic field generation by short-pulse laser-driven capacitor-coil targets

Magnetic fields generated by capacitor-coil targets driven by intense short-pulse lasers have been characterized using ultrafast proton radiography. A 1-kJ, 15-ps laser at a center wavelength of 1053 nm irradiated the back plate of the capacitor with an intensity of ∼8.3 × 10 18 W/cm 2 , creating ultra large currents in the connecting coils. High-quality proton data obtained in the axial probing geometry show definitive signatures of magnetic field generation, allowing precision measurement of the field distribution and strength. The data show a coil current of 120 ± 10 kA producing 200 ± 20 Tesla magnetic fields at the coil center at 1.127 ns after the laser drive. In conclusion, this sets a record for magnetic field generation by the short-pulse-powered capacitor-coil targets.

Gao, Lan [Princeton Plasma Physics Laboratory (PPP↗
DOE OSTI2026

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↗
DOE OSTI2026

An ultra-fast method for generating synthetic down-scattered neutron data for inertial confinement fusion implosions

In inertial confinement fusion experiments at the National Ignition Facility, asymmetries are probed by a variety of neutron diagnostics, including neutron imaging systems, real-time neutron activation diagnostics (RTNADs), and neutron spectrometers. It is often useful to generate synthetic data based on these diagnostics to validate and tune models. However, current methods of doing so using Monte Carlo particle tracing are time-consuming. In this paper, an ultra-fast method is presented for generating synthetic neutron images, RTNAD data, and spectrometry data using line integrals and 3D convolutions. While it does not contain as much physics as particle tracing codes, it is thousands of times faster and produces nearly identical data. This enables analysis techniques that depend on generating large amounts of synthetic data, which will prove very useful for the study of asymmetries going forward.

Deuterium↗
DOE OSTI2020

Generation of a quasi-static magnetic field by a circularly polarised laser pulse due to tunnelling gas ionisation

We present a theoretical model of the quasi-static magnetic field generation in a laser channel, which is formed behind the front of a short laser pulse that ionises a gas. The generation of a magnetic field is caused by the appearance of the electron pressure anisotropy during tunnelling ionisation of atoms. In the considered case of subrelativistic laser light intensities, the generated magnetic field can reach ∼1 MG with an energy transformation ratio of about 1 %, which paves the way for identifying the proposed mechanism when use is made of a wide class of ultrashort pulse lasers. (interaction of laser radiation with matter. laser plasma)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Evaluating Methods of Software Bill of Materials Generation to Enhance Nuclear Power Plant Cybersecurity

Instrumentation and control (I&C) systems in nuclear power plants (NPPs) are potential targets of cyberattacks and can prove deleterious for the safety of the NPPs. A Software Bill of Materials (SBOM) provides a detailed list of the various components and their dependencies in software, which helps in vulnerability and risk assessment for cyber hygiene and situational awareness. For an NPP, the process of generating an accurate SBOM report can be complex due to the legacy systems and firmware binaries involved. While most current SBOM tools are focused more on modern internet technology software, this research provides insights and guidelines for an NPP to generate an accurate and efficient SBOM. Here, the paper proposes a new methodology to help NPPs categorize software and use appropriate tools to generate SBOMs for their digital I&C systems.

SBOM↗
DOE OSTI2026

Delayed Neutron Precursor Group Parameter and Spectra Generation from Fast Fission of 235U in SCALE

Delayed neutron precursor (DNP) group data are important for modeling reactor dynamics. Although the data for individual DNPs have been developed over time, the DNP group data present in the Evaluated Nuclear Data Files (ENDF) have not been updated in the past 20 years. In this work, we use SCALE to recreate the Godiva experiment that was used to generate the original DNP group structure for fast fission of 235U. However, each DNP is modeled using up-to-date data, and the results are then converted into a newly updated group structure. This conversion uses an iterative linear least squares solver to minimize chi-squared. The approaches used in this work also enable energy spectrum generation and uncertainty tracking. The method used in this paper for fast 235U fission DNP group structure updating can be applied to different energies and fissile nuclides. Demonstration of the uncertainty tracking in reactor kinetics and dynamics simulations is shown using point reactor kinetics simulations. Results show that there are data discrepancies between the International Atomic Energy Agency database and data used in ORIGEN, which are currently being fixed. Results also show that the proposed method for group spectra generation performs well.

Seifert, Luke [University of Illinois]↗