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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Kinetic simulations comparing quasi-parallel and quasi-perpendicular piston-driven collisionless shock dynamics in magnetized laboratory plasmas

Magnetized collisionless shocks are common in astrophysical systems, and scaled versions can be created in laboratory experiments by utilizing laser-driven piston plasmas to create these shocks in a magnetized background plasma. A key parameter for these experiments is the angle θB between the shock propagation direction and the background magnetic field. We performed quasi-1D piston-driven shock simulations to explore shock formation, evolution, and key observables relevant to laboratory experiments for a range of shock angles between θB=90° to θB=30°. Our results show that the spatial and temporal scales of shock formation for all angles considered are similar when expressed in terms of the perpendicular component of the magnetic field. In a steady state, ion and electron temperatures become more isotropic, and the electron-to-ion temperature ratio is higher for smaller θB. At θB=30°, ion heating parallel to the magnetic field becomes dominant, associated with more ions being reflected at one discontinuity and subsequently trapped by the next discontinuity due to shock reformation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Wavelength modulation laser-induced fluorescence for plasma characterization

Laser-Induced Fluorescence (LIF) spectroscopy is an essential tool for probing ion and atom velocity distribution functions (VDFs) in complex plasmas. VDFs carry information about the kinetic properties of species that is critical for plasma characterization. Accurate interpretation of these functions is challenging due to factors such as multicomponent distributions, broadening effects, and background emissions. Our research investigates the use of Wavelength Modulation (WM) LIF to enhance the sensitivity of VDF measurements. Unlike standard Amplitude Modulation (AM) methods, WM–LIF measures the derivative of the LIF signal. This approach makes variations in VDF shape more pronounced. VDF measurements with WM–LIF were investigated with both numerical modeling and experimental measurements. The developed model enables the generation of both WM and AM signals, facilitating comparative analysis of fitting outcomes. Experiments were conducted in a weakly collisional argon plasma with magnetized electrons and non-magnetized ions. Measurements of the argon ion VDFs employed a narrow-band tunable diode laser, which scanned the 4p 4 D 7/2 –3d 4 F 9/2 transition centered at 664.553 nm in vacuum. A lock-in amplifier detected the second harmonic WM signal, which was generated by modulating the laser wavelength with an externally controlled piezo-driven mirror of the diode laser. Finally, our findings indicate that the WM–LIF signal is more sensitive to fitting parameters, allowing for better identification of VDF parameters such as the number of distribution components, their temperatures, and velocities. In addition, WM–LIF can serve as an independent method to verify AM measurements and is particularly beneficial in environments with substantial light noise or background emissions, such as those involving thermionic cathodes and reflective surfaces.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

High-resolution particle-in-cell simulations of two-dimensional Bernstein–Greene–Kruskal modes

We present two-dimensional (2D) particle-in-cell (PIC) simulations of 2D Bernstein–Greene–Kruskal modes, which are exact nonlinear steady-state solutions of the Vlasov–Poisson equations, on a 2D plane perpendicular to a background magnetic field, with a cylindrically symmetric electric potential localized on the plane. PIC simulations are initialized using analytic electron distributions and electric potentials from the theory. We confirm the validity of such solutions using high-resolutions up to a 20482 grid. We show that the solutions are dynamically stable for a stronger background magnetic field, while keeping other parameters of the model fixed, but become unstable when the field strength is weaker than a certain value. When a mode becomes unstable, we observe that the instability begins with the excitation of azimuthal electrostatic waves that ends with a spiral pattern.

Physics↗
DOE OSTI2024

Core-edge modeling of gyrokinetic turbulence by coupling the delta-f and total-f models in the XGC code

Whole device gyrokinetic turbulence is modeled using a delta-f model in the core coupled to a total-f model in the edge. This new model is implemented in the gyrokinetic code X-Point Included Gyrokinetic Code (XGC) and works within a single simulation. It employs a canonical Maxwellian background in the core and the usual local Maxwellian in the edge. These different core and edge backgrounds are coupled over an overlap region. A thermal-bath operator is used to keep δf small in the core.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Design and characterization of the time-resolved opacity spectrometer (OpSpecTR) for the NIF iron opacity campaign

A new time-resolved opacity spectrometer (OpSpecTR) is currently under development for the National Ignition Facility (NIF) opacity campaign. Here, the spectrometer utilizes Icarus version 2 (IV2) hybridized complementary metal–oxide–semiconductor sensors to collect gated data at the time of the opacity transmission signal, unlocking the ability to collect higher-temperature measurements on NIF. Experimental conditions to achieve higher temperatures are feasible; however, backgrounds will dominate the data collected by the current time-integrating opacity spectrometer. The shortest available OpSpecTR integration time of ~2 ns is predicted to reduce self-emission and other late-time backgrounds by up to 80%. Initially, three Icarus sensors will be used to collect data in the self-emission, backlighter, and absorption regions of the transmission spectrum, with plans to upgrade to five Daedalus sensors in future implementations with integration times of ~1.3 ns. We present the details of the diagnostic design along with recent characterization results of the IV2 sensors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Developing time-resolved x-ray diffraction diagnostics at the National Ignition Facility (invited)

As part of a program to measure phase transition timescales in materials under dynamic compression, we have designed new x-ray imaging diagnostics to record multiple x-ray diffraction measurements during a single laser-driven experiment. Our design places several ns-gated hybrid CMOS (hCMOS) sensors within a few cm of a laser-driven target. The sensors must be protected from an extremely harsh environment, including debris, electromagnetic pulses, and unconverted laser light. Another key challenge is reducing the x-ray background relative to the faint diffraction signal. Building on the success of our predecessor (Target Diffraction In Situ), we implemented a staged approach to platform development. First, we built a demonstration diagnostic (Gated Diffraction Development Diagnostic) with two hCMOS sensors to confirm we could adequately protect them from the harsh environment and also acquire acceptable diffraction data. This allowed the team to quickly assess the risks and address the most significant challenges. Here, we also collected scientifically useful data during development. Leveraging what we learned, we recently developed a much more ambitious instrument (Flexible Imaging Diffraction Diagnostic for Laser Experiments) that can field up to eight hCMOS sensors in a flexible geometry and participate in back-to-back shots at the National Ignition Facility (NIF). The design also allows for future iterations, such as faster hCMOS sensors and an embedded x-ray streak camera. The enhanced capabilities of the new instrument required a much more complex design, and the unexpected issues encountered on the first few shots at NIF remind us that complexity has consequences. Our progress in addressing these challenges is described herein, as is our current focus on improving data quality by reducing x-ray background and quantifying the uncertainties of our diffraction measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Studying single-electron traps in newly fabricated Skipper-CCDs for the Oscura experiment using the pocket-pumping technique

Understanding and characterizing very low-energy (⁠ ∼eV) background sources is a must in rare-event searches. Oscura, an experiment aiming to probe electron recoils from sub-GeV dark matter using a 10 kg skipper-CCD detector, has recently fabricated its first two batches of sensors. In this work, we present the characterization of defects/contaminants identified in the buried-channel region of these newly fabricated skipper-CCDs. These defects/contaminants produce deferred charge from trap emission in the images next to particle tracks, which can be spatially resolved due to the sub-electron resolution achieved with these sensors. Using the trap-pumping technique, we measured the energy and cross section associated with these traps in three Oscura prototype sensors from different fabrication batches which underwent different gettering methods during fabrication. Results suggest that the type of defects/contaminants is more closely linked to the fabrication batch rather than to the gettering method used. The exposure-dependent single-electron rate (SER) of one of these sensors was measured ∼100 m underground, yielding (1.8±0.3)×10−3e−/pix/day at 131 K. The impact of the identified traps on the measured exposure-dependent SER is evaluated via a Monte Carlo simulation. Results suggest that the exposure-dependent SER of Oscura prototype sensors would be lower in lower background environments as expected.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Evolution of intermittent filaments in the scrape-off layer of NSTX

Filamentary structures naturally arise from background turbulence in the scrape-off layer (SOL) of plasmas, leading to significant particle and heat transport that can degrade overall plasma confinement. This enhanced transport can contribute to unacceptably high heat loads on plasma-facing components. As such, understanding the physics of SOL plasma filaments is critical for predicting and mitigating their effects in future fusion devices. On the National Spherical Torus Experiment (NSTX), plasma filaments—commonly referred to as “blobs”—were investigated using the gas-puff imaging (GPI) diagnostic in the edge and SOL regions. The analysis involved identifying, segmenting, and tracking the characteristic contours of the blobs in each frame of the GPI video sequences. Their evolution was characterized through shape descriptors, velocity, and angular velocity derived from their contour coordinates. The results indicate that as the blob area increases, their shapes become more concave and less circular, suggesting reduced structural stability in larger blobs. This result aligns with previous theoretical results where it was shown that larger blobs are more susceptible to instabilities [Krasheninnikov et al., J. Plasma Phys. 74, 679–717 (2008) and D'Ippolito et al., Phys. Plasmas 18, 060501 (2011)]. A positive correlation was observed between radial velocity and radial position, suggesting radially outward acceleration of the filaments, potentially driven by decreasing viscous drag toward the far SOL. Interestingly, blobs in background SOL turbulence exhibited minimal spinning in contrast to filaments originating from edge localized modes, which show substantial rotation during their paths [Lampert et al., Phys. Plasmas 29, 102502 (2022)]. Statistical analysis of the solidity and total curvature shape descriptors, along with their temporal evolution, revealed relatively broad, near-Gaussian distributions. This suggests that blob morphology is strongly influenced by stochastic turbulent processes in the surrounding plasma environment. Blob parameters were also compared with bulk plasma and radial profile measurements. Notable trends were found between blob rotation and poloidal velocity with collisionality and line-integrated density. These findings contribute to a deeper understanding of blob dynamics and provide valuable insights for refining SOL turbulence models.

Covariance and correlation↗
DOE OSTI2026

Development of a broadband hard x-ray radiography platform for pulsed-power experiments

In this article, we develop and demonstrate a broadband hard x-ray radiography platform at the Zebra Pulsed Power Laboratory that integrates point-projection radiography, bremsstrahlung measurements, and hard x-ray pinhole imaging, designed to diagnose current-driven, cylindrically compressed matter. Initial laser-pulsed-power coupled experiments revealed that intense background radiation generated during 1 MA Zebra current shots overwhelmed laser-produced hard x-rays, obscuring radiographic images. Using combined spectral and spatial diagnostics, we identify energetic electrons accelerated by return currents as the dominant source of background hard x-rays, with electron energies inferred to be 3–4 MeV based on Monte Carlo simulations, and demonstrate mitigation through modifications to the radiation shielding and return-current configuration. The diagnostic platform was validated using a wire-pinch hard x-ray source, allowing radiographs of static 1-mm-diameter aluminum wires to be obtained while simultaneously measuring x-ray source spectra and spatial emission distributions within a single shot. Measured wire transmission profiles were quantitatively reconstructed using radiation transport simulations that incorporate an experimentally inferred two-temperature exponential x-ray spectrum from bremsstrahlung signal analysis and spatially distributed emission sources identified by pinhole imaging. Agreement between measured and simulated transmission profiles demonstrates the validity of the radiographic and x-ray source characterization approach, establishing this diagnostic platform as a promising tool for diagnosing magnetically driven, high-density plasmas relevant to warm dense matter and inertial fusion energy research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Collisionless Larmor coupling and blob formation in a laser-plasma expanding into a magnetized ambient plasma

Collisionless Larmor coupling is a fundamental process in space and astrophysical plasmas that enables momentum transfer between an expanding plasma and a magnetized ambient medium. Here, in this paper, we report on the laboratory experimental study of Larmor coupling leading to the formation of a plasma blob associated with a laser-driven, super-Alfvénic plasma flow on the Large Plasma Device at the University of California, Los Angeles. The high-repetition rate enables systematic spatial and temporal scans of the plasma evolution using Doppler spectroscopy, as well as measurements of the magnetic field, electrostatic field, and self-emission of both debris and ambient ions using filtered imaging. We observe the self-focusing of the laser-produced plasma and the formation of a secondary diamagnetic cavity associated with a blob composed of background ions. Doppler spectroscopy reveals the transverse velocity distribution of the background ions, providing direct evidence of ion energization via Larmor coupling. The systematic spatial and temporal scans enabled by the high-repetition-rate experiment allow for a detailed characterization of the ion dynamics. These experimental observations are supported by numerical simulations that provide more insight into the kinetic-scale physics associated with blob formation as well as the role of the ambient plasma density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Validation of 266 nm UV Raman thermometry using the alpha-to-beta quartz transition

Ultraviolet Raman scattering is a promising diagnostic for temperature measurements relevant to dynamic compression experiments, where improved signal strength and reduced background are critical. In this work, we experimentally validate Raman thermometry at 266 nm using crystalline quartz heated through the α to β phase transition in a tube furnace. Quartz provides a useful benchmark because of its well-characterized transition temperature near 846 K at ambient pressure. Temperatures inferred from the Stokes to anti-Stokes intensity ratio are compared with thermocouple measurements and with the observed phase transition. Single-shot Raman temperatures track the thermocouple closely, with an empirical single-shot scatter of approximately ±15 K under the present conditions. Temporal averaging reduces shot-to-shot scatter and improves agreement between the Raman temperatures and thermocouple readings to within approximately 8 K, while the transition is identified within 5 K of the accepted value. Measurements are performed using the fourth harmonic of a nanosecond pulsed Nd:YAG laser at 266 nm. The shorter excitation wavelength provides enhanced Raman scattering efficiency and reduced visible background relative to conventional visible excitation. Comparison with 532 nm Raman measurements acquired in the same experimental geometry demonstrates substantially improved signal-to-noise ratio for the UV configuration. These results establish 266 nm Raman thermometry as a reliable and accurate temperature diagnostic under controlled heating conditions and provide a quantitative benchmark for future application in dynamic compression and shock physics experiments.

Chemistry - Chemical explosives↗
DOE OSTI2023

INDETERMINATE1 -mediated expression of FT family genes is required for proper timing of flowering in Brachypodium distachyon

The transition to flowering is a major developmental switch in plants. In many temperate grasses, perception of indicators of seasonal change, such as changing day-length and temperature, leads to expression of FLOWERING LOCUS T1 ( FT1 ) and FT-Like ( FTL ) genes that are essential for promoting the transition to flowering. However, little is known about the upstream regulators of FT1 and FTL genes in temperate grasses. Here, we characterize the monocot-specific gene INDETERMINATE1 ( BdID1 ) in Brachypodium distachyon and demonstrate that BdID1 is a regulator of FT family genes. Mutations in ID1 impact the ability of the short-day (SD) vernalization, cold vernalization, and long-day (LD) photoperiod pathways to induce certain FTL genes. BdID1 is required for upregulation of FTL9 ( FT-LIKE9 ) expression by the SD vernalization pathway, and overexpression of FTL9 in an id1 background can partially restore the delayed flowering phenotype of id1 . We show that BdID1 binds in vitro to the promoter region of FTL genes suggesting that ID1 directly activates FTL expression. Transcriptome analysis shows that BdID1 is required for FT1 , FT2 , FTL12 , and FTL13 expression under inductive LD photoperiods, indicating that BdID1 is a regulator of the FT gene family. Moreover, overexpression of FT1 in the id1 background results in rapid flowering similar to overexpressing FT1 in the wild type, demonstrating that BdID1 is upstream of FT family genes. Interestingly, ID1 negatively regulates a previously uncharacterized FTL gene, FTL4, and we show that FTL4 is a repressor of flowering. Thus, BdID1 is critical for proper timing of flowering in temperate grasses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Better Method to Calculate Fuel Burnup in Pebble Bed Reactors Using Machine Learning

Burnup measurement is an important step in material control and accountancy (MC&A) at nuclear reactors, and may be done by examining gamma spectra of fuel samples. Traditional approaches rely on known correlations to specific photopeaks (e.g. 137 Cs) and operate via a standard linear regression method. However, the quality of these regression methods is limited even in the best case, and is significantly poorer at short fuel cool-down times, due to the elevated radiation background by short life-time isotopes, and self-shielding effect of the fuel. For practical operation of pebble bed reactors (PBRs), quick measurements (in minutes) and short cooling times (in hours) are required from a safety and security perspective. We investigated the efficacy and performance of machine learning (ML) methods to predict the burnup of the pebble fuel from full gamma spectra (rather than specific discrete photopeaks) and found a full-spectrum ML approach to far outperform baseline regression predictions in all measurement and cooling conditions - including in operational-like measurement conditions. We also performed model and data ablation experiments to determine the relative performance impact of our ML methods' capacity to model data nonlinearities and the inherent additional information in full spectra. Applying our ML methods, we found a number of surprising results, including improved accuracy at shorter fuel cooling times (the opposite of the norm), remarkable robustness to spectrum compression (via rebinning), and competitive burnup predictions even when using background signal only (i.e. explicitly omitting known isotope photopeaks).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Detection of Isotopes in Urban Source Search Low-Count Gamma Spectra Using Hopfield Neural Networks

Source search campaigns involve measurements of background gamma-ray spectra with a mobile detector-spectrometer traveling along arbitrarily chosen trajectories over a wide screening area. Radiation counts are typically measured with a tellurium-doped sodium iodide [NaI(Tl)] scintillator detector-spectrometer in short acquisition intervals, usually 1 s. The objective is to detect orphan isotopes with half-lives shorter than those of the isotopes in the natural background. In principle, radioisotopes can be identified by their unique gamma emission spectrum. However, detecting orphan isotopes in search data is challenging because low counts measured in short acquisition intervals result in incomplete spectral lines. In this study, we investigate the performance of a Hopfield neural network (HNN) that implements an auto-associative memory for the detection of isotopes of interest in an urban search campaign. The HNN is trained on one example of gamma spectra with well-resolved spectral lines of each isotope of interest. During testing, the auto-associative memory implementation of the HNN processes low-count gamma spectra with partially complete isotopic lines by matching incoming measurements to the closest one of its memory-stored patterns. The testing database consisted of almost 10 000 1-s gamma spectra, including measurements of orphan isotopes 137 Cs, 241 Am, and 131 I, obtained during two urban search surveys with a NaI(Tl) detector. The performance of the HNN detection algorithm was evaluated using precision, recall, and F1 scores, and benchmarked with a multiple linear regression (MLR) identification algorithm. In conclusion, the test results demonstrate that HNN outperforms MLR in the detection of all the isotopes of interest.

Auto associative memory↗
DOE OSTI2025

In-Field Testing of Components for Feedback and Control of the ITER Disruption Mitigation System

Here, the shattered pellet injection (SPI) method has been chosen as the disruption mitigation system (DMS) for ITER. To protect the device from plasma disruptions that cause damaging heat and electromagnetic loads, SPI is used to inject high-Z material into the plasma. The process of SPI utilizes cryogenic cooling to form solid pellets. Pellets are accelerated down a barrel and into an angled surface, causing the pellet to shatter prior to entering the tokamak chamber. For the DMS to function reliably, the 27 separate shattered pellet injectors planned for ITER must rely on many components to provide accurate feedback data and for control functions. Each component in the DMS is exposed to an elevated background magnetic field depending on its placement and proximity to the plasma chamber. A Helmholtz coil test stand that is operated at Oak Ridge National Laboratory was utilized to test the components in relevant background field levels to assess component performance. This paper details the test design and results for in-field component operation for a variety of components. This list includes the following components: two different network switches for camera connectivity, a VAT fast shutter valve intended to reduce the flow of SPI propellant gas into the torus, a solenoid control valve intended for use in the pellet formation process, pressure/vacuum switches to be used for feedback and control, a printed circuit board piezo pressure sensor to be used to measure breech pressure, and various relays for the high-voltage pulsed power supply used to drive the SPI propellant valve.

Disruption mitigation↗
DOE OSTI2020

Oscillon preheating in full general relativity

Abstract Oscillons are dense nonperturbative objects that may be copiously produced in the preheating period after inflation. Oscillon preheatings are usually simulated with nonlinear matter interactions but in a rigid FLRW background, without taking into account the gravitational backreactions. We investigate the oscillon preheating scenario in full general relativity with a full numerical relativity scheme, and compare the general-relativistic simulations with the traditional ones done in an FLRW background. We find that in certain parameter regions the general-relativistic corrections are significant, producing more and denser oscillons, and can be strong enough to collapse the oscillons to black holes.

Astronomy & Astrophysics↗
DOE OSTI2023

Gauge-invariant gravitational waves in matter beyond linearized gravity

Modeling the propagation of gravitational waves (GWs) in media other than vacuum is complicated by the gauge freedom of linearized gravity in that, once nonlinearities are taken into consideration, gauge artifacts can cause spurious acceleration of the matter. To eliminate these artifacts, we propose how to keep the theory of dispersive GWs gauge-invariant beyond the linear approximation and, in particular, obtain an unambiguous gauge-invariant expression for the energy–momentum of a GW in a dispersive medium. Using analytic tools from plasma physics, we propose an exactly gauge-invariant 'quasilinear' theory, in which GWs are governed by linear equations and also affect the background metric on scales large compared to their wavelength. As a corollary, the gauge-invariant geometrical optics of linear dispersive GWs in a general background is formulated. As an example, we show how the well-known properties of vacuum GWs are naturally and concisely yielded by our theory in a manifestly gauge-invariant form. We also show how the gauge invariance can be maintained within a given accuracy to an arbitrary order in the GW amplitude. These results are intended to form a physically meaningful framework for studying dispersive GWs in matter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗