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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Shape-Based Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron

Spintronic devices based on domain wall (DW) motion through ferromagnetic nanowire tracks have received great interest as components of neuromorphic information processing systems. Prior proposals for spintronic artificial neurons required external stimuli to perform the leaking functionality, one of the three fundamental functions of a leaky integrate-and-fire (LIF) neuron. The use of this external magnetic field or electrical current stimulus results in either a decrease in energy efficiency or an increase in fabrication complexity. Here, we modify the shape of previously demonstrated three-terminal magnetic tunnel junction neurons to perform the leaking operation without any external stimuli. The trapezoidal structure causes a shape-based DW drift, thus intrinsically providing the leaking functionality with no hardware cost. This LIF neuron, thus, promises to advance the development of spintronic neural network crossbar arrays.

42 ENGINEERING↗
DOE OSTI2021

Anomaly Detection, Localization and Classification using Drifting Synchrophasor Data Streams

With ongoing automation and digitization of the electric power system, several Phasor Measurement Units(PMUs) have been deployed for monitoring and control. PMU data can have multiple anomalies, and many of the researchers in the past have concentrated on training machine/deep learning algorithms offline for anomaly detection over PMU data (i.e., not in real time). These machine/deep learning algorithms, when trained offline on a sample rather than a population of the dataset, fail to consider the dynamic behavior of the power grid in real-time, resulting in low accuracy. Considering the dynamic behavior of the power grid (e.g., change in load, generation, distributed energy resources (DERs) switching, network, controls), the definition of data anomalies varies in time and requires online training. A fundamental challenge is to enable online (i.e., real-time) training of machine/deep learning algorithms for anomaly detection over streaming PMU data. While machine/deep learning is often desirable to manage data streams, training a deep learning algorithm over streaming PMU data is nontrivial due to changes in data statistics caused by dynamic streaming data. This paper proposes PMUNET: a novel device-level deep learning-based data-driven approach for anomaly detection, localization, and classification over streaming PMU data, using online learning and multivariate data-drift detection algorithm .Two variants of PMUNET, Dynamic data Change Driven Learning (DCDL) and Continuity Driven Learning (CDL), are proposed and compared. DCDL aims to train the deep learning algorithm whenever the definition of anomaly changes due to the power grid dynamics. On the other hand, CDL continuously trains the deep learning algorithm over the PMU data-stream. The experimental results verify that DCDL outperforms CDL and other efficient anomaly detection methods over multiple events such as faults and load/ generator/capacitor/DERs variations/switching for IEEE 14 and 39 Bus test system as well as real PMU industrial data. The result verifies that DCDL variant of PMUNET improves over existing approach with a gain of 2% - 10% in terms of accuracy, false-positive rate, and false-negative rate.

adversarial deep learning↗
DOE OSTI2018

The impacts of four potential bioenergy crops on soil carbon dynamics as shown by biomarker analyses and DRIFT spectroscopy

Abstract Perennial bioenergy crops accumulate carbon (C) in soils through minimally disturbing management practices and large root inputs, but the mechanisms of microbial control over C dynamics under bioenergy crops have not been clarified. Root‐derived C inputs affect both soil microbial contribution to and degradation of soil organic matter resulting in differing soil organic carbon ( SOC ) concentrations, storage, and stabilities under different vegetation regimes. Here, we measured biomarker amino sugars and neutral sugars and used diffuse reflectance mid‐infrared Fourier transform spectroscopy ( DRIFTS ) to explore microbial C contributions, degradation ability, and SOC stability, respectively, under four potential bioenergy crops, M .× giganteus ( Miscanthus × giganteus ), switchgrass ( Panicum virgatum L .), a mixed prairie, and a maize ( Zea mays L .)–maize–soybean ( Glycine max(L.) Merr .) ( MMS ) rotation over six growing seasons. Our results showed that SOC concentration (g/kg) increased by 10.6% in mixed prairie over the duration of this experiment and SOC storage (Mg/ha) increased by 17.0% and 15.6% in switchgrass and mixed prairie, respectively. Conversion of row crops to perennial grasses maintained SOC stability and increased bacterial residue contribution to SOC in M .× giganteus and switchgrass by 20.0% and 15.0%, respectively, after 6 years. Degradation of microbe‐derived labile SOC was increased in M .× giganteus, and degradation of both labile and stable SOC increased in MMS rotation. These results demonstrate that microbial communities under perennial grasses maintained SOC quality, while SOC quantity increased under switchgrass and mixed prairie. Annual MMS rotation displayed decreases in aspects of SOC quality without changes in SOC quantity. These findings have implications for understanding microbial control over soil C quantity and quality under land‐use shift from annual to perennial bioenergy cropping systems.

09 BIOMASS FUELS↗
DOE OSTI2015

Use of cluster counting technique for particle identification in a drift chamber with the cathode strip readout

The possibility of using the clusters counting technique for particle identification in a drift chamber with the cathode strip readout is experimentally investigated. Results of counting of primary ionization clusters on a relativistic particle track, as well as results of computer simulation of pion, kaon, and proton identification in the momentum range of 1–8 GeV/c, are presented.

Berdnikov, Vladimir V.↗
DOE OSTI2018

On the Possibility of the Precise Test of Interatomic Interaction Potentials Using the Effect of Anomalous Light-Induced Drift

The spectral features of the velocity of light-induced drift (LID) of lithium atoms in a neon buffer gas have been theoretically studied using four known ab initio calculated interatomic interaction potentials for the Li–Ne system of colliding particles. The calculations with each of these four potentials predict a strong temperature dependence of the spectral shape of the LID signal of Li atoms in the Ne atmosphere in various temperature intervals. The results allow the high-precision test of the interatomic interaction potentials in experiments on anomalous LID.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Dynamic characteristics of 4H-SiC drift step recovery diodes

The dynamic characteristics of 4H-SiC p{sup +}–p–n{sub 0}–n{sup +} diodes are experimentally studied in the pulsed modes characteristic of the operation of drift step recovery diodes (DSRD-mode). The effect of the subnanosecond termination of the reverse current maintained by electron-hole plasma preliminarily pumped by a forward current pulse is analyzed in detail. The influence exerted on the DSRD effect by the amplitude of reverse-voltage pulses, the amplitude and duration of forward-current pulses, and the time delay between the forward and reverse pulses is demonstrated and accounted for.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Features of the Upsurge in Drift Velocity of Electrons in DA-pHEMT

A simple phenomenological model for estimating the upsurge in drift velocity of electrons in transistor heterostructures is proposed. This model is based on a self-consistent solution of Schrödinger and Poisson equations and the hydrodynamic system of equations of energy and momentum conservation. It is demonstrated that the conditions in the layer channel of DA-pHEMT structures with additional potential barriers, which are produced by donor–acceptor doping and enhance the localization of hot electrons, are even more conducive to reducing the time of flight of electrons under the gate than those established in heterostructures with deeper quantum wells produced by increasing the conduction band offset at the heterojunction interface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Reconstruction of atmospheric neutrinos in DUNE’s horizontal-drift far-detector module

This paper reports on the capabilities in reconstructing and identifying atmospheric neutrino interactions in one of the Deep Underground Neutrino Experiment’s (DUNE) far detector modules, a liquid argon time projection chamber (LArTPC) with horizontal drift (FD-HD) of ionization electrons. The reconstruction is based upon the workflow developed for DUNE’s long-baseline oscillation analysis, with some necessary machine-learning models’ retraining and the addition of features relevant only to atmospheric neutrinos such as the neutrino direction reconstruction. Where relevant, the impact of the detection of the charged particles of the hadronic system is emphasized, and comparisons are carried out between the case when lepton-only information is considered in the reconstruction (as is the case for many neutrino oscillation experiments), versus when all particles identified in the LArTPC were included. Three neutrino direction reconstruction methods have been developed and studied for the atmospheric analyses: using lepton-only information, using all reconstructed particles, and using only correlations from reconstructed hits. The results indicate that incorporating more than just lepton information significantly improves the resolution of both neutrino direction and energy reconstruction. The angle reconstruction algorithms developed in this work result in no strong dependence on particle direction for reconstruction efficiencies or neutrino flavor identification. This comprehensive review of the reconstruction of atmospheric neutrinos in DUNE’s FD-HD LArTPC is the first step towards developing a first neutrino oscillation sensitivity analysis, which will ready DUNE for its first measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Parametric dependencies of resonant layer responses across linear, two-fluid, drift-MHD regimes

Non-axisymmetric magnetic fields arising in a tokamak either by external or internal perturbations can induce complex non-ideal MHD responses in their resonant surfaces while remaining ideally evolved elsewhere. This layer response can be characterized in a linear regime by a single parameter called the inner-layer Delta, which enables outer-layer matching and the prediction of torque balance to non-linear island regimes. Here, we follow strictly one of the most comprehensive analytic treatments including two-fluid and drift MHD effects and keep the fidelity of the formulation by incorporating the numerical method based on the Riccati transformation when quantifying the inner-layer Delta. The proposed scheme reproduces not only the predicted responses in essentially all asymptotic regimes but also with continuous transitions as well as improved accuracies. In particular, the Delta variations across the inertial regimes with viscous or semi-collisional effects have been further resolved, in comparison with additional analytic solutions. The results imply greater shielding of the electromagnetic torque at the layer than what would be expected by earlier work when the viscous or semi-collisional effects can compete against the inertial effects, and also due to the intermediate regulation by kinetic Alfven wave resonances as rotation slows down. These are important features that can alter the nonaxisymmetric plasma responses including the field penetration by external fields or island seeding process in rotating tokamak plasmas.

MHD instability↗
DOE OSTI2018

IMS Drift Time Aligner

This program processes IMS data in a UIMF file to align all frames to a base frame, adjusting the observed drift times of each frame to align with the base frame.

Monroe, Matthew↗
DOE OSTI2024

Steric Sea Level Rise and Relationships with Model Drift and Water Mass Representation in GFDL CM4 and ESM4

Abstract Density-driven steric seawater changes are a leading-order contributor to global mean sea level rise. However, intermodel differences in the magnitude and spatial patterns of steric sea level rise exist at regional scales and often emerge during the spinup and preindustrial control integrations of climate models. Steric sea level results from an eddy-permitting climate model, GFDL CM4, are compared with a lower-resolution counterpart, GFDL-ESM4. The results from both models are examined through basin-scale heat budgets and watermass analysis, and we compare the patterns of ocean heat uptake, redistribution, and sea level differ in ocean-only [i.e., Ocean Model Intercomparison Project (OMIP)] and coupled climate configurations. After correcting for model drift, both GFDL CM4 and GFDL-ESM4 simulate nearly equivalent ocean heat content change and global sea level rise during the historical period. However, the GFDL CM4 model exhibits as much as a 40% increase in surface ocean heat uptake in the Southern Ocean and subsequent increases in horizontal export to other ocean basins after bias correction. The results suggest regional differences in the processes governing Southern Ocean heat export, such as the formation of Antarctic Intermediate Water (AAIW), Subpolar Mode Water (SPMW), and gyre transport between the two models, and that sea level changes in these models cannot be fully bias-corrected. Since the process-level differences between the two models are evident in the preindustrial control simulations of both models, these results suggest that the control simulations are important for identifying and correcting sea level–related model biases.

Krasting, John P. [a NOAA/OAR/Geophysical Fluid Dy↗
DOE OSTI2017

A Laser-Based Optical Sensor for Broad-Band Measurements of Building Earthquake Drift

Accurate measurements of the time-dependent deformations of a building during earthquake excitation are essential for interpretation of the dynamic response of the as-built system and for quantifying the seismic demands. Traditional approaches for monitoring building systems are based on strong motion accelerometers mounted at selected elevations. However, accelerometer-based systems do not directly measure the deformations of the structure, and can have significant limitations that make it challenging to correctly measure deformations, particularly permanent deformations from inelastic response. In the study described herein, computational simulations and experiments were combined to evaluate the potential of a new optically based sensor to directly measure time-dependent deformations of a building, including inelastic deformations. The sensor methodology includes corrections for localized structural member rotations and can provide estimates of the absolute accelerations at each floor. A laser-based system utilizing a recently developed discrete diode position sensor (DDPS) is evaluated, and the ability of such a system to measure earthquake induced transient deformations characterized by building interstory drift is demonstrated.

58 GEOSCIENCES↗
DOE OSTI2015

High level tritiated water monitoring by Bremsstrahlung counting using a silicon drift detector

The β-ray induced X-ray spectrometry (BIXS) is a promising technique to monitor the tritium concentration in a fuel cycle of a fusion reactor. For in-situ measurements of high level tritiated water by Bremsstrahlung counting, the characteristics of a low-noise silicon drift detector (SDD) have been examined at the Tritium Laboratory Karlsruhe (TLK). In static measurements with constant sample volume and tritium concentration, the Bremsstrahlung spectra of tritiated water samples in a concentration range of 0.02 to 15 MBq/ml have been obtained. The volume has been kept constant at 5 cm{sup 3}. The observed spectra are well above the noise threshold. In addition to X-rays induced by β-rays, the spectra feature X-ray fluorescence peaks of the surrounding materials. No indications of memory effects have been observed. A linear relation between the X-ray intensity and the tritium concentration was obtained and the lower detection limit of the setup has been determined to 1 MBq ml{sup -1}, assessed by the Curie criterion. In addition, the spectra obtained experimentally could be reproduced with high agreement by Monte-Carlo simulations using the GEANT4-tool-kit. It was found that the present detection system is applicable to non-invasive measurements of high-level tritiated water and the SDD is a convenient tool to detect the low energy Bremsstrahlung X-rays. (authors)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Characterizing thermal-induced temporal drift in deployed quantum fiber networks

We study temperature-induced fiber-delay drifts affecting entanglement fidelity in deployed quantum systems. Using field data and simulations, we model timing uncertainties and evaluate their impact on coincidence detection, revealing critical challenges for robust quantum networks.

Alshowkan, Muneer [ORNL] (ORCID:0000000264293450)↗
DOE OSTI2024

Roles of temperature, materials, and domain inversion in high-performance, low-bias-drift thin film lithium niobate blue light modulators

We demonstrate a thin film lithium niobate electro-optic modulator operating at 456 nm with an RF voltage-length product of 0.38 V-cm and a bandwidth of 6.9 GHz. We test the dielectric relaxation of the modulator with sweeps of temperature and optical input power, and compare equivalent modulators with electrode materials of Cr-Au, Ti-Au and Al in terms of bias stability and current-voltage characteristics. We demonstrate bias stability over at least 8 hours with Al devices, and show relationships between drift, I-V characteristics and ferroelectric domain switching.

Celik, Oguz Tolga (ORCID:0000000264542306)↗