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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Vulnerability Detection Methodology for a Digital Signal Processor Micro-Controller at Edge Level Distributed Energy Resource Controller

Integration of renewable energy and energy storage based Distributed Energy Resource (DER) assets to the grid has seen an upsurge over the past few decades. Traditionally, energy would be generated at a thermal or nuclear power plant and then transmitted over long distance through the transmission grid and then supply to the customers at the distribution grid. Modern renewable energy based DER assets have brought energy production at the edge of distribution grid, which has made the grid vulnerable to cyber intrusion as the power flow controllers for such DER assets are now distributed across the grid from distribution level to transmission level. This paper discusses the vulnerability posed by such power flow controllers of DER assets and demonstrates a detection methodology for unauthorized access and manipulation of system configuration for Digital Signal Processor based Microcontrollers. Experimental results proving efficacy of the methodology have been shown in paper.

Bhowmik, Pankaj↗
DOE OSTI2021

Online Detection of Low-Quality Synchrophasor Data Considering Frequency Similarity

Here, this letter proposes a new approach for online detection of low-quality synchrophasor data under both normal and event conditions. The proposed approach utilizes the features of synchrophasor data in time and frequency domains to distinguish multiple regional PMU signals and detect low-quality synchrophasor data. It is more effective to detect low-quality data with apparently indistinguishable profiles. Case studies from recorded synchrophasor measurements verify the effectiveness of the proposed approach for detecting low-quality synchrophasor data in frequency, voltage magnitude and voltage angle.

42 ENGINEERING↗
DOE OSTI2021

A Data-Driven Framework for Automated Detection of Aircraft-Generated Signals in Seismic Array Data Using Machine Learning

Abstract Ground motions associated with aircraft overflights can cover a significant portion of the seismic data collected by shallowly emplaced seismometers, such as new nodal and Distributed Acoustic Sensing systems. This article describes the first published framework for automated detection of aircraft on single channel and multichannel seismic data. The seismic data are converted to spectrograms in a sliding time window and classified as aircraft or nonaircraft in each window using a deep convolutional neural network trained with analyst-labeled data. A majority voting scheme is used to convert the output from the sequence of sliding time windows onto a decision time sequence for each channel and to combine the binary classifications on the decision time sequences across multiple channels. Precision, recall, and F-score are used to quantify the detection performance of the algorithm on nodal data using fourfold time-series cross validation. By applying our framework to data from the Sage Brush Flats nodal array in Southern California, we provide a benchmark performance and demonstrate the advantage of using an array of sensors.

Geochemistry & Geophysics↗
DOE OSTI2021

SDSS-IV MaNGA: 3D spin alignment of spiral and S0 galaxies

ABSTRACT We investigate the 3D spin alignment of galaxies with respect to the large-scale filaments using the MaNGA survey. The cosmic web is reconstructed from the Sloan Digital Sky Survey using disperse and the 3D spins of MaNGA galaxies are estimated using the thin disc approximation with integral field spectroscopy kinematics. Late-type spiral galaxies are found to have their spins parallel to the closest filament’s axis. The alignment signal is found to be dominated by low-mass spirals. Spins of S0-type galaxies tend to be oriented preferentially in perpendicular direction with respect to the filament’s axis. This orthogonal orientation is found to be dominated by S0s that show a notable misalignment between their kinematic components of stellar and ionized gas velocity fields and/or by low-mass S0s with lower rotation support compared to their high-mass counterparts. Qualitatively similar results are obtained when splitting galaxies based on the degree of ordered stellar rotation, such that galaxies with high spin magnitude have their spin aligned, and those with low spin magnitude in perpendicular direction to the filaments. In the context of conditional tidal torque theory, these findings suggest that galaxies’ spins retain memory of their larger scale environment. In agreement with measurements from hydrodynamical cosmological simulations, the measured signal at low redshift is weak, yet statistically significant. The dependence of the spin-filament orientation of galaxies on their stellar mass, morphology, and kinematics highlights the importance of sample selection to detect the signal.

Kraljic, Katarina↗
DOE OSTI2024

Acoustoelastic characterization of plates using zero group velocity Lamb modes

Acoustoelasticity, a characteristic of material anharmonicity, gives rise to a link between wave propagation velocity and the stress state in materials. Ultrasonic techniques to monitor this coupling, particularly with high sensitivity and in a noncontact manner, can have widespread application both in the quantification of applied and residual stress and in the characterization of nonlinear material behavior through measurement of higher order elastic constants. Here, we use a laser ultrasonic technique to excite and detect zero group velocity (ZGV) Lamb wave resonances in aluminum plates under uniaxial loading. A laser line source is used to excite these resonances at different orientations with respect to the applied load, and the signals are detected using an interferometer. The effects of stress and source orientation on ZGV resonance frequencies are validated using the theory of acoustoelastic Lamb wave propagation. In addition, a model-based inversion technique is used to extract Murnaghan's third-order elastic constants from measurements of the stress dependence of the first two ZGV modes generated parallel and perpendicular to the applied load. Laser generation and detection of ZGV resonances is shown to be an effective and powerful approach for the noncontact and nondestructive acoustoelastic characterization of elastic waveguides.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electronic noise of a single skyrmion

To enable the practical use of skyrmion-based devices, it is essential to achieve a balance between energy efficiency and thermal stability while also ensuring reliable electrical detection against noise. Understanding how a skyrmion interacts with material disorder and external perturbations is thus essential. Here, we investigate the electronic noise of a single skyrmion under the influence of thermal fluctuations and spin currents in a magnetic thin film. We detect the thermally induced noise with a 1/ƒ $\gamma$ signature in the strong pinning regime but a random telegraph noise in the intermediate pinning regime. Both the thermally dominated and current-induced telegraphlike signals are detected in the weak pinning regime. Our results provide a comprehensive electronic noise picture of a single skyrmion, demonstrating the potential of noise fluctuation as a valuable tool for characterizing the pinning condition of a skyrmion. In conclusion, these insights could also aid in the development of low-noise and reliable skyrmion-based devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Continuous automatic polarization channel stabilization from heterodyne detection of coexisting dim reference signals

Quantum networking continues to encode information in polarization states due to ease and precision. The variable environmental polarization transformations induced by deployed fiber need correction for deployed quantum networking. Here, we present a method for automatic polarization compensation (APC) and demonstrate its performance on a metropolitan quantum network. Designing an APC involves many design decisions as indicated by the diversity of previous solutions in the literature. Our design leverages heterodyne detection of wavelength-multiplexed dim classical references for continuous high-bandwidth polarization measurements used by newly developed multi-axis (non-)linear control algorithm(s) for complete polarization channel stabilization with no downtime. This enables continuous relatively high-bandwidth correction without significant added noise from classical reference signals. We demonstrate the performance of our APC using a variety of classical and quantum characterizations. Finally, we use C-band and L-band APC versions to demonstrate continuous high-fidelity entanglement distribution on a metropolitan quantum network with an average relative fidelity of 0.94 ± 0.03 for over 30 hrs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Projected network performance for multiple isotopes using next-generation xenon monitoring systems

Since about 2000 (Bowyer et al., 1998), radioxenon monitoring systems have been under development and testing for the verification of the Comprehensive Nuclear Test-Ban Treaty (CTBT). Operation of the systems since then has resulted in development of a next-generation of systems that are nearly ready for operational deployment. By 2010, the need to screen out civilian sources was well known (Auer et al., 2010; Saey, 2009), and isotopic ratio approaches were soon considered (Kalinowski et al., 2014) to identify specific sources. New generation systems are expected to improve the ability to verify the absence of nuclear tests by using isotopic ratios when multiple isotopes are detected. In this work, thousands of releases were simulated to compute the global detection probability of 131m Xe, 133m Xe, 133 Xe, and 135 Xe at 39 noble gas systems in the International Monitoring System (IMS) for both current and next-generation systems. Three release scenarios are defined at 1 h, 1 d, and 10 d past a 1 kt TNT equivalent 235U explosion event. Multiple cases using from one part in a million to the complete release of the xenon isotopic activity are evaluated for each scenario. Coverage maps and global integrals comparing current and next-generation monitoring systems are presented showing that next-generation noble gas systems will create measurable improvements in the IMS. The global detection probability for 133 Xe is shown to be strong in all scenarios, but only modestly improved by next-generation equipment. However, the detection probability for 131m Xe and 133m Xe increased to about 50% in different scenarios, providing a second detectable isotope for many events. As anticipated from shorter sampling intervals, the expected number of detecting samples roughly doubled and the expected number of detecting stations rose by approximately 50% for all release scenarios. Thus, it might be anticipated that future events would consist of multiple 133 Xe detections and one or more second isotope detections. In conclusion, signals of this nature should increase detection confidence, tighten release location estimates, improve rejection of civilian signals, and lessen the impacts from individual systems being offline for maintenance or repair reasons.

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

Geophysical Observations of the 2023 September 24 OSIRIS-REx Sample Return Capsule Reentry

Sample return capsules (SRCs) entering Earth's atmosphere at hypervelocity from interplanetary space are a valuable resource for studying meteor phenomena. The 2023 September 24 arrival of the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer SRC provided an unprecedented chance for geophysical observations of a well-characterized source with known parameters, including timing and trajectory. A collaborative effort involving researchers from 16 institutions executed a carefully planned geophysical observational campaign at strategically chosen locations, deploying over 400 ground-based sensors encompassing infrasound, seismic, distributed acoustic sensing, and Global Positioning System technologies. Additionally, balloons equipped with infrasound sensors were launched to capture signals at higher altitudes. This campaign (the largest of its kind so far) yielded a wealth of invaluable data anticipated to fuel scientific inquiry for years to come. The success of the observational campaign is evidenced by the near-universal detection of signals across instruments, both proximal and distal. This paper presents a comprehensive overview of the collective scientific effort, field deployment, and preliminary findings. The early findings have the potential to inform future space missions and terrestrial campaigns, contributing to our understanding of meteoroid interactions with planetary atmospheres. Furthermore, the data set collected during this campaign will improve entry and propagation models and augment the study of atmospheric dynamics and shock phenomena generated by meteoroids and similar sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Temporal Convolutional Network Using Empirical Mode Decomposition to Detect Faults in Grid Connected Systems

Grid-connected power electronic systems require timely and reliable fault detection to prevent equipment damage and reduce downtime. This paper presents a forecasting-based anomaly detection pipeline that decomposes voltage and current measurements into intrinsic mode functions (IMFs) using empirical mode decomposition (EMD), then trains a causal temporal convolutional network (TCN) on normal-operation IMF data to predict short-horizon future dynamics. Deviations between forecasts and observations are summarized as reliability-weighted residual scores and thresholded per sensor using robust statistics with temporal persistence constraints to suppress false positives. To reduce runtime, EMD is performed on downsampled signals for detection, while raw-rate EMD is applied only within a short region of interest for high-frequency interpretability near detected events. Results on a simulated grid-connected converter system demonstrate that IMF-domain forecasting improves anomaly separability relative to raw-signal forecasting and provides interpretable evidence of faults across decomposition channels.

Sutton, Elizabeth [ORNL] (ORCID:0009000078885935)↗
DOE OSTI2026

Searches for Light Dark Matter and Evidence of Coherent Elastic Neutrino-Nucleus Scattering of Solar Neutrinos with the LUX-ZEPLIN (LZ) Experiment

We present searches for light dark matter (DM) with masses 3–9 GeV/𝑐 2 in the presence of coherent elastic neutrino-nucleus scattering (CE⁢𝜈⁢NS) from 8 B solar neutrinos with the LUX-ZEPLIN experiment. This analysis uses a 5.7 tonne-yr exposure with data collected between March 2023 and April 2025. In an energy range spanning 1–6 keV, we report no significant excess of events attributable to dark matter nuclear recoils, but we observe a significant signal from 8 B CE ⁢𝜈 ⁢NS interactions that is consistent with expectation. We set world-leading limits on spin-independent and spin-dependent-neutron DM-nucleon interactions for masses down to 5 GeV/𝑐 2 . In the no-dark-matter scenario, we observe a signal consistent with 8 B CE⁢ 𝜈 ⁢NS events, corresponding to a 4.5⁢𝜎 statistical significance. This is the most significant evidence of 8 B CE 𝜈 ⁢NS interactions and is enabled by robust background modeling and mitigation techniques. This demonstrates LZ’s ability to detect rare signals at keV-scale energies.

Dark matter detectors↗
DOE OSTI2025

DUNE Photon Detection System

The Deep Underground Neutrino Experiment (DUNE) aims to provide a broad physics program primarily addressed to probing CP violation in the neutrino sector and identifying the neutrino mass hierarchy. The search for proton decay, the observation of supernova neutrino bursts, and the investigation of solar neutrinos represent other additional goals of DUNE experiment, which can be enhanced by the use and the high performances of the Photon Detection System (PDS). Using the technology based on liquid argon Time Projection Chamber (LArTPC), the experiment plans to observe neutrino interactions inside detectors located 1300 km away from the Long Baseline Neutrino Facility (LBNF) at Fermi National Accelerator Laboratory (FNAL), where the neutrinos are produced. The experiment consists of two main parts, respectively the far and near detectors. The far site will comprise four detector modules. The first module is constituted by a vertical drift single-phase LArTPC, while the second module provides a horizontal drift single-phase LArTPC. The configurations of the other modules are still under definition. Neutrino detection in LArTPCs is achieved by identifying the charge and light generated from its interactions with liquid argon. The wire planes of the instrumented anode and the PDS detect these signals, respectively. The PDS in the first two modules, detailed in the present document, uses a modified version of the so-called ARAPUCA technology, named X-ARAPUCA. This system consisting of a highly reflecting box with an entrance window made by dichroic filters and wavelength shifters, creates a trap to detect the VUV (128 nm) scintillation photons. The X-ARAPUCA of the first module is called Supercell, and it has dimensions of 488×100 mm 2 , while Megacell is the second module version, with an active area of 60×60 cm 2 . This latter configuration also represents a significant technological advancement. Since half of the modules are placed on the cathode at high voltage, they are powered and read out using innovative power-over-fiber (PoF) and signal-over-fiber (SoF) technologies. Meanwhile, the other half are installed in a membrane behind the field cage, with a total transparency of around 70%.

Neutrino detectors↗
DOE OSTI2021

Cherenkov Telescope Array sensitivity to the putative millisecond pulsar population responsible for the Galactic Centre excess

ABSTRACT The leading explanation of the Fermi Galactic Centre γ-ray excess is the extended emission from an unresolved population of millisecond pulsars (MSPs) in the Galactic bulge. Such a population would, along with the prompt γ-rays, also inject large quantities of electrons/positrons (e±) into the interstellar medium. These e± could potentially inverse-Compton (IC) scatter ambient photons into γ-rays that fall within the sensitivity range of the upcoming Cherenkov Telescope Array (CTA). In this article, we examine the detection potential of CTA to this signature by making a realistic estimation of the systematic uncertainties on the Galactic diffuse emission model at TeV-scale γ-ray energies. We forecast that, in the event that e± injection spectra are harder than E−2, CTA has the potential to robustly discover the IC signature of a putative Galactic bulge MSP population sufficient to explain the Galactic Centre excess for e± injection efficiencies in the range of ≈2.9–74.1 per cent, or higher, depending on the level of mismodelling of the Galactic diffuse emission components. On the other hand, for spectra softer than E−2.5, a reliable CTA detection would require an unphysically large e± injection efficiency of ${\gtrsim} 158{{\ \rm per\ cent}}$. However, even this pessimistic conclusion may be avoided in the plausible event that MSP observational and/or modelling uncertainties can be reduced. We further find that, in the event that an IC signal were detected, CTA can successfully discriminate between an MSP and a dark matter origin for the radiating e±.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Optimizing Traffic Signal Control to Enhance Transportation Efficiency and Maximize Pedestrian Benefits in the Road Network

Increasing urban mobility requirements demand efficient transportation system strategies for both vehicular and pedestrian movement. This study enhances the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) approach, originally tailored for vehicular traffic signal timing, to incorporate pedestrian traffic dynamics. The improved algorithm considers crucial metrics such as Eco_PI, assesses vehicle fuel consumption by factoring in stops and delays, and addresses pedestrian waiting time, crucial for system efficiency while acknowledging driver waiting time impact. Utilizing Digital Twin simulation along the MLK Smart Corridor in Chattanooga, Tennessee, the algorithm's performance is compared for various pedestrian control scenarios. To evaluate the effectiveness of DGMARL, this study compared DGMARL-enabled signal management with automated pedestrian traffic detection and an actuated signal management system (real-word baseline) with pedestrian recall, which predetermingly enforces a pedestrian phase every cycle. Findings indicate substantial improvements with DGMARL, showing a 28.29% enhancement in vehicle Eco_PI, a 60.55 % reduction in pedestrian waiting time, and a 55.74% decrease in driver stop delay, on average, compared to the baseline actuated signal timing plan.

Kumarasamy, Vijayalakshmi K [The University of Ten↗
DOE OSTI2022

Preliminary Transfer Learning Results on Israel Data

In this preliminary report, we use publicly available data recorded in Israel to test and expand upon existing machine learning models for seismic-phase detection and arrival-time measurement. We downloaded 3-years of waveform data from Geofon, and cross referenced the waveforms to Israel bulletin picks (Schardong et al., 2021). The initial results using existing models directly generated ubiquitous false detections and that obscured detections of signals that are clearly visible in the waveforms. However, after applying transfer learning (tuning parameters in the existing ML models using one year of the Israel-network data), the results are encouraging, i.e. ML picks agree within a few tenths of a second with bulletin picks and the number of false detections is greatly reduced. The bulletin picks are a good starting point, but they cannot be considered ground-truth. To test potential improvement in picking using ML we would like to relocate the events using the ML picks to see if the events cluster more tightly at known mine locations. However, in order to constrain event locations, we need ML picks for the whole Israeli-Jordanian network, which requires waveforms that are not publicly available.

58 GEOSCIENCES↗
DOE OSTI2026

Electrical readout of topological spin order in ultrathin insulators with small magnetization

Probing magnetic order in insulators with small magnetization is particularly challenging in the ultrathin limit, where magnetometry and diffraction lose sensitivity. Here, in this study, we show that topological spin order with vanishingly small magnetization can be electrically detected through an interfacial topological Hall effect in heavy-metal/magnetic-insulator heterostructures. Using Pt coupled to the canted antiferromagnetic insulator hexagonal LuFe⁢O 3 (h-LuFe⁢O 3 ) we observe an unusually large and robust Hall response arising from the transfer of real-space spin topology across the interface via magnetic proximity effect (MPE). This interfacial signal enables detection of magnetic order in h-LuFe⁢O 3 with an extremely small net magnetization (0.025 𝜇 B /Fe), corresponding to Hall-conductivity-magnetization ratio ≈ 2 V −1 , which is one to two orders of magnitude large than other MPE-induced Hall effects and anomalous Hall effects of conducting magnets. This high sensitivity allows detection of magnetic order in h-LuFe⁢O 3 down to a thickness of only 1.5 unit cells. Our results establish an interfacial Hall-based approach for electrically probing topological spin structures in ultrathin insulators and the related interfaces, enabling access to magnetic order in regimes where conventional probes fail.

Topological Hall Effect↗
DOE OSTI2023

Cycle-by-cycle Delay Estimation at Signalized Intersections by using Machine Learning and Simulated Video Detection Data

Accurate estimation of delay is crucial for efficient traffic signal operations. Estimation of delay in the real-time manner using traditional loop detectors requires advanced detectors (in addition to stop-bar detection). In cases when this detection layout is not in place, delay estimates are approximated with a lower accuracy. Video detection is one of the most frequently deployed detection systems at signalized intersections in recent years. In most cases video detection operates in the same way as traditional inductive loops. However, when coupled with computer vision algorithms, video detection systems could be used to retrieve additional information (e.g., vehicular arrivals and departures) that cannot be taken out from the conventional systems (e.g., long stop-bar loop detectors). Although present for several decades, video detection data were not frequently examined for delay estimation purposes. In this study, we proposed a novel delay estimation model which can be developed with only data from stop-bar video detectors. Relevant data were collected from a simulation model of 11 signalized intersections at downtown Chattanooga, TN and processed to create needed inputs for model development. With the use of multigene genetic programming the authors developed a delay model that outperforms accuracy of multi regression model. Furthermore, authors evaluated the developed model by comparison with the other benchmark delay models, such as HCM and approach delay model. It was found that the developed MGGP delay model outperforms benchmark models for a wide range of traffic and signal operation conditions.

Erdagi, Ismet Goksad↗
DOE OSTI2021

Interfacing Atmospheric Flow Tube to Ion Mobility Spectrometry: FY 2021 Final Report

An atmospheric flow tube (AFT) provides extended ion-molecule reaction times of 2-3 seconds compared to milliseconds in typical mass spectrometers. This results in several orders of magnitude enhanced sensitivity allowing for vapor detection at the parts-per-quadrillion levels when an AFT is coupled to a mass spectrometer (MS). The goal of this project was to demonstrate the feasibility of integrating an AFT ionization source to a more portable ion mobility spectrometer (IMS). This project was successful in integrating AFT to IMS, as shown in Figure ES.1. The PNNL team demonstrated measurable ion signal from an AFT-IMS with a Faraday plate detector. Reasonable ion signals were detectable at low flow rates approaching 1 m/s. This is close to the flow rates used with the AFT-MS, which has demonstrated parts-per-quadrillion vapor detection. Vapor detection enables non-contact detection of a variety of illicit substances for various applications including cargo screening, mail sorting facilities, and checkpoints. With further improvements to enhance detection, AFT-IMS has the potential to allow ultra-trace vapor detection in a more portable device.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗