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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

GaN/AlGaN 2DEGs in the quantum regime: Magneto-transport and photoluminescence to 60 tesla

Here, using high magnetic fields up to 60 T, we report magneto-transport and photoluminescence (PL) studies of a two-dimensional electron gas (2DEG) in a GaN/AlGaN heterojunction grown by molecular-beam epitaxy. Transport measurements demonstrate that the quantum limit can be exceeded (Landau level filling factor v <1) and show evidence for the v =2/3 fractional quantum Hall state. Simultaneous optical and transport measurements reveal synchronous quantum oscillations of both the PL intensity and the longitudinal resistivity in the integer quantum Hall regime. PL spectra directly reveal the dispersion of occupied Landau levels in the 2DEG and, therefore, the electron mass. These results demonstrate the utility of high (pulsed) magnetic fields for detailed measurements of quantum phenomena in high-density 2DEGs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe)

Recent proliferation of distributed energy sources in distribution or sub-transmission systems necessitates close monitoring of these three-phase power grids which typically operate under unbalanced loading conditions. Unlike the transmission systems where the network equations are commonly based on the positive sequence component models, a detailed three phase model will have to be used in implementing network applications for these systems. In the specific case of the state estimator, where measurement and parameter errors may bias the solution, bad data and parameter error detection algorithms should also be incorporated. Implementing the state estimator and error detection algorithms for three-phase systems impose additional computational burden and modifications to the state estimation code. This paper proposes a practical solution to avoid these issues by using synchronized phasor measurements and modal decoupling. The previously developed parameter error detection algorithm based on the normalized Lagrange multipliers (NLM) test is applied to the measurements independently in each mode in parallel, not only saving CPU time but also avoiding new code development for a three-phase estimator. Different parameter error scenarios are created and tested to verify the effectiveness of the proposed error detection approach.

Khalili, Ramtin↗
DOE OSTI2020

Performance and Wake Characterization of a Model Hydrokinetic Turbine: The Reference Model 1 (RM1) Dual Rotor Tidal Energy Converter

The mechanical power and wake flow field of a 1:40 scale model of the US Department of Energy’s Reference Model 1 (RM1) dual rotor tidal energy converter are characterized in an open-channel flume to evaluate power performance and wake flow recovery. The NACA-63(4)-24 hydrofoil profile in the original RM1 design is replaced with a NACA-4415 profile to minimize the Reynolds dependency of lift and drag characteristics at the test chord Reynolds number. Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADV) aligned with each rotor centerline and the midpoint between the rotor axes. Flow conditions for each case were controlled to maintain a hub height velocity, uhub= 1.04 ms−1, a flow Reynolds number, ReD= 4.4 × 105, and a blade chord length Reynolds number, Rec= 3.1 × 105. Performance was measured for a range of tip-speed ratios by varying rotor angular velocity. Peak power coefficients, CP= 0.48 (right rotor) and CP= 0.43 (left rotor), were observed at a tip speed ratio, λ= 5.1. Vertical velocity profiles collected in the wake of each rotor between 1 and 10 rotor diameters are used to estimate the turbulent flow recovery in the wake, as well as the interaction of the counter-rotating rotor wakes. The observed performance characteristics of the dual rotor configuration in the present study are found to be similar to those for single rotor investigations in other studies. Similarities between dual and single rotor far-wake characteristics are also observed.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

Danovo Energy Solution's presented its paper named: Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events at the 2026 Georgia Tech Fault & Disturbance Analysis Conference. The full paper can be found at OSTI ID# 3169150 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danova Energy Solutions]↗
DOE OSTI2026

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

This paper is the basis for a presentation help at the 2026 Georgia Tech Fault & Disturbance Analysis Conference, which can be found at OSTI # 3168287 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danovo Energy Solutions]↗
DOE OSTI2021

Synchronized Waveforms – A Frontier of Data-Based Power System and Apparatus Monitoring, Protection, and Control

Voltage and current waveforms contain the most authentic and granular information on the behaviors of power systems. In recent years, it has become possible to synchronize waveform data measured from different locations. Thus large-scale coordinated analyses of multiple waveforms over a wide area are within our reach. This development could unleash a set of new concepts, strategies, and tools for monitoring, protecting, and controlling power systems and apparatuses. This paper presents an in-depth review and analysis of the advancements in synchronized waveform data, including measurement devices, data characteristics, use cases, and comparisons with synchrophasor data. Based on the findings, five strategies are proposed to discover and develop synchronized waveform based applications over multiple application areas. The paper also presents three complementary measurement platforms and two data screening algorithms for application implementation. It further discusses committee activities and standard developments useful to explore the full potential of the data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Event Detection and Classification Using Machine Learning Applied to PMU Data for the Western US Power System

Smart grid technology enhances our comprehension and reliability of the power grid, leveraging Phasor Measurement Unit (PMU) data—time-synchronized, high-frequency measurements gathered across the US power grid. This paper employs machine learning techniques to effectively analyze the vast PMU data in Wide Area Monitoring Systems (WAMS) for power grid event detection and classification. Analyzing several months of real-world PMU data, the paper focuses on machine learning for fast, precise event detection and classification, corroborated by utility event logs. Practical challenges like feature extraction, dimensionality reduction, and model selection are addressed. A novel feature yielding improved results is discovered, and a supplementary algorithm for detecting small power grid faults is developed. The final algorithm is validated using a month-long real PMU data set, demonstrating its capability in accurately identifying power grid events in near real-time.

machine learning, event detection, PMU↗
DOE OSTI2024

Curl up with a good B : detecting ultralight dark matter with differential magnetometry

Ultralight dark matter (such as kinetically mixed dark-photon dark matter or axionlike dark matter) can source an oscillating magnetic-field signal at the Earth’s surface, which can be measured by a synchronized array of ground-based magnetometers. The global signal of ultralight dark matter can be robustly predicted for low masses, when the wavelength of the dark matter is larger than the radius of the Earth, $λ_{DM}$ $\gg$ R. However, at higher masses, environmental effects, such as the Schumann resonances, can become relevant, making the global magnetic-field signal B difficult to reliably model. In this work, we show that ∇ × B is robust to global environmental details, and instead only depends on the local dark matter amplitude. We therefore propose to measure the local curl of the magnetic field at the Earth’s surface, as a means for detecting ultralight dark matter with $λ_{DM}$ ≲ R. As this measurement requires vertical gradients, it can be done near a hill/mountain. Our measurement scheme not only allows for a robust prediction, but also acts as a background rejection scheme for external noise sources. We show that our technique can be the most sensitive terrestrial probe of dark-photon dark matter for frequencies 10 Hz ≤ $f_{A'}$ ≤ 1 kHz (corresponding to masses 4 × 10 –14 eV ≤ $m_{A'}$ ≤ 4 × 10 –12 eV). It can also achieve sensitivities to axionlike dark matter comparable to the CAST helioscope, in the same frequency range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Implementation of a laser–neutron pump–probe capability for inelastic neutron scattering

Knowledge about nonequilibrium dynamics in spin systems is of great importance to both fundamental science and technological applications. Inelastic neutron scattering (INS) is an indispensable tool to study spin excitations in complex magnetic materials. However, conventional INS spectrometers currently only perform steady-state measurements and probe averaged properties over many collision events between spin excitations in thermodynamic equilibrium, while the exact picture of re-equilibration of these excitations remains unknown. In this paper, we report on the design and implementation of a time-resolved laser–neutron pump–probe capability at hybrid spectrometer (beamline 14-B) at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory. This capability allows us to excite out-of-equilibrium magnons with a nanosecond pulsed laser source and probe the resulting dynamics using INS. Here, we discussed technical aspects to implement such a capability in a neutron beamline, including choices of suitable neutron instrumentation and material systems, laser excitation scheme, experimental configurations, and relevant firmware and software development to allow for time-synchronized pump–probe measurements. We demonstrated that the laser-induced nonequilibrium structure factor is able to be resolved by INS in a quantum magnet. In conclusion, the method developed in this work will provide SNS with advanced capabilities for performing out-of-equilibrium measurements, opening up an entirely new research direction to study out-of-equilibrium phenomena using neutrons.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Performance Testing and Assessment of Protection Scheme Using Real-Time Hardware-in-the-Loop and IEC 61850 Standard

The main challenge of the microgrid is to design a suitable protection scheme due to the complexity of the architecture of the microgrid. The importance of the proposed protection technique is threefold. First, it presents a co-simulation platform to integrate between a simulated model on power system computer aided design (PSCAD)/real time digital simulator computer aided design (RSCAD) software’s and physical devices schweitzer engineering laboratories (SEL) 421-7 relays to protect the microgrid that includes different resources connected based on inverter interface. Second, it presents a comprehensive hardware/software setup to test the protective relays in a closed loop system and shows how to configure the protective relay’s International Electrotechnical Commission 61850 communications. Third, IEEE 1588 standard is used to provide sub nanoseconds latency between the simulated model that emulated on real time digital simulator (RTDS) and the external devices. Also, the measurement signals are synchronized between RTDS and the external devices using giga-transceiver synchronization card (GTSYNC) interface card and SEL-2488 satellite-synchronized network clock. The results showed that the co-simulation infrastructure introduces a highly dependable design, analysis, and testing environment for cyber and physical data flow in the system. Besides that, the voltages at ac/dc sides and frequency at fault condition were maintained due to the energy storage device contributions at different modes of operation.

42 ENGINEERING↗
DOE OSTI2021

Best Practices for Timing Attack Mitigation

GPS signals play essential roles in the electric subsector by providing precision timing used to synchronize and record measurements from a range of equipment. However, previous research has demonstrated that GPS signals can be spoofed or jammed relatively easily in order to interfere with timing-reliant equipment. This document outlines utility best practices for mitigating against timing attacks in the electric subsector based on an assessment of the difficulty and impact of realistic timing attacks and testing of the effectiveness of technologies capable of mitigating them. This analysis builds on research establishing the vulnerability of GPS-reliant timing equipment to jamming and spoofing by elaborating the difficulty, consequences, and mitigations for timing attacks that adversaries might realistically attempt. While timing attacks are relatively low-cost, low-sophistication, and capable of systemic consequences in the electric subsector, they can be effectively mitigated through well-targeted and diverse mitigations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Synchronized electric meter having an atomic clock

Smart electric meters configured to perform fast, time-synchronized electrical energy measurements at the consumer-level are disclosed herein. In some embodiments, a smart electric meter includes circuitry configured to measure an electrical value at a location of an end user in a power system. The smart electric meter can further include an atomic clock configured to output a timing signal, and a controller configured to receive (a) the measured electrical value from the circuitry and (b) the timing signal from the atomic clock. The controller can further (a) process the electrical value to generate meter data and (b) generate a time tag based on the timing signal. Then, the controller can associate the time tag with the meter data to generate time-tagged meter data.

Min, Liang↗
DOE OSTI2021

In situ characterization of laser-generated melt pools using synchronized ultrasound and high-speed X-ray imaging

Metal additive manufacturing is a fabrication method that forms a part by fusing layers of powder to one another. An energy source, such as a laser, is commonly used to heat the metal powder sufficiently to cause a molten pool to form, which is known as the melt pool. The melt pool can exist in the conduction or the keyhole mode where the material begins to rapidly evaporate. The interaction between the laser and the material is physically complex and difficult to predict or measure. Here, high-speed X-ray imaging was combined with immersion ultrasound to obtain synchronized measurements of stationary laser-generated melt pools. Furthermore, two-dimensional and three-dimensional finite-element simulations were conducted to help explain the ultrasonic response in the experiments. In particular, the time-of-flight and amplitude in pulse-echo configuration were observed to have a linear relationship to the depth of the melt pool. These results are promising for the use of ultrasound to characterize the melt pool behavior and for finite-element simulations to aid in interpretation.

42 ENGINEERING↗
DOE OSTI2021

Pulsar-Calibrated Timing Source for Synchronized Sampling

The Global Positioning System (GPS) is critical to the real-time synchronized sampling of phasor measurement units (PMUs). Unfortunately, GPS signals are occasionally unstable due to several factors such as weak satellite signal and GPS spoofing, thereby leaving the PMU with a degraded sampling performance. In this letter, a novel Pulsar-calibrated Timing Source (PTS) is proposed as the alternative timing source for synchronized sampling. Further, the PTS can generate the timing signal with a 1 μs drift error within 91 holdover minutes to ensure continuity of sampling accuracy. Experimental tests are conducted and the results reveal the reliability and accuracy of the PTS for PMU synchronization.

42 ENGINEERING↗
DOE OSTI2023

Global droughts connected by linkages between drought hubs

Abstract Quantifying the spatial and interconnected structure of regional to continental scale droughts is one of the unsolved global hydrology problems, which is important for understanding the looming risk of mega-scale droughts and the resulting water and food scarcity and their cascading impact on the worldwide economy. Using a Complex Network analysis, this study explores the topological characteristics of global drought events based on the self-calibrated Palmer Drought Severity Index. Event Synchronization is used to measure the strength of association between the onset of droughts at different spatial locations within the time lag of 1-3 months. The network coefficients derived from the synchronization network indicate a highly heterogeneous connectivity structure underlying global drought events. Drought hotspot regions such as Southern Europe, Northeast Brazil, Australia, and Northwest USA behave as drought hubs that synchronize regionally and with other hubs at inter-continental or even inter-hemispheric scale. This observed affinity among drought hubs is equivalent to the ‘rich-club phenomenon’ in Network Theory, where ‘rich’ nodes (here, drought hubs) are tightly interconnected to form a club, implicating the possibility of simultaneous large-scale droughts over multiple continents.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Asynchronous x-ray multiprobe data acquisition for x-ray transient absorption spectroscopy

Laser pump X-ray Transient Absorption (XTA) spectroscopy offers unique insights into photochemical and photophysical phenomena. X-ray Multiprobe data acquisition (XMP DAQ) is a technique that acquires XTA spectra at thousands of pump-probe time delays in a single measurement, producing highly self-consistent XTA spectral dynamics. In this work, we report two new XTA data acquisition techniques that leverage the high performance of XMP DAQ in combination with High Repetition Rate (HRR) laser excitation: HRR-XMP and Asynchronous X-ray Multiprobe (AXMP). HRR-XMP uses a laser repetition rate up to 200 times higher than previous implementations of XMP DAQ and proportionally increases the data collection efficiency at each time delay. This allows HRR-XMP to acquire more high-quality XTA data in less time. AXMP uses a frequency mismatch between the laser and x-ray pulses to acquire XTA data at a flexibly defined set of pump-probe time delays with a spacing down to a few picoseconds. AXMP introduces a novel pump-probe synchronization concept that acquires data in clusters of time delays. Further, the temporally inhomogeneous distribution of acquired data improves the attainable signal statistics at early times, making the AXMP synchronization concept useful for measuring sub-nanosecond dynamics with photon-starved techniques like XTA. In this paper, we demonstrate HRR-XMP and AXMP by measuring the laser-induced spectral dynamics of dilute aqueous solutions of Fe(CN) 6 4₋ and [Fe II (bpy) 3 ] 2+ (bpy: 2,2'-bipyridine), respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Cause identification of electromagnetic transient events using spatiotemporal feature learning

This paper presents a spatiotemporal feature learning method for cause identification of electromagnetic transient events in power grids. The proposed method is formulated based on the availability of time-synchronized high-frequency measurements and using the convolutional neural network as the spatiotemporal feature representation along with softmax function for the classification. Despite the existing threshold-based, or energy-based events analysis methods, such as support vector machine autoencoder, and tapered multi-layer perceptron neural network, the proposed feature learning is carried out with respect to both time and space. The effectiveness of the proposed feature learning and the subsequent cause identification is validated through the Electromagnetic Transients Program (EMTP) simulation of different events such as line energization, capacitor bank energization, lightning, fault, and high-impedance fault in the IEEE 30-bus, and the real-time digital simulation of the Western System Coordinating Council (WSCC) 9-bus system.

42 ENGINEERING↗