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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

High-resolution inelastic x-ray scattering at the high energy density scientific instrument at the European X-Ray Free-Electron Laser

We introduce a setup to measure high-resolution inelastic x-ray scattering at the High Energy Density scientific instrument at the European X-Ray Free-Electron Laser (XFEL). The setup uses the Si (533) reflection in a channel-cut monochromator and three spherical diced analyzer crystals in near-backscattering geometry to reach a high spectral resolution. An energy resolution of 44 meV is demonstrated for the experimental setup, close to the theoretically achievable minimum resolution. The analyzer crystals and detector are mounted on a curved-rail system, allowing quick and reliable changes in scattering angle without breaking vacuum. The entire setup is designed for operation at 10 Hz, the same repetition rate as the high-power lasers available at the instrument and the fundamental repetition rate of the European XFEL. Among other measurements, it is envisioned that this setup will allow studies of the dynamics of highly transient laser generated states of matter.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Upgrades and redesign of the National Ignition Facility’s soft x-ray opacity spectrometer (OpSpec)

The soft x-ray Opacity Spectrometer (OpSpec) used on the National Ignition Facility (NIF) has recently incorporated an elliptically shaped crystal. The original OpSpec used two convex cylindrical crystals for time-integrated measurements of point-projection spectra from 540 to 2100 eV. However, with the convex geometry, the low-energy portion of the spectrum suffered from high backgrounds due to scattered x-rays as well as reflections from alternate crystal planes. An elliptically shaped crystal allows an acceptance aperture at the crossover focus between the crystal and the detector, which reduces background and eliminates nearly all reflections from alternate crystal planes. The current elliptical design is an improvement from the convex cylindrical design but has a usable energy range from 900 to 2100 eV. In addition, OpSpec is currently used on 18 NIF shots/year, in which both crystals are typically damaged beyond reuse, so efficient production of 36 crystals/year is required. Design efforts to improve the existing system focus on mounting reliability, reducing crystal strain to increase survivability between mounting and shot time, and extending the energy range of the instrument down to 520 eV. The elliptical design, results, and future options are presented.

Wallace, M. S. (ORCID:0000000310871216)↗
DOE OSTI2021

Superconducting qubits in a flip-chip architecture

Flip-chip architectures have recently enabled significant scaling-up of multi-qubit circuits and have been used to assemble hybrid quantum systems that combine different substrates, for example, for quantum acoustics experiments. The standard flip-chip method uses superconducting galvanic connections between two substrates, typically implemented using sophisticated indium wafer-bonding systems, which give highly reliable and temperature-cyclable assemblies, but are expensive, somewhat inflexible in design, and require robust substrates that can sustain the large compressive forces required to cold-weld the indium bonds. A much simpler method is to assemble dies using very low-force contacts and air-dried adhesives, although this does not provide a galvanic contact between the dies. In this work, we demonstrate that the latter technique can be used to reliably couple superconducting qubit circuits, in which the qubits are on separate dies, without the need for a galvanic connection. We demonstrate full vector qubit control of each qubit on each of the two dies, with high-fidelity single-shot readout, and further demonstrate entanglement-generating excitation swaps as well as benchmark a controlled-Z entangling gate between the two qubits on the two dies. This exemplifies a simple and inexpensive assembly method for two-plus-one-dimensional quantum circuit integration that supports the use of delicate or unusually shaped substrates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Overview of preparation for the American WAKE ExperimeNt (AWAKEN)

The American WAKE ExperimeNt (AWAKEN) is a multi-institutional field campaign focused on gathering critical observations of wind farm–atmosphere interactions. These interactions are responsible for a large portion of the uncertainty in wind plant modeling tools that are used to represent wind plant performance both prior to construction and during operation and can negatively impact wind energy profitability. The AWAKEN field campaign will provide data for validation, ultimately improving modeling and lowering these uncertainties. The field campaign is designed to address seven testable hypotheses through the analysis of the observations collected by numerous instruments at 13 ground-based locations and on five wind turbines. The location of the field campaign in Northern Oklahoma was chosen to leverage existing observational facilities operated by the U.S. Department of Energy Atmospheric Radiation Measurement program in close proximity to five operating wind plants. The vast majority of the observations from the experiment are publicly available to researchers and industry members worldwide, which the authors hope will advance the state of the science for wind plants and lead to lower cost and increased reliability of wind energy systems.

17 WIND ENERGY↗
DOE OSTI2022

Atomistic measurement and modeling of intrinsic fracture toughness of two-dimensional materials

Quantifying the intrinsic mechanical properties of two-dimensional (2D) materials is essential to predict the long-term reliability of materials and systems in emerging applications ranging from energy to health to next-generation sensors and electronics. Currently, measurements of fracture toughness and identification of associated atomistic mechanisms remain challenging. Herein, we report an integrated experimental–computational framework in which in-situ high-resolution transmission electron microscopy (HRTEM) measurements of the intrinsic fracture energy of monolayer MoS 2 and MoSe 2 are in good agreement with atomistic model predictions based on an accurately parameterized interatomic potential. Changes in crystalline structures at the crack tip and crack edges, as observed in in-situ HRTEM crack extension tests, are properly predicted. Such a good agreement is the result of including large deformation pathways and phase transitions in the parameterization of the inter-atomic potential. The established framework emerges as a robust approach to determine the predictive capabilities of molecular dynamics models employed in the screening of 2D materials, in the spirit of the materials genome initiative. Moreover, it enables device-level predictions with superior accuracy (e.g., fatigue lifetime predictions of electro- and opto-electronic nanodevices).

Zhang, Xu↗
DOE OSTI2024

Analysis of AP1000 Small-Break Loss-of-Coolant Accident Using Reactor Transient Simulator

The Westinghouse Electric Company’s Advanced Passive Reactor (AP1000) is characterized by the incorporation of passive safety systems (PSSs) designed to ensure core cooling during transient events. The assessment of PSSs requires evaluation of their performance through a combination of experiments and simulations employing various thermal-hydraulic codes. In addition, detailed evaluation of PSSs for a specific reactor system transient analysis such as loss-of-coolant-accident analysis supports understanding representative integral effects test facility development and the further evolution model development and assessment process. Developing a reactor system code is a complex and time-consuming process that requires significant engineering expertise and effort. It can take several months to even years to complete in the early stages of reactor system design and analysis. However, this process can be expedited through the use of transient simulator models for similar reactor systems, which can be used for lesson learning and training purposes. This study uses the Personal Computer Transient Analyzer (PCTRAN) code. The main advantage of PCTRAN is its ease of use and ability to run faster than real time. This study presents the results obtained for a small-break loss-of-coolant accident (SBLOCA) for two breaks using the full version (licensed) of PCTRAN. The purpose of this investigation is to evaluate the overall system behavior during the postulated SBLOCA event as well as assess the capability of the PCTRAN code to reproduce the system response during transient events. The obtained results were compared with the Westinghouse NOTRUMP system code. The PCTRAN code proved to be reliable in predicting the qualitative behavior of the system in both transient cases. As for the system response, it was found that it is contingent on the activation time of the PSSs. The differences in reactor coolant system pressure between the two codes were attributed to the critical flow model and simplification of mass and energy balance. Despite PCTRAN’s limitations, it can still provide a reasonable prediction of various reactor parameters such as pressure, mass flow rate, and void fraction during a SBLOCA scenario. It is worth noting that PCTRAN currently employs a bulk approach similar to that of the Modular Accident Analysis Program (MAAP) and MELCOR codes. However, the upcoming version of PCTRAN will include an artificial intelligence–based detection and accident prevention system, as well as different models for different reactor components. Consequently, PCTRAN has the potential to be upgraded to match the system thermal-hydraulic codes of the U.S. Nuclear Regulatory Commission and become more widely used in cybersecurity to safeguard nuclear power plants from cyberattacks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

On the age of Gliese 86

Gliese 86 is a nearby planet hosting a visual binary consisting of a K-type primary, Gl 86 A, and a white dwarf secondary, Gl 86 B. In this work, we present a model atmosphere analysis of the M {sub A} = 0.83 M {sub ☉} primary, whose chemistry unambiguously identifies it as a 10 Gyr old disk star. For the secondary, this gives rise to a progenitor mass M {sub prog} = 1.11 ± 0.05 M {sub ☉}, and—by inference with its local sibling o {sup 2} Eri—a white dwarf mass M {sub B} = 0.49 ± 0.02 M {sub ☉}. The discrepancy with the 2-3 Gyr chromospheric age of Gl 86 A, as first noted by Rocha-Pinto, Castilho and Maciel, is thus most plausibly the result of a former accretion of mass and angular momentum from the distant degenerate. In consequence, this also implies that with respect to shorter-period systems, like Sirius or Procyon, one must expect significant wind accretion when they evolve through the planetary nebula phase, such that the system ages cannot be reliably determined from their currently bright primaries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The end of the MACHO era, revisited: New limits on MACHO masses from halo wide binaries

In order to determine an upper bound for the mass of the massive compact halo objects (MACHOs), we use the halo binaries contained in a recent catalog by Allen and Monroy-Rodríguez. To dynamically model their interactions with massive perturbers, a Monte Carlo simulation is conducted, using an impulsive approximation method and assuming a galactic halo constituted by massive particles of a characteristic mass. The results of such simulations are compared with several subsamples of our improved catalog of candidate halo wide binaries. In accordance with Quinn et al., we also find our results to be very sensitive to the widest binaries. However, our larger sample, together with the fact that we can obtain galactic orbits for 150 of our systems, allows a more reliable estimate of the maximum MACHO mass than that obtained previously. If we employ the entire sample of 211 candidate halo stars we, obtain an upper limit of 112 M{sub ☉}. However, using the 150 binaries in our catalog with computed galactic orbits, we are able to refine our fitting criteria. Thus, for the 100 most halo-like binaries we obtain a maximum MACHO mass of 21-68 M{sub ☉}. Furthermore, we can estimate the dynamical effects of the galactic disk using binary samples that spend progressively shorter times within the disk. By extrapolating the limits obtained for our most reliable—albeit smallest—sample, we find that as the time spent within the disk tends to zero, the upper bound of the MACHO mass tends to less than 5 M{sub ☉}. The non-uniform density of the halo has also been taken into account, but the limit obtained, less than 5 M{sub ☉}, does not differ much from the previous one. Together with microlensing studies that provide lower limits on the MACHO mass, our results essentially exclude the existence of such objects in the galactic halo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Evolving language of pediatric anxiety in electronic health records

Objectives This study aimed to identify and quantify semantic drift (ie, the change in semantic meaning over time) within expert-defined anxiety-related (AR) terminology and compare it to common electronic health record (EHR) vocabulary across longitudinal pediatric clinical notes. Materials and Methods A corpus of pediatric clinical notes from 2009 to 2022 was analyzed using computational methods. Semantic drift for each term was quantified using cosine similarity between annual temporal word embeddings. Contextual meaning was examined through changes in nearest neighbors across years. The Laws of Semantic Change were applied to assess the influence of word frequency and polysemy. Vocabulary terms were categorized as AR or common EHR. Results 98% of AR terminology maintained a cosine similarity between 0.00 and 0.50, indicating moderate semantic stability, whereas 90% of common EHR terms remained between 0.00 and 0.25, showing greater contextual stability overall. Frequent terms exhibited minimal change (Frequency Coefficient = 0.04), whereas highly polysemous or abbreviated terms showed less stability (Polysemy Coefficient = 0.630). AR terminology drifted more slowly than general EHR vocabulary (Type Coefficient = −0.179), further supported by significant year–type interactions (Coef = −0.09 to −0.523). Discussion Although anxiety-related terminology demonstrates slower semantic drift than general EHR vocabulary, subtle contextual shifts still occur that may affect downstream interpretability and retrieval in automated systems. Conclusion Continuous linguistic monitoring and adaptive modeling are essential to maintain semantic fidelity and ensure the long-term reliability of clinical decision support systems as healthcare documentation evolves.

Pediatric anxiety disorders↗
DOE OSTI2025

Open-source library for performance-portable neutrino reaction rates: Application to neutron star mergers

A realistic and detailed description of neutrinos in binary neutron star (BNS) mergers is essential to build reliable models of such systems. To this end, we present bns_nurates, a novel open-source numerical library designed for the efficient on-the-fly computation of neutrino interactions, with particular focus on regimes relevant to BNS mergers. bns_nurates targets a higher level of accuracy and realism in the implementation of commonly employed reactions by accounting for relevant microphysics effects on the interactions, such as weak magnetism and mean field effects. It also includes the contributions of inelastic neutrino scattering off electrons and positrons and (inverse) nucleon decays. Finally, it offers a way to reconstruct the neutrino distribution function in the framework of moment-based transport schemes. As a first application, we compute both energy-dependent and energy-integrated neutrino emissivities and opacities for conditions extracted from a BNS merger simulation with m1 transport scheme. We find some qualitative differences in the results when considering the impact of the additional relevant reactions and of microphysics effects. For example, neutrino-electron/positron scattering reactions are important for the energy exchange of heavy-type neutrinos as they do not undergo semileptonic charged-current processes, when μ± are not accounted for. Moreover, weak magnetism and mean field effects can significantly modify the contribution of β processes for electron-type (anti)neutrinos, increasing at the same time the importance of (inverse) neutron decays. Here, the improved treatment for the reaction rates also modifies the conditions at which neutrinos decouple from matter in the system, potentially affecting their emission spectra.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Convolutional Neural Network-Based Protection-Zone Classification of Faults in Distribution Feeders with Photovoltaics.

Fault detection and isolation is critical for reliable operation of distribution systems. The ride-through requirements for the distributed energy resources (DER), mandated by the IEEE 1547-2018 standard, makes it challenging to use undervoltage (UV) conditions for fault detection. In addition, with low fault current contribution from these inverter-based DERs, the time-overcurrent relays are also less effective. Thus motivated, this paper presents a learning-based approach for fault detection and localization. A convolutional neural network (CNN)-based model is proposed which uses local voltage and current waveforms from DER locations and feeder substations, for training a zonal classifier. The classifier can be adopted into any relay-like device for discriminating between faults originating from different protection zones. The performance of the proposed approach was tested on publicly available test feeders with distributed photovoltaics (PVs).

Fault localization, convolutional neural networks,↗
DOE OSTI2024

Characterizing Interaction Uncertainty in Human-Machine Teams

With the increasing use and adoption of artificial intelligence (AI), the reliability of modern data systems will be driven by a tighter teaming between human experts and intelligent machine teammates. As in the case of human-human teams, the success of human-machine teams will also rely on clear communication about mutual goals and actions. In this paper, we combine related literature from cognitive psychology, human-machine teaming, uncertainty in data analysis, and multi-agent systems to propose a new form of uncertainty: interaction uncertainty for characterizing bidirectional communication in human-machine teams. We map the causes and effects of interaction uncertainty and outline potential ways to mitigate uncertainty for mutual trust in a high-consequence real-world scenario.

uncertainty, data analytics, interaction, trust, h↗
DOE OSTI2023

Fault Detection via Occupation Kernel Principal Component Analysis

Reliable operation of automatic systems is heavily dependent on the ability to detect faults in the underlying dynamics. While traditional model-based methods have been widely used for fault detection, data-driven approaches have garnered increasing attention due to their ease of deployment and minimal need for expert knowledge. In this letter, we present a novel principal component analysis (PCA) method that uses occupation kernels. Occupation kernels result in feature maps that are tailored to the measured data, have inherent noise-robustness due to the use of integration, and can utilize irregularly sampled system trajectories of variable lengths for PCA. The occupation kernel PCA method is used to develop a reconstruction error approach to fault detection and its efficacy is validated using numerical simulations.

42 ENGINEERING↗
DOE OSTI2026

Failure Mode and Effects Analysis (FMEA) for Photovoltaic Inverter

Photovoltaic (PV) inverters are critical yet vulnerable components in modern energy systems, often acting as reliability bottlenecks that increase the levelized cost of energy (LCOE). To address this, this paper presents a comprehensive Failure Mode and Effects Analysis (FMEA) tailored for PV inverters. Leveraging field data and literature, we identify failure-prone components, such as capacitors,, and relays, and prioritize their risks based on quantitative Risk Priority Numbers (RPNs). The analysis reveals that surge-induced MOV short circuits, capacitor degradation, and environmental cooling fan failures dominate the risk profile. These findings provide a targeted framework for reliability improvement, guiding future efforts in predictive diagnostics, design optimization, and accelerated life testing strategies.

14 SOLAR ENERGY↗
DOE OSTI2026

Zero-day Attack Detection in Digital Substations Using In-Context Learning

In this paper, we address the critical challenge of detecting zero-day attacks in digital substations that employ the IEC-61850 communication protocol to ensure the security and reliability of modern power systems. While many heuristic and machine learning (ML)-based methods have been proposed for attack detection in IEC-61850 digital substations, generalization to unknown or zero-day attacks remains a challenge. We propose an approach that leverages the in-context learning ability of transformer architecture, which enables the model to learn from a few examples of a new task without explicit retraining. Our experiments on the IEC-61850 dataset demonstrate that the proposed method achieves more than 87% detection accuracy on zero-day attacks while the existing baselines fail. We believe this work has the potential to enhance the security of digital substations by enabling the effective detection of zero-day attacks.

LIu, Chen-Ching [Virginia Tech] (ORCID:00000002894↗
DOE OSTI2021

Advanced Performance Metrics and their Application to the Sensitivity Analysis for Model Validation and Calibration

High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. In this work, results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Machine Learning-Based Anomaly Detection for Load Forecasting Under Cyberattacks

Accurate load forecasting can create both economic and reliability benefits for power system operators. However, the cyberattack on load forecasting may mislead operators to make unsuitable operational decisions for the electricity delivery. To effectively and accurately detect these cyberattacks, this paper develops a machine learning-based anomaly detection (MLAD) methodology. First, load forecasts provided by neural networks are used to reconstruct the benchmark and scaling data by using the k-means clustering. Second, the cyberattack template is estimated by the naive Bayes classification based on the cumulative distribution function and statistical features of the scaling data. Finally, the dynamic programming is utilized to calculate both the occurrence and parameter of one cyberattack on load forecasting data. Here, a widely used symbolic aggregation approximation method is compared with the developed MLAD method. Numerical simulations on the publicly load data show that the MLAD method can effectively detect cyberattacks for load forecasting data with relatively high accuracy. Also, the robustness of MLAD is verified by thousands of attack scenarios based on Monte Carlo simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A New Design Approach to Mitigating the Effect of Parasitics in Capacitive Wireless Power Transfer Systems for Electric Vehicle Charging

This paper introduces a new design approach to mitigate the effect of parasitic capacitances and achieve high performance in large air-gap capacitive wireless power transfer (WPT) systems for electric vehicle (EV) charging. In a capacitive WPT system for EVs, the vehicle chassis and roadway introduce multiple parasitic capacitances that can overwhelm the coupling capacitance and severely degrade power transfer and efficiency. The proposed approach addresses this challenge by employing split-inductor matching networks, which allow the complex network of parasitic capacitances to be simplified into an equivalent four-capacitance model. The shunt capacitances of this model are directly utilized as the matching network capacitors, hence, absorbing the parasitic capacitances and eliminating the need for discrete high-voltage capacitors. A systematic procedure is developed to accurately measure the equivalent capacitances of the model, enabling the system's performance to be reliably predicted. The proposed approach is used to design two 6.78-MHz 12-cm air-gap prototype capacitive WPT systems with capacitor-free matching networks. The first system transfers up to 590 W using 150-cm 2 square coupling plates and achieves an efficiency of 88.4%. The second prototype system transfers up to 1217 W using 118-cm 2 circular coupling plates, achieving a power transfer density of 51.6 kW/m 2 . The measured output power profiles of the two systems match well with their predicted counterparts, validating the proposed design approach.

33 ADVANCED PROPULSION SYSTEMS↗