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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Experimental Verification of Ocean Bounced GPS Signals and Analysis of their Application to Ionospheric Corrections for Satellite Altimetry

An algorithm is presented which uses observations of Global Positioning System (GPS) signals reflected from the ocean surface and acquired by a GPS receiver onboard an altimetric satellite to compute the ionospheric delay present in the altimeter measurement. This eliminates the requirement for a dual frequency altimeter for many Earth observing missions. A ground-based experiment is described which confirms the presence of these ocean-bounced signals and demonstrates the potential for altimeter ionospheric correction at the centimeter level.

Axelrad, P.↗
DOE OSTI2021

LL18-Signal Analysis-NDD2Ad (Final Report)

Under favorable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially-distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection, and scaling with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning, and possible application to studies of repeating events in induced, volcanic, and glacial seismicity. Our results place limits on the widely-held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗
NASA NTRS1991

An evaluation of HEMT potential for millimeter-wave signal sources using interpolation and harmonic balance techniques

A large-signal analysis method based on an harmonic balance technique and a 2-D cubic spline interpolation function has been developed and applied to the prediction of InP-based HEMT oscillator performance for frequencies extending up to the submillimeter-wave range. The large-signal analysis method uses a limited number of DC and small-signal S-parameter data and allows the accurate characterization of HEMT large-signal behavior. The method has been validated experimentally using load-pull measurement. Oscillation frequency, power performance, and load requirements are discussed, with an operation capability of 300 GHz predicted using state-of-the-art devices (fmax is approximately equal to 450 GHz).

Kwon, Youngwoo↗
NASA NTRS1990

Automated eddy current analysis of materials

This research effort focused on the use of eddy current techniques for characterizing flaws in graphite-based filament-wound cylindrical structures. A major emphasis was on incorporating artificial intelligence techniques into the signal analysis portion of the inspection process. Developing an eddy current scanning system using a commercial robot for inspecting graphite structures (and others) has been a goal in the overall concept and is essential for the final implementation for expert system interpretation. Manual scans, as performed in the preliminary work here, do not provide sufficiently reproducible eddy current signatures to be easily built into a real time expert system. The expert systems approach to eddy current signal analysis requires that a suitable knowledge base exist in which correct decisions as to the nature of the flaw can be performed. In eddy current or any other expert systems used to analyze signals in real time in a production environment, it is important to simplify computational procedures as much as possible. For that reason, we have chosen to use the measured resistance and reactance values for the preliminary aspects of this work. A simple computation, such as phase angle of the signal, is certainly within the real time processing capability of the computer system. In the work described here, there is a balance between physical measurements and finite element calculations of those measurements. The goal is to evolve into the most cost effective procedures for maintaining the correctness of the knowledge base.

Workman, Gary L.↗
DOE OSTI2024

Holistic Small-Signal Stability Analysis for Large-Scale Inverter-Intensive Power Systems with Coupled and Full-Order Dynamics from Control Systems and Power Networks

The increasing penetration of inverter-based resources (IBRs) into the existing power systems introduces tremendous benefits for enhanced sustainability but also poses inevitable challenges in terms of insufficient inertia, potential instability, and complex network dynamics, among others. However, the additional coupling introduced by the interactions among gridfollowing (GFL) and grid-forming (GFM) IBRs and the other components (i.e., synchronous generators [SGs], loads, and network, etc.) has not been clearly explored. A holistic, scalable, and quantitative stability analysis framework with the control systems and power networks is still missing. Here, in this paper, to fill in the technical gaps, a holistic small-signal model of the entire system with both rotating generation units and IBRs is established. An extended power flow model with operation dynamics from both generator control schemes and power networks is proposed to provide the varying steady-state operating points for small-signal modeling. The proposed method is compared with MATLAB solvers, and the results show that the proposed approach has a minimum calculation time, which can be less than 12 seconds for a large-scale power system with up to 2,000 buses. Furthermore, a quantitative method is developed to identify the impacts of IBRs on system performance with emphases on the potential stability issues with GFL IBRs, additional benefits of employing GFM IBRs, the feasibility of replacing SGs with GFM IBRs, and the impact of penetration level of different kinds of generation units. Finally, a field island power system is used to verify the proposed approach, and hardware-in-the-loop (HIL) tests are provided to further demonstrate the effectiveness of the proposed analysis.

14 SOLAR ENERGY↗
NASA NTRS1991

Automated eddy current analysis of materials

The use of eddy current techniques for characterizing flaws in graphite-based filament-wound cylindrical structures is described. A major emphasis was also placed upon incorporating artificial intelligence techniques into the signal analysis portion of the inspection process. Developing an eddy current scanning system using a commercial robot for inspecting graphite structures (and others) was a goal in the overall concept and is essential for the final implementation for the expert systems interpretation. Manual scans, as performed in the preliminary work here, do not provide sufficiently reproducible eddy current signatures to be easily built into a real time expert system. The expert systems approach to eddy current signal analysis requires that a suitable knowledge base exist in which correct decisions as to the nature of a flaw can be performed. A robotic workcell using eddy current transducers for the inspection of carbon filament materials with improved sensitivity was developed. Improved coupling efficiencies achieved with the E-probes and horseshoe probes are exceptional for graphite fibers. The eddy current supervisory system and expert system was partially developed on a MacIvory system. Continued utilization of finite element models for predetermining eddy current signals was shown to be useful in this work, both for understanding how electromagnetic fields interact with graphite fibers, and also for use in determining how to develop the knowledge base. Sufficient data was taken to indicate that the E-probe and the horseshoe probe can be useful eddy current transducers for inspecting graphite fiber components. The lacking component at this time is a large enough probe to have sensitivity in both the far and near field of a thick graphite epoxy component.

Workman, Gary L.↗
DOE OSTI2023

Quantitative Small-Signal Stability Analysis of Grid-Forming Inverters in Large-Scale Power Systems

In this paper, the challenges induced by the integration of inverter-based resources (IBRs) into existing power systems are discussed. Although the grid-forming (GFM) control has been used to enhance system performance in multiple sections of electric power systems (e.g., transmission and distribution systems, microgrids, among others), the coupling mechanism between GFM inverter and various types of other components in modern power systems should be clearly explored. Existing analyses mainly focus on qualitative investigations that verify the effectiveness of deploying GFM inverters for stability enhancement. A holistic system-level quantitative analysis is still missing to verify the detailed benefits of GFM inverters and their interactions with other generation units (e.g., synchronous generators [SGs], conventional grid-following [GFL] inverters, synchronous condensers, among others). To fill in the technical gaps, a holistic small-signal model of the entire system with both rotating generation units and IBRs is established along with the customized power flow analysis for varying steady-state operating points. Further, a quantitative method is proposed to identify the impacts of GFM inverters on system performance with an emphasis on a quantifiable stability margin and a complete modal analysis at the system level. Finally, a realistic test system is used to verify the proposed approach.

grid-following↗
DOE OSTI2026

Analytical small-signal stability analysis of low-inertia power system frequency response considering secondary frequency regulation

Modern power systems are increasingly vulnerable to frequency instability as inverter-based resources (IBRs) replace synchronous machines and reduce system rotational inertia. Existing small-signal frequency stability assessment methods are either computationally intensive, relying on simulation-driven approaches, or lack analytical stability regions that explicitly account for secondary frequency response (SFR). This paper introduces new analytical frameworks that enable evaluation small-signal frequency stability while explicitly incorporating tunable IBR and SFR parameters. Using Kharitonov’s theorem with an overbounding approach, explicit small-signal stability criteria are derived. In addition, based on Białas’ criterion and Hurwitz matrix, analytical stability regions are established to reveal feasible design spaces for SFR and IBR parameters tuning. Extensive Matlab/Simulink-based simulations validate the accuracy and computational efficiency of the proposed methods, demonstrating that coordinated tuning of SFR and IBR parameters can substantially enhance system resilience. By bridging analytical rigor with practical tunability, this work provides an analytical framework for assessing small-signal frequency stability in low-inertia grids, supporting the real-time, scalable, and resilient operation of sustainable power systems.

14 SOLAR ENERGY↗
NASA NTRS2002

Micro-Pulse Lidar Signals: Uncertainty Analysis

Micro-pulse lidar (MPL) systems are small, autonomous, eye-safe lidars used for continuous observations of the vertical distribution of cloud and aerosol layers. Since the construction of the first MPL in 1993, procedures have been developed to correct for various instrument effects present in MPL signals. The primary instrument effects include afterpulse, laser-detector cross-talk, and overlap, poor near-range (less than 6 km) focusing. The accurate correction of both afterpulse and overlap effects are required to study both clouds and aerosols. Furthermore, the outgoing energy of the laser pulses and the statistical uncertainty of the MPL detector must also be correctly determined in order to assess the accuracy of MPL observations. The uncertainties associated with the afterpulse, overlap, pulse energy, detector noise, and all remaining quantities affecting measured MPL signals, are determined in this study. The uncertainties are propagated through the entire MPL correction process to give a net uncertainty on the final corrected MPL signal. The results show that in the near range, the overlap uncertainty dominates. At altitudes above the overlap region, the dominant source of uncertainty is caused by uncertainty in the pulse energy. However, if the laser energy is low, then during mid-day, high solar background levels can significantly reduce the signal-to-noise of the detector. In such a case, the statistical uncertainty of the detector count rate becomes dominant at altitudes above the overlap region.

Welton, Ellsworth J.↗
DOE OSTI2024

Lightwave-electronic harmonic frequency mixing

Electronic frequency mixers are fundamental building blocks of electronic systems. Harmonic frequency mixing in particular enables broadband electromagnetic signal analysis across octaves of spectrum using a single local oscillator. However, conventional harmonic frequency mixers do not operate beyond hundreds of gigahertz to a few terahertz. If extended to the petahertz scale in a compact and scalable form, harmonic mixers would enable field-resolved optical signal analysis spanning octaves of spectra in a monolithic device without the need for frequency conversion using nonlinear crystals. Here, we demonstrate lightwave-electronic harmonic frequency mixing beyond 0.350 PHz using plasmonic nanoantennas. We demonstrate that the mixing process enables complete, field-resolved detection of spectral content far outside that of the local oscillator, greatly extending the range of detectable frequencies compared to conventional heterodyning techniques. Our work has important implications for applications where optical signals of interest exhibit coherent femtosecond-scale dynamics spanning multiple harmonics.

Science & Technology - Other Topics↗
DOE OSTI2025

Respiration Signal Pattern Analysis for Doppler Radar Sensor with Passive Node and Its Application in Occupancy Sensing of a Stationary Subject

Doppler radar node occupancy sensors are promising for applications in smart buildings due to their simple circuits and price advantage compared to quadrature radar sensors. However, single-channel sensitivity limitations may result in low sensitivity and misinterpreted motion rates if the detected subject is at or close to “null” points. We designed and tested a novel method to eliminate such limits, demonstrating that passive nodes can be used to detect a sedentary person regardless of position. This method is based on characteristics of chest motion due to respiration, found via both simulations and experiments based on a sinusoidal model and a more realistic model of cardiorespiratory motion. In addition, respiratory rate variability is considered to distinguish a true human presence from a mechanical target. Sensor node data were collected simultaneously with an infrared camera system, which provided a respiration signal reference, to test the algorithm with 19 human subjects and a mechanical target. The results indicate that a human presence was detected with 100% accuracy and successfully differentiated from a mechanical target in a controlled environment. The developed method can greatly improve the occupancy detection accuracy of single-channel radar-based occupancy sensors and facilitate their adoption in smart building applications.

Song, Chenyan↗
NASA NTRS2001

Performance of the Wavelet Decomposition on Massively Parallel Architectures

Traditionally, Fourier Transforms have been utilized for performing signal analysis and representation. But although it is straightforward to reconstruct a signal from its Fourier transform, no local description of the signal is included in its Fourier representation. To alleviate this problem, Windowed Fourier transforms and then wavelet transforms have been introduced, and it has been proven that wavelets give a better localization than traditional Fourier transforms, as well as a better division of the time- or space-frequency plane than Windowed Fourier transforms. Because of these properties and after the development of several fast algorithms for computing the wavelet representation of any signal, in particular the Multi-Resolution Analysis (MRA) developed by Mallat, wavelet transforms have increasingly been applied to signal analysis problems, especially real-life problems, in which speed is critical. In this paper we present and compare efficient wavelet decomposition algorithms on different parallel architectures. We report and analyze experimental measurements, using NASA remotely sensed images. Results show that our algorithms achieve significant performance gains on current high performance parallel systems, and meet scientific applications and multimedia requirements. The extensive performance measurements collected over a number of high-performance computer systems have revealed important architectural characteristics of these systems, in relation to the processing demands of the wavelet decomposition of digital images.

El-Ghazawi, Tarek A.↗
DOE OSTI2024

Advanced Signal Decomposition Analysis and Anomaly Detection in Photovoltaic Systems

With the rapid expansion of large-scale photovoltaic (PV) plants, it is paramount for solar stakeholders to understand the reliability and efficiency of their plants to inform maintenance decisions, increase production, and understand the design factors that impact performance. Diagnosing underperformance in PV plants is challenging due to the relatively few monitoring points with respect to the large geographic footprint of the plant. This work introduces a cutting-edge method that transforms the analysis and management of key factors influencing PV plant performance, including performance loss rate (PLR), recoverable soiling, and major system changes. Identifying these factors is critical for deriving actionable insights. Leveraging advanced analytical techniques such as wavelet transformation, robust regression, and extreme point analysis, this approach provides a nuanced understanding of these factors. This method has been tested across two synthetic datasets and one real dataset, consistently surpassing existing benchmarks by achieving a lower median mean absolute error and reduced error variability across all comparable components.

14 SOLAR ENERGY↗