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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 NTRS1987

Full-scale engine demonstration of an advanced sensor failure detection, isolation and accommodation algorithm: Preliminary results

The objective of the advanced detection, isolation, and accommodation (ADIA) program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, algorithms were developed which detect, isolate, and accommodate sensor failures using analytical redundancy. Preliminary results of a full scale engine demonstration of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 turbofan engine control system are determined and compared to those obtained during a previous evaluation of this algorithm using a real-time hybrid computer simulation of the engine.

Merrill, Walter C.↗
NASA NTRS1987

Full-scale engine demonstration of an advanced sensor failure detection isolation, and accommodation algorithm - Preliminary results

The objective of the advanced detection, isolation, and accommodation (ADIA) program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, algorithms were developed which detect, isolate, and accommodate sensor failures using analytical redundancy. Preliminary results of a full scale engine demonstration of the ADIA algorithm are presented. Minimum detectable levels of sensor failures for an F100 turbofan engine control system are determined and compared to those obtained during a previous evaluation of this algorithm using a real-time hybrid computer simulation of the engine.

Merrill, Walter C.↗
NASA NTRS1973

Investigation of the detection and monitoring of forest insect infestation in the Sierra Nevada Mountains of California

The author has identified the following significant results. Results of analysis of ERTS-1 color composites made by NASA from MSS bands 4, 5, and 7, frame #1055-18055 at a scale of 1:1,000,000 indicate that forests damaged by insects can be delineated and mapped from areas with no damage; and at this same scale other details detected include timbered and nontimbered areas, pasture and agricultural land, deserts, lakes, mountain meadows, riparian vegetation, rock domes, old burned areas, and major stream courses. Enlargements from the above to a scale of 1:80,000 have improved detectibility to the point that three degrees of timber mortality can be identified and mapped.

Hall, R. C.↗
NASA NTRS1978

X-ray observations of a flare in NGC 4151 from OSO 8

The 2-60-keV flux from NGC 4151 has been observed to change by a factor of 2 on a time scale of 1.5 days. No fluctuations in excess of a factor of 3 are detected on time scales less than 4 hours. During a total observation of approximately 11 days there were no statistically significant changes in spectral shape. The spectrum can be fitted by a power law with photon index of about 1.42 + or - 0.06 and a hydrogen column density of approximately 7.5 + or - 0.5 x 10 to the 22nd power atoms/sq cm. A 2-sigma residual to this fit implies fluorescent Fe line emission with an equivalent width of about 240 eV. Both synchrotron self-Compton and thermal Compton models are consistent with the X-ray data.

Mushotzky, R. F.↗
DOE OSTI2025

When can we detect lianas from space? Toward a mechanistic understanding of liana‐infested forest optics

Abstract Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals—reflectance across wavelengths—from liana‐infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine‐scale airborne reflectance data from 999 liana‐infested canopies, and coarse‐scale satellite reflectance data covering 775 ha of liana‐infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short‐wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large‐scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy‐reflectance signal are not exclusive to lianas, accurate large‐scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross‐site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits.

Environmental Sciences & Ecology↗
DOE OSTI2026

A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks

Atmospheric methane (CH4) concentrations are accelerating global warming as net emissions increase. Observing systems that quantify sources remain too sparse and fragmented to detect trends—especially in remote regions where climate‐driven natural emissions may be rising. We provide a framework for quantifying uncertainty reductions through the implementation of a global ecosystem‐methane observing system designed to: (i) substantially lower uncertainty in sectoral and regional emissions, (ii) separate co‐occurring anthropogenic and natural fluxes, and (iii) trend detection at regional scales to verify mitigation progress and provide early warning of natural feedbacks. Using bottom‐up inventories and process‐model ensembles for 2014–2023, we show that anthropogenic emissions remain uncertain by ∼32% globally, while natural sources—tropical and boreal‐arctic wetlands, fires, and inland waters—carry far larger uncertainties (+ 70%) and trend uncertainties reaching ∼200%. Additional observations must match spatial emission structure to increase observability of emissions: high‐resolution satellite constellations for point sources combined with expanded flux networks and wetland mapping for diffuse sources, and denser ground‐based atmospheric column measurements to restore observability in under‐sampled tropics and high latitudes. Notional analyses indicate that targeted additions of flux towers and ∼20 in situ atmospheric column concentration instruments per key tropical region could reduce continental‐scale uncertainties at modest cost. Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and enables early detection of climate‐driven feedbacks from wetlands, fires, permafrost, agriculture, and fossil‐fuel emissions.

Ciais, P↗
NASA NTRSDate not supplied

Monocular Ranging for Small Unmanned Aerial Systems in the Far-Field

Recent proliferation of small Unmanned Aerial Systems (sUAS) applications requires onboard collision avoidance systems to mitigate the risk of collision with non-cooperative aircraft and manned aircraft, which may not see sUAS in time to perform an avoidance maneuver. An attractive avenue for onboard collision avoidance is the utilization of machine vision cameras due to their low size, weight and power (SWaP) requirements. In this paper, we characterize the range performance of a machine vision system developed in-house and mounted onto an sUAS. The technique was designed to estimate the performance of a sense-and-avoid system to ensure that the sensing components meet the well-clear requirements for the chosen platform and avoidance strategy. Experimental flight-test data was acquired from test-flights flown along multiple collision geometries for two intruders: a general Aviation (GA) aircraft and a fixed-wing sUAS. The ownship and both intruders were instrumented with inertial navigation systems (INS) recording position and attitude information. The range at first detection, 𝑹𝟎, was extracted from in-flight imagery of head-on collision course geometry synchronized with INS data from both aircraft and ground-truth values extracted from the raw imagery. This initial detection distance, 𝑹𝟎, scales with atmospheric attenuation. Therefore, under clear sky conditions, the derived 𝑹𝟎 value represents the upper bound on the detection range achievable by the test configuration of the detector. Results indicate that the maximum initial detection distance for a 4k resolution action camera fitted with a 41º Field of View (FOV) lens is 2.763 ± 0.037 km for a GA aircraft and 0.881 ± 0.061 km for a fixed-wing sUAS, respectively. The in results this study suggest that a vision-based detect and track system may be analyzed using the sensor characterization and contextualized within aircraft well-clear volumes.

Chester V. Dolph↗
NASA NTRS1999

Cloud Power Spectra-Dependence on Solar Zenith Angle and Wavelength, Implications for Cloud Optical Property Retrievals

Scale breaks (spatial scales at which power-law exponent changes occur) observed in Landsat radiances have proven to be useful indicators of radiative interactions, and have aided the development of improved techniques in the remote sensing of clouds. This work extends previous theoretical studies to absorbing wavelengths by using both Landsat Thematic Mapper (TM) observations and Monte Carlo (MC) simulations to infer the systematic dependencies of power spectral shape on cloud characteristics, illumination conditions, and wavelength. We show that MC simulations operating on a simple fractal model of horizontally inhomogeneous clouds produce power spectra that qualitatively resemble observed spectra. We also show that the decrease in the spectra power-law exponent seen at intermediate scales (referred to as "roughening") as the Sun becomes more oblique is more pronounced at absorbing wavelengths. An automated procedure designed to detect the small scale break location is unable to find systematic differences between TM Band 4 and Band 7, despite the fact that MC simulations point to systematic differences in horizontal fluxes. The effect of these qualitative characteristics of the spatial spectra on the retrieval of cloud optical properties is examined by comparing power spectra of nadir radiances with power spectra of optical properties retrieved using either traditional Independent Pixel Approximation approaches or modifications based on normalized radiance indices and the inverse Non-local Independent Pixel Approximation. Assuming that the actual cloud properties follow perfect scaling behavior at all scales, we show the improvement of the proposed retrieval modifications.

Oreopoulos, Lazaros↗
DOE OSTI2024

A Novel Method to Train Classification Models for Structure Detection in In Situ Spacecraft Data

We present a method for creating spacecraft-like data which can be used to train Machine Learning (ML) models to detect and classify structures in in situ spacecraft data. First, we use the Grad-Shafranov equation to numerically solve for several magnetohydrostatic equilibria which are variations on a known analytic equilibrium. These equilibria are then used as the initial conditions for Particle-In-Cell simulations in which the structures of interest are observed and labeled. We then take one-dimensional slices through the simulations to replicate what a spacecraft collecting data from the simulation would observe. This sliced data then can be used as training data for the initial training of ML models intended for use on spacecraft data. We demonstrate the method applied to the problem of detecting small-scale plasmoids in the magnetotail, which is important for understanding complex magnetotail reconnection dynamics. The simple 1D classifier we train is able to detect more than 70% of the plasmoid points in the data set but also produces a large number of false positives. Our further work on this example problem is detailed, and further potential uses of the method are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1977

Observations of intense velocity shear and associated electrostatic waves near an auroral arc

Simultaneous measurements of energetic particles and ac electric fields made by the javelin sounding rocket NASA 8:56 during the late expansion phase of a magnetic storm have revealed an intense shear in plasma flow of magnitude 20 (m/s)/m at the edge of an auroral arc. Structure with two characteristic scales sizes is displayed in the region of shear. Larger structures are of the order of several kilometers in size. Intense irregularities with characteristic wavelengths smaller than the scale size of the shear have also been detected. The large-scale changes in the orientation of the charge sheet at the edge of the arc may be due to the Kelvin-Helmholtz branch; shorter-wavelength modes may be related to the shear driven resistive drift wave. Observations are consistent with the suggestion that velocity shear instabilities may play a role in the formation of high-latitude irregularities.

Kelley, M. C.↗
NASA NTRS1986

High dynamic range VLBI observations of NGC 6251

The large radio galaxy NGC 6251 has been observed with an 11-telescope VLBI array, including the full VLA, at 18 cm. High-dynamic-range maps of both the VLBI-scale and VLA-scale radio structure from these observations, as well as hybrid maps from earlier VLBI experiments at 6 and 13 cm, are presented. The 18-cm VLBI hybrid map has an unusually high dynamic range of about 300 to 1 (ratio of the peak brightness to five times the rms noise level) and is limited by thermal noise rather than calibration errors. A lower limit of 80 to 1 for the ratio of jet/counterjet brightness at parsec scales can be set. This is the strongest such limit produced by VLBI observations of any source to date. If the absence of a detectable counterjet is caused by relativistic beaming, then the jet must be aligned within 45 deg of the line of sight. The VLA map shows a complex structure along the previously detected kiloparsec-scale counterjet. The physical conditions in the inner few parsecs of the NGC 6251 jet and their relation to the conditions in the extraordinarily long and well collimated kiloparsec-scale jets are discussed, and it is shown that both small-scale and large-scale morphology can be explained in terms of a simple model and relativistic beaming.

Jones, D. L.↗
DOE OSTI2026

Detecting and Characterizing Fracture Zones Using a Convolutional Neural Network

This project directly supports the Geothermal Technologies Office (GTO) objectives outlined in the Multi-Year Program Plan (MYPP) by advancing two key research areas: “Exploration and Characterization” and “Data, Modeling, and Analysis.” This project has successfully demonstrated a pre-drilling ability to image and characterize the distribution and connectivity of subsurface faults and fractures, key parameters for identifying permeable pathways that enable geothermal fluids to circulate and produce energy. Specifically, we developed and implemented innovative machine learning methodologies to enhance geothermal exploration. Large-scale faults were detected using a Convolutional Neural Network (CNN), while small-scale fractures were characterized using a novel Double-Beam Neural Network (DBNN). These tools have proven both technically effective and cost-efficient by reducing reliance on expensive exploratory drilling. Through collaboration with our geothermal industry partner, this research has significantly advanced techniques for identifying hidden geothermal systems and extending the productive lifespan of existing geothermal fields. We applied our methods to two geothermal fields—Soda Lake (Nevada) and Lightning Dock (New Mexico)—to identify shallow steam-charged fracture zones and characterize deep faults at depths of 1.5-2 km. The steam zone identified at the Soda Lake geothermal field showed excellent agreement with prior drilling data, validating the effectiveness of our approaches. In addition, the analysis revealed three new prospective drilling targets for further development and verification. The outcomes of this project improve our scientific understanding of geothermal reservoir behavior, enhance exploration efficiency, extend the economic life of existing geothermal plants. Ultimately, these advancements contribute to GTO’s goal of achieving more sustainable, affordable, and data-driven geothermal energy development across the United States.

15 GEOTHERMAL ENERGY↗
NASA NTRS2021

Parsec-scale Properties of Steep- and Flat-spectrum Extragalactic Radio Sources from a VLBA Survey of a Complete North Polar Cap Sample

We observed with the Very Long Baseline Array (VLBA) at 2.3 and 8.6 GHz a complete flux-density-limited sample of 482 radio sources with decl. > +75° brighter than 200 mJy at 1.4 GHz drawn from the NVSS catalog. A total of 34% of the sources show parsec-scale emission above the flux density detection limit of 30 mJy; their accurate positions and parsec-scale structure parameters are determined. Among all the sources detected at least at the shortest VLBA baselines, the majority, or 72%, have a steep single-dish spectrum. The fraction of the sources with a detectable parsec-scale structure is above 95% among the flat-spectrum objects and close to 25% among the steep-spectrum objects. We identified 82 compact steep-spectrum source candidates, which make up 17% of the sample; most of them are reported for the first time. The compactness and the brightness temperature of the sources in our sample show a positive correlation with single-dish and VLBA spectral indices. All the sources with a significant 8 GHz variability were detected by the VLBA snapshot observations, which independently confirmed their compactness. We demonstrated that 54% of the sources detected by the VLBA at 2.3 GHz in our sample have a steep VLBA spectrum. The compact radio emission of these sources is likely dominated by optically thin jets or mini-lobes, not by an opaque jet core. These results show that future VLBI surveys aimed at searching for new sources with parsec-scale structure should include not only flat-spectrum sources but also steep-spectrum ones in order to reach an acceptable level of completeness.

A V Popkov↗
NASA NTRS2001

Comparison of Fault Detection Algorithms for Real-time Diagnosis in Large-Scale System

In this paper, we present a review of different real-time capable algorithms to detect and isolate component failures in large-scale systems in the presence of inaccurate test results. A sequence of imperfect test results (as a row vector of I's and O's) are available to the algorithms. In this case, the problem is to recover the uncorrupted test result vector and match it to one of the rows in the test dictionary, which in turn will isolate the faults. In order to recover the uncorrupted test result vector, one needs the accuracy of each test. That is, its detection and false alarm probabilities are required. In this problem, their true values are not known and, therefore, have to be estimated online. Other major aspects in this problem are the large-scale nature and the real-time capability requirement. Test dictionaries of sizes up to 1000 x 1000 are to be handled. That is, results from 1000 tests measuring the state of 1000 components are available. However, at any time, only 10-20% of the test results are available. Then, the objective becomes the real-time fault diagnosis using incomplete and inaccurate test results with online estimation of test accuracies. It should also be noted that the test accuracies can vary with time --- one needs a mechanism to update them after processing each test result vector. Using Qualtech's TEAMS-RT (system simulation and real-time diagnosis tool), we test the performances of 1) TEAMSAT's built-in diagnosis algorithm, 2) Hamming distance based diagnosis, 3) Maximum Likelihood based diagnosis, and 4) HidderMarkov Model based diagnosis.

Kirubarajan, Thiagalingam↗
NASA NTRS2014

Detecting Change in Urban Areas at Continental Scales with MODIS Data

Urbanization is one of the most important components of global environmental change, yet most of what we know about urban areas is at the local scale. Remote sensing of urban expansion across large areas provides information on the spatial and temporal patterns of growth that are essential for understanding differences in socioeconomic and political factors that spur different forms of development, as well the social, environmental, and climatic impacts that result. However, mapping urban expansion globally is challenging: urban areas have a small footprint compared to other land cover types, their features are small, they are heterogeneous in both material composition and configuration, and the form and rates of new development are often highly variable across locations. Here we demonstrate a methodology for monitoring urban land expansion at continental to global scales using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The new method focuses on resolving the spectral and temporal ambiguities between urban/non-urban land and stable/changed areas by: (1) spatially constraining the study extent to known locations of urban land; (2) integrating multitemporal data from multiple satellite data sources to classify c. 2010 urban extent; and (3) mapping newly built areas (2000-2010) within the 2010 urban land extent using a multi-temporal composite change detection approach based on MODIS 250 m annual maximum enhanced vegetation index (EVI). We test the method in 15 countries in East-Southeast Asia experiencing different rates and manifestations of urban expansion. A two-tiered accuracy assessment shows that the approach characterizes urban change across a variety of socioeconomic/political and ecological/climatic conditions with good accuracy (70-91% overall accuracy by country, 69-89% by biome). The 250 m EVI data not only improve the classification results, but are capable of distinguishing between change and no-change areas in urban areas. Over 80% of the error in the change detection can be related to definitional issues or error propagation, rather than algorithm error. As such, these methods hold great potential for routine monitoring of urban change, as well as for providing a consistent and up-to-date dataset on urban extent and expansion for a rapidly evolving region.

Urban areas↗
NASA NTRS1988

Statistics of galaxy orientations - Morphology and large-scale structure

Using the Uppsala General Catalog of bright galaxies and the northern and southern maps of the Lick counts of galaxies, statistical evidence of a morphology-orientation effect is found. Major axes of elliptical galaxies are preferentially oriented along the large-scale features of the Lick maps. However, the orientations of the major axes of spiral and lenticular galaxies show no clear signs of significant nonrandom behavior at a level of less than about one-fifth of the effect seen for ellipticals. The angular scale of the detected alignment effect for Uppsala ellipticals extends to at least theta of about 2 deg, which at a redshift of z of about 0.02 corresponds to a linear scale of about 2/h Mpc.

Lambas, Diego G.↗
NASA NTRS1994

Probing the interstellar medium with pulsars on AU scales

We present a new technique, multiepoch observations of 21 cm absorption against high-velocity pulsars, to probe the properties of the cold neutral hydrogen gas (H I) in the interstellar medium (ISM) at AU scales. In three epochs, over a 1.7 yr interval, we find evidence for significant opacity variations toward all of the pulsars in our sample. Small-scale structure in the ISM is detected on a range of scales from 5 AU to 100 AU, over a wide range of distances (50-2600 pc), opacities (tau(sub max) = 0.1 - 2.5) and directions (anticenter, interarm, high latitude, and local ISM). It appears that small-scale structure is a general property of the ISM and is not confined to special lines of sight. A significant fraction (10%-15%) of the cold H I gas is in this form. These opacity variations do not show any strong correlations with such parameters as transverse distance or integrated opacity, and there is no obvious relation between these structures and those seen in the ionized phase of the ISM.

Frail, Dale A.↗