Search NASA⌕ Search

SEARCH · Search NASA

Results for “scale detection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

The Role of Fire in Global Forest Loss Dynamics

Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land-use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite-derived data for the 2003–2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire-related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire-related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire-related forest loss, with larger contributions in small clearings in interior tropical forests and human-dominated landscapes. Comparison to higher-resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental-scale estimates of fire-related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire-related and non-fire-related land-use change emissions in forested ecosystems.

Dan van Wees↗
NASA NTRSDate not supplied

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
NASA NTRSDate not supplied

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗
DOE OSTI2026

FATHOMS-RAG: A Framework for the Assessment of Thinking and Observation in Multimodal Systems that use Retrieval Augmented Generation

Retrieval-augmented generation (RAG) has emerged as a promising paradigm for improving factual accuracy in large language models (LLMs). We introduce a benchmark designed to evaluate RAG pipelines as a whole, evaluating a pipelines ability to ingest several modalities of information. We present (1) a curated dataset of 93 questions designed to evaluate a pipeline's ability to ingest textual data, tables, images, multimodal data, and cross-document multimodal data; (2) a phrase-level recall metric for correctness; (3) a nearest-neighbor embedding classifier in an attempt to classify pipeline hallucinations; (4) a comparative evaluation of 2 pipelines built with open-source retrieval mechanisms and 4 closed-source foundational models; and (5) a third-party human evaluation of the alignment of our correctness and hallucination metrics. We find that closed-source pipelines significantly outperform open-source pipelines in both the correctness and halucination metrics, with a wider performance gap in questions relying on multimodal and cross-document information. We also find after a human evaluation of our correctness and hallucination metric compared with our questions and pipeline responses, average agreement was 4.62 for correctness 4.53 for hallucination detection on a 1-5 Likert scale with 5 being strongly agree with our determination.

Hildebrand, Samuel [ORNL] (ORCID:0009000465963104)↗
NASA NTRS2020

Detecting differential ground displacements of civil structures in fast-subsiding metropolises with interferometric SAR and band-pass filtering

Ground displacements due to changes in soil conditions represent a threat to the stability of civil structures in many urban areas, worldwide. In fast-subsiding areas, regional subsidence (wavelength ~ 1,000’s m) can be dominantly high and, consequently, mask other signals at local scales (wavelength ~ 10–100’s m). Still, engineering and construction applications require a comprehensive knowledge of local-scale signals, which can threaten the stability of buildings and infrastructure. Here we present a new technique based on band-pass filters for uncovering local-scale signals hidden by regional subsidence as detected by interferometric SAR measurements. We apply our technique to a velocity field calculated from 21 high-resolution COSMO-SkyMed scenes acquired over Mexico City and obtain components of long (> 478 m), intermediate (42–478 m) and short (< 42 m) spatial wavelengths. Our results reveal that long-wavelength velocities exceed − 400 mm/year, whereas intermediate- and short-wavelength velocities are in the order of ± 15 mm/year. We show that intermediate-wavelength velocities are useful for retrieving signals such as uplift along elevated viaducts of Metro lines 4 and B, as well as differential displacements in Pantitlán station’s pedestrian overpass system and across sharp geotechnical boundaries in the piedmont of Sierra de Santa Catarina—where surface faulting occurs.

Darío Solano-Rojas↗
NASA NTRS2011

Dual-Frequency VLBI Study of Centaurus A on Sub-Parsec Scales: The Highest-Resolution View of an Extragalactic Jet

Centaurus A is the closest active galactic nucleus. High resolution imaging using Very Long Baseline Interferometry (VLBI) enables us to study the spectral and kinematic behavior of the radio jet-<:ounterjet system on sub-parsec scales, providing essential information for jet emission and formation models. Aims. Our aim is to study the structure and spectral shape of the emission from the central-parsec region of Cen A. Methods. As a target of the Southern Hemisphere VLBI monitoring program TANAMI (Tracking Active Galactic Nuclei with Millliarcsecond Interferometry), VLBI observations of Cen A are made regularly at 8.4 and 22.3 GHz with the Australian Long Baseline Array (LBA) and associated telescopes in Antarctica, Chile, and South Africa. Results. The first dual-frequency images of this source are presented along with the resulting spectral index map. An angular resolution of 0.4 mas x 0.7 mas is achieved at 8.4 GHz, corresponding to a linear scale of less than 0.013 pc. Hence, we obtain the highest resolution VLBI image of Cen A, comparable to previous space-VLBI observations. By combining with the 22.3 GHz image, we present the corresponding dual-frequency spectral index distribution along the sub-parsec scale jet revealing the putative emission regions for recently detected y-rays from the core region by Fermi/LAT. Conclusions. We resolve the innermost structure of the milliarcsecond scale jet and counter jet system of Cen A into discrete components. The simultaneous observations at two frequencies provide the highest resolved spectral index map of an AGN jet allowing us to identify up to four possible sites as the origin of the high energy emission. Key words. galaxies: active galaxies: individual (Centaurus A, NGC 5128) - galaxies: jets - techniques: high angular resolution

Mueller, C.↗
NASA NTRS2018

On the Ability of Space- Based Passive and Active Remote Sensing Observations of CO2 to Detect Flux Perturbations to the Carbon Cycle

Space-borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT (Greenhouse Gases Observing Satellite) and OCO-2 (Orbiting Carbon Observatory 2), however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high-latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO-2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint. Plain Language Summary: Active and passive remote sensors show the potential to provide unprecedented information on the carbon cycle. With the all-season sampling, active remote sensors are more capable of constraining high-latitude emissions. The reduced sensitivity to cloud and aerosol also makes active sensors more capable of providing information in cloudy and polluted scenes with sufficient accuracy. These experiments account for errors that are fundamental to the top-down approach for constraining emissions, and even including these sources of error, we show that satellite remote sensors are critical for understanding the carbon cycle.

tropical terrestrial biosphere↗
NASA NTRS1990

Tropical Pacific moisture variability

The objectives are to describe synoptic scale variability of moisture over the tropical Pacific Ocean and the systems leading to this variability; implement satellite analysis procedures in support of this effort, and to incorporate additional satellite information into operational analysis forecast systems at the National Meteorological Center (NMC). Composite satellite radiance patterns describe features detectable well before the development of synoptic scale tropical plumes. These typical features were extracted from historical files of Tiros Operational Vertical Sounder (TOVS) radiance observations for a pair of tropical plumes which developed during January 1989. Signals were inserted into the NMC operational medium range forecast model and a suite of model integrations were conducted. Many of the 48 h model errors of the historical forecasts were eliminated by the inclusion of more complete satellite observations. Three studies in satellite radiance analysis progressed. An analysis which blended TOVS moisture channels, OLR observations and European Center for Medium Weather Forecasts (ECMWF) model analysis to generate fields of total precipitable water comparable to those estimated from Scanning Multichannel Microwave Radiometer (SMMR) mu-wave observations. This study demonstrated that a 10 y climatology of precipitable water over the oceans is feasible, using available infrared observations (OLR and TOVS) and model analysis (ECMWF, NMC or similar quality). The estimates are sensitive to model quality and the estimating model must be updated with operational model changes. Coe developed a set of tropical plume and ITCZ composites from TOVS observations, and from NMC and ECMWF analyses which had been passed through a radiative transfer model to simulate TOVS radiances. The composites have been completed as well as many statistical diagnostics of individual TOVS channels. Analysis of the computations is commencing. Chung has initiated a study of the differences between TOVS observed vapor structure during El Nino Southern Oscillation (ENSO) (1983) and non-ENSO (1984) years. Preliminary diagnosis demonstrates gross moisture changes between warm and cold sea surface temperature episodes.

Mcguirk, James P.↗
NASA NTRS2011

TRMM-Based Lightning Climatology

Gridded climatologies of total lightning flash rates seen by the spaceborne Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) have been updated. OTD collected data from May 1995 to March 2000. LIS data (equatorward of about 38 deg) has been added for 1998-2010. Flash counts from each instrument are scaled by the best available estimates of detection efficiency. The long LIS record makes the merged climatology most robust in the tropics and subtropics, while the high latitude data is entirely from OTD. The mean global flash rate from the merged climatology is 46 flashes per second. The peak annual flash rate at 0.5 deg scale is 160 fl/square km/yr in eastern Congo. The peak monthly average flash rate at 2.5 scale is 18 fl/square km/mo, from early April to early May in the Brahmaputra Valley of far eastern India. Lightning decreases in this region during the monsoon season, but increases further north and west. A monthly average peak from early August to early September in northern Pakistan also exceeds any monthly averages from Africa, despite central Africa having the greatest yearly average. Most continental regions away from the equator have an annual cycle with lightning flash rates peaking in late spring or summer. The main exceptions are India and southeast Asia, with springtime peaks in April and May. For landmasses near the equator, flash rates peak near the equinoxes. For many oceanic regions, the peak flash rates occur in autumn. This is particularly noticeable for the Mediterranean and North Atlantic. Landmasses have a strong diurnal cycle of lightning, with flash rates generally peaking between 3-5 pm local solar time. The central United States flash rates peak later, in late evening or early night. Flash rates peak after midnight in northern Argentina. These regions are known for large, intense, long-lived mesoscale convective systems.

Cecil, Daniel J.↗
NASA NTRSDate not supplied

Phenomena Portal: Large- Scale Visual Exploration of Atmospheric Phenomena

The Earth science community is experiencing a high influx of remote sensing data due to recent advancements in sensor technology. This enables the community to extend their research on a larger scale than ever before. Unfortunately, traditional data processing techniques do not scale well to these new, high volume data sources. State-of-the-art machine learning (ML) pipelines have been proven to overcome these burdens in various other fields but are underexploited within the physical sciences community. Moreover, ML is reliant on labeled data, which is currently sparsely available, owing to the fact that ML adoption is still in the early stages within the Earth and atmospheric science communities. To address these issues, we developed the Phenomena Portal, a visual exploration tool that uses ML to detect various atmospheric phenomena on a global scale. This allows the Earth and atmospheric science communities to view trends of occurrences of phenomena, identify potential relationships between them, and analyze spatiotemporal patterns over time. These detections can also serve as initial labeled data for ML research pertaining to the respective phenomena. The tool also incorporates feedback from subject matter experts to further improve the model detection accuracy, thereby facilitating human-in-the-loop. This presentation will provide an overview of the ML model development and cloud deployment. We also discuss the capabilities of the user interface for displaying the detections.

Muthukumaran Ramasubramanian↗
NASA NTRS1976

Jupiter at five microns

The paper summarizes the information obtained in recent maps of Jupiter at 5 microns, a frequency at which the gases in Jupiter have a relatively low opacity. It is highly possible that 5-micron hot spots are breaks in the cloud deck permitting observation of the hot lower layers of the atmosphere. Many 5-micron sources coincide with blue visual features, but the details of the correspondence need further investigation. Large-scale changes in the appearance of the planet occur at 5 microns on time scales of months; these changes are sufficiently dramatic to produce detectable variations in the whole-disk flux from the planet. Their correspondence to large-scale changes in visual features is not yet determined.

Armstrong, K. R.↗
NASA NTRS1999

Characterizing the Small Scale Structure in Clusters of Galaxies

We have applied a wavelet transform analysis to quantify the small-scale (less than a few arcminutes) X-ray structure of clusters of galaxies to several clusters. Three of these clusters show interesting structure. In addition to the small scale structure in surface brightness, we have searched for temperature structure using Advanced Satellite for Cosmology and Astrophysics (ASCA) observations. For A754, we find a filamentary structure, similar to that previously detected in A85. For A119, we find small scale structure associated with both cool and hot regions with a hot filament extending to the northeast. For A1750, one of the first clusters to show substructure from Einstein, we have a rederived the substructure from the ROSAT observations. The ASCA observations show a hot region between the two small scale features - sub-clusters. The hot region shows that the two subclusters are merging and producing a shock wave at the leading edge of the interaction. This analysis had been applied to a sample of 17 clusters to determine the radial distribution of substructure in a sample. The number of detected substructures was rather small and it was decided to select a different cluster sample at larger redshift. This provided a larger radial range over which substructure could be detected. This new cluster sample also includes about 20 clusters and is being analyzed. Finally, we are considering how to compare the substructure parameters of nearby clusters with a more distant sample to see if one can extract cosmological information. Since substructure frequency should depend on the cosmological density parameter, it may be possible to derive new constraints by comparing nearby and distant clusters.

Forman, William R.↗
NASA NTRS1982

An analysis of Seasat SAR for detecting geologic linears

The value of Seasat synthetic aperture radar (SAR) imagery for detecting geologic linears was assessed in a study of an 89,000 sq km section of New York's Adirondack Mountains. A photographic print of optically processed, 1:500,000 scale SAR imagery (one look direction) was analyzed visually, and the detected linears were compared to those recorded on a 1:250,000 scale geologic map. Eighty percent of the 4,170 km of mapped, geologic linears were detected with the SAR imagery. Moreover, nearly 6,900 km of unmapped linears were also detected. Of these, an estimated 90 percent could be observed on high altitude aerial photographs. The relationship between SAR image detection of linears and the different types of indicators (e.g., straight valleys or shorelines) is reported.

Yan, S.-Y.↗
DOE OSTI2026

The SPT-3G+ Experiment on the South Pole Telescope

Observations of the cosmic microwave background (CMB) offer an unparalleled opportunity to advance our understanding of fundamental physics. SPT-3G+ is an upgraded receiver for the arcminute-resolution South Pole Telescope (SPT) that plans to deploy in late 2028. SPT-3G+ will increase the CMB mapping speed of SPT by nearly an order of magnitude over the currently installed SPT-3G receiver. SPT-3G+ will have ~24,000 transition-edge sensor (TES) bolometers in two frequency bands with center frequencies at 95 GHz and 150 GHz that will be read out with microwave multiplexing. SPT-3G+ will measure the CMB lensing spectrum and galaxy clusters to constrain the growth of structure, dark matter, and dark energy. SPT-3G+ will also reach critical thresholds on inflationary constraints by combining data with BICEP/Keck, forming the South Pole Observatory (SPO). BICEP/Keck has deep degree-angular scale measurements but is currently delensing-limited, while SPT-3G+ will provide deep lensing measurements. Forecasts show that SPO will reach an uncertainty on the tensor-to-scalar ratio $r$ of $\sigma(r) \sim 1.2\times 10^{-3}$ by 2034. A detection at these levels would provide evidence of inflation and probe new physics at grand unified theory energy scales, while no detection would exclude large classes of models and shift the scientific paradigm describing the early universe. I will give an overview of SPT-3G+ including its design and current status.

Simon, Sara M. [Fermilab] (ORCID:0009000006683584)↗
NASA NTRS1976

The application of an optical Fourier spectrum analyzer on detecting defects in mass-produced satellite photographs

Various defects in mass-produced pictures transmitted to earth from a satellite are investigated. It is found that the following defects are readily detectable via Fourier spectrum analysis: (1) bit slip, (2) breakup causing loss of image, and (3) disabled track at the top of the imagery. The scratches made on the film during mass production, which are difficult to detect by visual observation, also show themselves readily in Fourier spectrum analysis. A relation is established between the number of scratches, their width and depth and the intensity of their Fourier spectra. Other defects that are found to be equally suitable for Fourier spectrum analysis or visual (image analysis) detection are synchronous loss without blurring of image, and density variation in gray scale. However, the Fourier spectrum analysis is found to be unsuitable for detection of such defects as pin holes, annotation error, synchronous loss with blurring of images, and missing image in the beginning of the work order. The design of an automated, real time system, which will reject defective films, is treated.

Athale, R.↗
NASA NTRS1996

A Structured Grid Based Solution-Adaptive Technique for Complex Separated Flows

The objective of this work was to enhance the predictive capability of widely used computational fluid dynamic (CFD) codes through the use of solution adaptive gridding. Most problems of engineering interest involve multi-block grids and widely disparate length scales. Hence, it is desirable that the adaptive grid feature detection algorithm be developed to recognize flow structures of different type as well as differing intensity, and adequately address scaling and normalization across blocks. In order to study the accuracy and efficiency improvements due to the grid adaptation, it is necessary to quantify grid size and distribution requirements as well as computational times of non-adapted solutions. Flow fields about launch vehicles of practical interest often involve supersonic freestream conditions at angle of attack exhibiting large scale separate vortical flow, vortex-vortex and vortex-surface interactions, separated shear layers and multiple shocks of different intensity. In this work, a weight function and an associated mesh redistribution procedure is presented which detects and resolves these features without user intervention. Particular emphasis has been placed upon accurate resolution of expansion regions and boundary layers. Flow past a wedge at Mach=2.0 is used to illustrate the enhanced detection capabilities of this newly developed weight function.

Thornburg, Hugh↗
NASA NTRS1977

Research in the use of electrets in measuring effluents from rocket exhaust of the space shuttle (6.4 percent scaled model) and Viking 1 launch

Electrets used to detect the chemical composition of rocket exhaust effluents were investigated. The effectiveness of electrets was assessed while comparisons were made with hydrogen chloride measuring devices from chamber and field tests, and computed results from a multilayer diffusion model. The experimental data used were obtained from 18 static test firings, chamber tests, and the Viking 1 launch to Mars. Results show that electrets have multipollutant measuring capabilities, simplicity of deployment, and speed of assessment. The electrets compared favorably with other hydrogen chloride measuring devices. The summary of the measured data from the electrets and the hydrogen chloride detectors was within the upper and lower bounds of the computed hydrogen chloride concentrations from the multilayer diffusion model.

Susko, M.↗
NASA NTRS1985

G27.4+0.0 - A galactic supernova remnant with a central compact source

High-resolution X-ray and radio images of the galactic supernova remnant G27.4+0.0 are presented. The X-ray image reveals a centrally located compact source of emission which accounts for 25 percent + or - 2 percent of the emission. The rest of the emission is found in diffuse patches defining a circle of diameter 4 arc min. The radio image is an incomplete shell of comparable diameter with no apparent counterpart to the compact X-ray source. The X-ray luminosity of the supernova remmant implied by the distance of 26 kpc inferred from the Sigma-D relationship exceeds that of any known remnant. This fact, plus the relatively low X-ray absorption, suggests that the remnant is substantially closer than 26 kpc. No X-ray variability of the central source has been detected to a level of 50 percent on time scales of about 1 year, and no periodicity in the range 0.0001-100 Hz to a limit of 16 percent was detected. If G27.4 +0.0 is within a few kiloparsecs, the central source is most likely to be an accretion-powered X-ray binary.

Kriss, G. A.↗