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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Typical Types and Formation Mechanisms of Haze in an Eastern Asia Megacity, Shanghai

An intensive aerosol and gases campaign was performed at Shanghai in the Yangtze River Delta region over Eastern China from late March to early June 2009. This study provided a complementary picture of typical haze types and the formation mechanisms in megacities over China by using a synergy of ground-based monitoring, satellite and lidar observations. During the whole study period, several extreme low visibility periods were observed with distinct characteristics, and three typical haze types were identified, i.e. secondary inorganic pollution, dust, and biomass burning. Sulfate, nitrate and ammonium accounted for a major part of PM2.5 mass during the secondary inorganic pollution, and the good correlation between SO2/NOx/CO and PM2.5 indicated that coal burning and vehicle emission were the major sources. Large-scale regions with high AOD (aerosol optical depths) and low Angstrom exponent were detected by remote-sensing observation during the dust pollution episode, and this episode corresponded to coarse particles rich in mineral components such as Al and Ca contributing 76.8% to TSP. The relatively low Ca/Al ratio of 0.75 along with the air mass backward trajectory analysis suggested the dust source was from Gobi Desert. Typical tracers for biomass burning from satellite observation (column CO and HCHO) and from ground measurement (CO, particulate K+, OC, and EC) were greatly enhanced during the biomass burning pollution episode. The exclusive linear correlation between CO and PM2.5 corroborated that organic aerosol dominated aerosol chemistry during biomass burning, and the high concentration and enrichment degree of arsenic (As) could be also partly derived from biomass burning. Aerosol optical profile observed by lidar demonstrated that aerosol was mainly constrained below the boundary layer and comprised of spheric aerosol (depolarization ratio <5%) during the secondary inorganic and biomass burning episodes, while thick dust layer distributed at altitudes from near surface to 1.4 km (average depolarization ratio = 0.122+/-0.023) with dust accounting for 44-55% of the total aerosol extinction coefficient during the dust episode. This study portrayed a good picture of the typical haze types and proposed that identification of the complicated emission sources is important for the air quality improvement in megacities in China.

haze↗
NASA NTRS2016

Measuring Small Debris - What You Can't See Can Hurt You

While modeling gives us a tool to better understand the Earth orbit debris environment, it is measurements that give us "ground truth" about what is happening in space. Assets that can detect orbital debris remotely from the surface of the Earth, such as radars and telescopes, give us a statistical view of how debris are distributed in space, how they are being created, and how they are evolving over time. In addition, in situ detectors in space are giving us a better picture of how the small particle environment is actually damaging spacecraft today. IN addition, simulation experiments on the ground help us to understand what we are seeing in orbit. This talk will summarize the history of space debris measurements, how it has changed our view of the Earth orbit environment, and how we are designing the experiments of tomorrow.

Matney, Mark↗
NASA NTRS1988

Detection of a buried horizon with a high thermal diffusivity using thermal remote sensing

A field investigation using thermal remote sensing was performed to test the feasibility of detecting the surface topography of granite bedrock beneath a thin cover of alluvium. Imagery of a region of the Mojave Desert were taken with an airborne multispectral scanner with thermal spectral bandwidths of 10.4 and 12.5 microns an instantaneous field of view of 2.5 mrad. It is suggested that a buried high thermal diffusivity horizon measurably lowers the surface temperature of the overlying lower diffusivity material during the peak of the annual heating cycle.

Nash, David B.↗
NASA NTRSDate not supplied

Image-to-Image Wildfire Detection via Quantum-Compatible Variational Segmentation from Remotely-sensed Data

Over the last decade, the incidence of wildfires has surged, causing widespread destruction globally. To better comprehend and manage these incidents, remote sensing and aerial missions have been implemented in recent efforts. However, this has resulted in an exponential rise in the amount of remote sensing data utilization, leading to a need for intelligent automation of data extraction in wildfire studies. Machine learning provides an accurate automated approach for detecting these natural anomalies and facilitates decision-makers to take prompt actions. To make insightful decisions in wildfire management, it is imperative to move beyond simple detection and explore the potential of probabilistic generative machine learning for creating "what-if" scenarios for various wildfire conditions. Such models offer improved representation of the stochastic nature of wildfire events. However, the optimization of these models can be computationally expensive, especially when using classical computers. Quantum computers have recently emerged as a promising solution to reduce the computational cost of training such models and improve their performance. In this study, we aim to utilize quantum-compatible machine learning techniques to implement our probabilistic generative approach. To that end, we propose a supervised probabilistic variational model consisting of a U-NET-based image-to-image component along with encoder and decoder networks which work as a variational autoencoder (VAE) component. Additionally, we explore the type of latent distribution type in the VAE component and implement different means for modeling the prior distribution. We further investigate the quantum-compatible versions of the model compared to the classical counterpart and benchmark potential benefits of quantum compatibility over the classical model.

quantum machine learning↗
NASA NTRS2023

Automated Global-Scale Detection and Characterization of Anthropogenic Activity using Multi-Source Satellite-Based Remote Sensing Imagery

Satellite-based remote sensing imagery is an effective means for detecting objects and structures in support of many applications. However, detecting the spatial and temporal bounds of a specific activity in satellite imagery is inherently more complex and research in this area is nascent. One reason for this is that describing an activity implies defining both spatial and temporal bounds and while activity is inherently continuous in nature, the geospatial (imagery) time series for any particular swath of ground provided by satellite imagery is relatively sparse and discrete in comparison. The IARPA Space-Based Machine Automated Recognition Technique (SMART)1 program is the first large-scale research program to target advancing the state of the art for automatically detecting, characterizing, and monitoring large-scale anthropogenic activity in global, multispectral satellite imagery. The program has two primary research objectives: 1) the “harmonization” of multiple imagery sources and 2) automated reasoning at scale to detect, characterize, and monitor activities of interest. This paper provides details on the goals, dataset, metrics, and lessons learned of the IARPA SMART program. By releasing the annotated dataset, the program aims to foster additional research in this area by the community at large.

Hirsh R Goldberg↗
NASA NTRS2011

Rapid Detection of the Varicella Zoster Virus

1.Technology Description-Researchers discovered that when the Varicella Zoster Virus (VZV) reactivates from latency in the body, the virus is consistently present in saliva before the appearance of skin lesions. A small saliva sample is mixed with a specialized reagent in a test kit. If the virus is present in the saliva sample, the mixture turns a red color. The sensitivity and specificity emanates from an antibody-antigen reaction. This technology is a rapid, non-invasive, point of-of-care testing kit for detecting the virus from a saliva sample. The device is easy to use and can be used in clinics and in remote locations to quickly detect VZV and begin treatment with antiviral drugs. 2.Market Opportunity- RST Bioscience will be the first and only company to market a rapid, same day test kit for the detection of VZV in saliva. The RST detection test kit will have several advantages over existing, competitive technology. The test kit is self contained and laboratory equipment is not required for analysis of the sample. Only a single saliva sample is required to be taken instead of blood or cerebral spinal fluid. The test kit is portable, sterile and disposable after use. RST detection test kits require no electrical power or expensive storage equipment and can be used in remote locations. 3.Market Analysis- According to the CDC, it is estimated that 1 million cases of shingles occur each year in the U.S. with more than half over the age of sixty. There is a high demand for rapid diagnostics by the public. The point-of-care testing (POCT) market is growing faster than other segments of in vitro diagnostics. According to a July 2007 InteLab Corporation industry report the overall market for POCT was forecast to increase from $10.3 billion in 2005 to $18.7 billion by 2011. The market value of this test kit has not been determined. 4.Competition- The VZV vaccine prevents 50% of cases and reduces neuralgia by 66%. The most popular test detects VZV-specific IgM antibody in blood. Other tests include running a sample in a polymerase chain reaction analyzer, enzyme immunoassay, latex agglutination, indirect fluorescent antibody and fluorescent antibody to membrane antigen assay. These existing tests require laboratory analysis by trained personnel, expensive equipment, invasive procedures and a longer period of time to obtain test results.

Lewis, Michelle P.↗
NASA NTRS1988

Detection and identification of Arctic landforms - An assessment of remotely sensed data

The use of remote sensing data to monitor and analyze the arctic environment is examined. Landsat MSS, TM simulated, NS001, Seasat, and airborne radar are employed to investigate the Strand and Dune areas on the Arctic Coastal Plain in Alaska. The Strand area contains landforms associated with permafrost and the Dune area is dominated by eolian deposits consisting of large longitudinal dunes. The remote sensing data are compared to baseline geomorphic maps derived from aerial photography. It is observed that the multispectral data are better than the radar data for the detection and recognition of arctic landforms, and the NS001 data provided the highest spatial resolution and correlated well with the high-altitude aerial photography.

Dean, Kenneson G.↗
NASA NTRS1977

Microwave remote sensing and its application to soil moisture detection

The author has identified the following significant results. Experimental measurements were utilized to demonstrate a procedure for estimating soil moisture, using a passive microwave sensor. The investigation showed that 1.4 GHz and 10.6 GHz can be used to estimate the average soil moisture within two depths; however, it appeared that a frequency less than 10.6 GHz would be preferable for the surface measurement. Average soil moisture within two depths would provide information on the slope of the soil moisture gradient near the surface. Measurements showed that a uniform surface roughness similar to flat tilled fields reduced the sensitivity of the microwave emission to soil moisture changes. Assuming that the surface roughness was known, the approximate soil moisture estimation accuracy at 1.4 GHz calculated for a 25% average soil moisture and an 80% degree of confidence, was +3% and -6% for a smooth bare surface, +4% and -5% for a medium rough surface, and +5.5% and -6% for a rough surface.

Newton, R. W.↗
NASA NTRS1987

Remote noncontacting measurements of heat transfer coefficients for detection of boundary layer transition in wind tunnel tests

An infrared measurement system is used that consists of a laser heating source, an infrared camera for data acquisition, and a video recorder for data storage. A laser beam is scanned over an airfoil, heating its surface to a few degrees above ambient. An infrared camera then measures the temperature of the airfoil over a two-dimensional field, and these temperatures are stored as a function of time on a video recorder. The resulting temperature pictures are digitized and an iterative approximation algorithm is used to extract the heat transfer coefficient. The resulting values are normalized to the natural convection condition. The technique has been applied in low-speed wind tunnel tests and compared to well-established hot-film measurements which were made simultaneously to confirm the flow conditions. Heat transfer coefficients were determined using a linear scanning pattern, to indicate the position of natural and of artificially induced transition on an airfoil, at various wind speeds. The technique is shown to be sensitive to transition at low Mach numbers. The advantages of the technique are discussed.

Heath, D. Michele↗
NASA NTRS2017

NExSS/NAI Joint ExoPAG SAG 16 Report on Remote Biosignatures for Exoplanets

Future exoplanet observations will soon focus on the search for life beyond the Solar System. Exoplanet biosignatures to be sought are those with global, potentially detectable, impacts on a planet. Biosignatures occur in an environmental context in which geological, atmospheric, and stellar processes and interactions may work to enhance, suppress or mimic these biosignatures. Thus biosignature scienceis inherently interdisciplinary. Its advance is necessary to inform the design of the next flagship missions that will obtain spectra of habitable extrasolar planets. The NExSS NAI Joint Exoplanet Biosignatures Workshop Without Walls brought together the astrobiology, exoplanet, and mission concept communities to review, discuss, debate, and advance the science of remote detection of planetary biosignatures. The multi-meeting workshop began in June 2016, and was a process that engaged a broad range of experts across the interdisciplinary reaches of NASA's Nexus for Exoplanet System Science (NExSS) program, the NASA Astrobiology Institute (NAI), NASAs Exoplanet Exploration Program (ExEP), and international partners, such as the European Astrobiology Network Association (EANA) and Japans Earth Life Science Institute (ELSI). These groups spanned expertise in astronomy, planetary science, Earth sciences, heliophysics, biology, instrument mission development, and engineering.

Kiang, Nancy Y.↗
NASA NTRS2012

Compact Two-step Laser Time-of-Flight Mass Spectrometer for in Situ Analyses of Aromatic Organics on Planetary Missions

RATIONALE A miniature time-of-flight mass spectrometer has been adapted to demonstrate two-step laser desorption-ionization (LOI) in a compact instrument package for enhanced organics detection. Two-step LDI decouples the desorption and ionization processes, relative to traditional laser ionization-desorption, in order to produce low-fragmentation conditions for complex organic analytes. Tuning UV ionization laser energy allowed control ofthe degree of fragmentation, which may enable better identification of constituent species. METHODS A reflectron time-of-flight mass spectrometer prototype measuring 20 cm in length was adapted to a two-laser configuration, with IR (1064 nm) desorption followed by UV (266 nm) postionization. A relatively low ion extraction voltage of 5 kV was applied at the sample inlet. Instrument capabilities and performance were demonstrated with analysis of a model polycyclic aromatic hydrocarbon, representing a class of compounds important to the fields of Earth and planetary science. RESULTS L2MS analysis of a model PAH standard, pyrene, has been demonstrated, including parent mass identification and the onset o(tunable fragmentation as a function of ionizing laser energy. Mass resolution m/llm = 380 at full width at half-maximum was achieved which is notable for gas-phase ionization of desorbed neutrals in a highly-compact mass analyzer. CONCLUSIONS Achieving two-step laser mass spectrometry (L2MS) in a highly-miniature instrument enables a powerful approach to the detection and characterization of aromatic organics in remote terrestrial and planetary applications. Tunable detection of parent and fragment ions with high mass resolution, diagnostic of molecular structure, is possible on such a compact L2MS instrument. Selectivity of L2MS against low-mass inorganic salt interferences is a key advantage when working with unprocessed, natural samples, and a mechanism for the observed selectivity is presented.

Getty, Stephanie↗
NASA NTRS1987

Wind shear detection. Forward-looking sensor technology

A meeting took place at NASA Langley Research Center in February 1987 to discuss the development and eventual use of forward-looking remote sensors for the detection and avoidance of wind shear by aircraft. The participants represented industry, academia, and government. The meeting was structured to provide first a review of the current FAA and NASA wind shear programs, then to define what really happens to the airplane, and finally to give technology updates on the various types of forward-looking sensors. This document is intended to informally record the essence of the technology updates (represented here through unedited duplication of the vugraphs used), and the floor discussion following each presentation. Also given are key issues remaining unresolved.

Bracalente, E. M.↗
NASA NTRS2001

Derivative Analysis of AVIRIS Hyperspectral Data for the Detection of Plant Stress

A remote sensing campaign was conducted over a U.S. Department of Agriculture test site at Shelton, Nebraska. The test field was set off in blocks that were differentially treated with nitrogen. Four replicates of 0-kg/ha to 200-kg/ha, in 50-kg/ha increments, were present. Low-altitude AVIRIS hyperspectral data were collected over the site in 224 spectral bands. Simultaneously, ground data were collected to support the airborne imagery. In an effort to evaluate published, derivative-based algorithms for the detection of plant stress, different derivative-based approaches were applied to the collected AVIRIS image cube. The results indicate that, given good quality hyperspectral imagery, derivative techniques compare favorably with simple, well known band ratio algorithms for detection of plant stress.

Estep, Lee↗
NASA NTRS2001

Band-Moment Compression of AVIRIS Hyperspectral Data and its Use in the Detection of Vegetation Stress

A remote sensing campaign was conducted over a U.S. Department of Agriculture test farm at Shelton, Nebraska. An experimental field was set off in plots that were differentially treated with anhydrous ammonia. Four replicates of 0-kg/ha to 200-kg/ha plots, in 50-kg/ha increments, were set out in a random block design. Low-altitude (GSD of 3 m) Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral data were collected over the site in 224 bands. Simultaneously, ground data were collected to support the airborne imagery. In an effort to reduce data load while maintaining or enhancing algorithm performance for vegetation stress detection, band-moment compression and analysis was applied to the AVIRIS image cube. The results indicated that band-moment techniques compress the AVIRIS dataset significantly while retaining the capability of detecting environmentally induced vegetation stress.

Estep, L.↗
NASA NTRS1979

Detecting transition in agricultural systems

Remote sensing of agricultural phenomena has been largely concentrated on analysis of agriculture at the field level. Concern has been to identify crop status, crop condition, and crop distribution, all of which are spatially analyzed on a field-by-field basis. A more general level of abstraction is the agricultural system, or the complex of crops and other land cover that differentiate various agricultural economies. The paper reports on a methodology to assist in the analysis of the landscape elements of agricultural systems with Landsat digital data. The methodology involves tracing periods of photosynthetic activity for a fixed area. Change from one agricultural system to another is detected through shifts in the intensity and periodicity of photosynthetic activity as recorded in the radiometric return to Landsat. The Landsat-derived radiometric indicator of photosynthetic activity appears to provide the ability to differentiate agricultural systems from each other as well as from conterminous natural vegetation.

Neary, P. J.↗
DOE OSTI2021

Companion Assisted Software Based Remote Attestation in SCADA Networks

Critical infrastructure such as power generation and water distribution systems have become a priority target in cyber warfare because of their recent computerization and introduction to the internet. As a result, Supervisory Control and Data Acquisition (SCADA) system security has become a hot topic in academic and industrial research. Among these topics, Remote Attestation is a security method intended to detect the presence of fileless malware in remote devices as they continue to operate. This allows for the detection of malware in the absence of long-term storage artifacts before symptoms of compromise begin to appear. In general, a trusted device (the verifier) makes a request for evidence of innocence from the untrusted device (the prover). In software-based schemes, the verifier can then measure the delay between its request and the prover’s response. If this delay is greater than the known computational time of the evidence gathering algorithm performed by the prover, then evidence may have been forged. Multi-hop networks often introduce too much network jitter to allow accurate measurement of prover response time, which limits the effectiveness of software based Remote Attestation in a real-world setting. In this work, we introduce a companion device that the verifier can trust to perform a subset of attestation, thereby removing any network jitter. This device is a Field Programmable Gate Array (FPGA) that is physically connected to the prover. We provide a communication protocol between the verifier, prover, and companion. To evaluate our scheme, we simulate it in a common SCADA network environment under normal and heavy traffic loads. Our simulations are performed in the discrete event network simulator NS-3, and we perform statistical analysis over our results to show that our scheme allows for tight timing constraints to be placed on the prover such that the verifier can more easily determine the validity of the evidence that it receives.

Johnson, William A.↗
DOE OSTI2025

Remote Sensing Improves Multi‐Hazard Flooding and Extreme Heat Detection by Fivefold Over Current Estimates

The co‐occurrence of multiple hazards is of growing concern globally as the frequency and magnitude of extreme climate events increases. Despite studies examining the spatial distribution of such events, there has been little work in examining if all relevant life threatening and damaging hazards are captured in existing hazard databases and by common hazard metrics. For example, local/regional flash flooding events are seldom captured by optical satellite instruments and are subsequently excluded from global hazard databases. Similarly, the heat hazard definitions most frequently used in multi‐hazard studies inherently fail to capture events that are life‐threatening but climatologically within an expected range. Our goal is to determine the potential for increasing multi‐hazard event detection capabilities by inferring additional hazard footprints from widely accessible satellite data. We use daily precipitation and temperature satellite data to develop an open‐source framework that infers additional hazard footprints that are not included in traditional methods. With the state of Texas as our study area, we detected 2.5 times as many flood hazards, equivalent to $320 million in property and crop damages. Furthermore, our expanded heat hazard definition increases the impacted area by 56.6%, equivalent to 91.5 million km 2 over an 18 year period. Increasing hazard detection capabilities and expanding existing definitions of hazards using daily satellite data increases the temporal and spatial resolutions at which multi‐hazard events are detected. Having more complete data sets of all relevant hazard extents improves our ability to track global trends and more accurately determine the magnitude of hazard exposure inequities.

equity↗