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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

On the probability of undetected error for the maximum distance separable codes

The performance of maximum-distance-separable codes with symbols from GF(1) when they are used for pure error detection or for simultaneous error correction and detection is investigated. These codes are good for symbol error detection. Their probability of undetected error is upper bounded by q to the -r and decreases monotonically as the symbol error probability epsilon decreases from (q-1)/q to 0, where r is the number of parity-check symbols of a code.

Kasami, T.↗
DOE OSTI2022

The impact of detection rate changes and correlations on random-coincidence background measurements

Coincidence detection of multiple particles emitted during an experiment can yield a new depth of understanding of the underlying process under study. However, the probability of detecting particles that are generated from the same physical event within a given coincidence time window is generally much lower than that of detecting particles that appear in the same coincidence time window, but were not created from the same physical event, and are therefore detected randomly in coincidence with each other. Thus, accurate and precise methods of measuring this random-coincidence background are essential for a wide variety of fields of science. A method to determine this background directly using the data themselves without any additional experimental run time or fake signals introduced in the data was recently established (O’Donnell, 2016). This method yields a statistical uncertainty on the random-coincidence background that is orders of magnitude smaller than that of the true coincidence data, though the potential for systematic errors of backgrounds from this method was never explored. In this work, we discuss common varieties of correlated and uncorrelated changes in the detection rates of each particle detected in an experiment. Here we demonstrate here that a correlation between particle detection rates from, for example, an incident particle beam that initiates a physical process of interest, creates systematic errors in the random-coincidence background measurement. We also discuss the impact of a variety of other realistic scenarios for rate changes in experiments. Lastly, a method is introduced to correct for errors in the random-coincidence background from any source, yielding an optimization between statistical precision and eliminating potential lingering systematic errors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Effects of Phasor Measurement Uncertainty on Power Line Outage Detection

Phasor measurement unit (PMU) technology provides an effective tool to enhance the wide-area monitoring systems (WAMSs) in power grids. Although extensive studies have been conducted to develop several PMU applications in power systems (e.g., state estimation, oscillation detection and control, voltage stability analysis, and line outage detection), the uncertainty aspects of PMUs have not been adequately investigated. This paper focuses on quantifying the impact of PMU uncertainty on power line outage detection and identification, in which a limited number of PMUs installed at a subset of buses are utilized to detect and identify the line outage events. Specifically, the line outage detection problem is formulated as a multi-hypothesis test, and a general Bayesian criterion is used for the detection procedure, in which the PMU uncertainty is analytically characterized. We further apply the minimum detection error criterion for the multi-hypothesis test and derive the expected detection error probability in terms of PMU uncertainty. The framework proposed provides fundamental guidance for quantifying the effects of PMU uncertainty on power line outage detection. Case studies are provided to validate our analysis and show how PMU uncertainty influences power line outage detection.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Remote sensing detection enhancement

Big Data in the area of Remote Sensing has been growing rapidly. Remote sensors are used in surveillance, security, traffic, environmental monitoring, and autonomous sensing. Real-time detection of small moving targets using a remote sensor is an ongoing, challenging problem. Since the object is located far away from the sensor, the object often appears too small. The object’s signal-to-noise-ratio (SNR) is often very low. Occurrences such as camera motion, moving backgrounds (e.g., rustling leaves), low contrast and resolution of foreground objects makes it difficult to segment out the targeted moving objects of interest. Due to the limited appearance of the target, it is tough to obtain the target’s characteristics such as its shape and texture. Without these characteristics, filtering out false detections can be a difficult task. Detecting these targets, would often require the detector to operate under a low detection threshold. However, lowering the detection threshold could lead to an increase of false alarms. In this paper, the author will introduce a new method that improves the probability to detect low SNR objects, while decreasing the number of false alarms as compared to using the traditional baseline detection technique.

47 OTHER INSTRUMENTATION↗
NASA NTRS1986

Theory of optimal weighting of data to detect climatic change

A search for climatic change predicted by climate models can easily yield unconvincing results because of 'climatic noise,' the inherent, unpredictable variability of time-average atmospheric data. A weighted average of data that maximizes the probability of detecting predicted climatic change is presented. To obtain the optimal weights, an estimate of the covariance matrix of the data from a prior data set is needed. This introduces additional sampling error into the method. This is presently taken into account. A form of the weighted average is found whose probability distribution is independent of the true (but unknown) covariance statistics of the data and of the climate model prediction.

Bell, T. L.↗
NASA NTRS1991

Report on the search for atmospheric holes using airs image data

Frank et al (1986) presented a very controversial hypothesis which states that the Earth is being bombarded by water-vapor clouds resulting from the disruption and vaporization of small comets. This hypothesis was based on single-pixel intensity decreases in the images of the earth's dayglow emissions at vacuum-ultraviolet (VUV) wavelengths using the DE-1 imager. These dark spots, or atmospheric holes, are hypothesized to be the result of VUV absorption by a water-vapor cloud between the imager and the dayglow-emitting region. Examined here is the VUV data set from the Auroral Ionospheric Remote Sensor (AIRS) instrument that was flown on the Polar BEAR satellite. AIRS was uniquely situated to test this hypothesis. Due to the altitude of the sensor, the holes should show multi-pixel intensity decreases in a scan line. A statistical estimate indicated that sufficient 130.4-nm data from AIRS existed to detect eight to nine such holes, but none was detected. The probability of this occurring is less than 1.0 x 10(exp -4). A statistical estimate indicated that sufficient 135.6-nm data from AIRS existed to detect approx. 2 holes, and two ambiguous cases are shown. In spite of the two ambiguous cases, the 135.6-nm data did not show clear support for the small-comet hypothesis. The 130.4-nm data clearly do not support the small-comet hypothesis.

Reinleitner, Lee A.↗
NASA NTRS2012

Development of Standards for Nondestructive Evaluation of COPVs Used in Aerospace Applications

Composite OverWrapped Pressure Vessels (COPVs) are currently accepted by NASA based on design and qualification requirements and generally not verified by NDE for the following reasons: (1) Manufactures and end users generally do not have experience and validated quantitative methods of detecting flaws and defects of concern (1-a) If detected, the flaws are not adequately quantified and it is unclear how they may contribute to degradation in mechanical response (1-b) Carbon-epoxy COPVs also extremely sensitive to impact damage and impacts may be below the visible detection threshold (2) If damage is detected, this generally results in rejection since the effect on mechanical response is generally not known (3) NDE response has not generally been fully characterized, probability of detection (POD) established, and processes validated for evaluation of vessel condition as manufactured and delivered.

Waller, Jess M.↗
DOE OSTI2022

Precoder Design for Physical-Layer Security and Authentication in Massive MIMO UAV Communications

Supporting reliable and seamless wireless connectivity for unmanned aerial vehicles (UAVs) has recently become a critical requirement to enable various different use cases of UAVs. Due to their widespread deployment footprint, cellular networks can support beyond visual line of sight (BVLOS) communications for UAVs. In this paper, we consider cellular connected UAVs (C-UAVs) that are served by massive multiple input-multiple-output (MIMO) links to extend coverage range, while also improving physical layer security and authentication. Here, we consider Rician channel and propose a novel linear precoder design for transmitting data and artificial noise (AN). We derive the closed-form expression of the ergodic secrecy rate of CUAVs for both conventional and proposed precoder designs. In addition, we obtain the optimal power splitting factor that divides the power between data and AN by asymptotic analysis. Then, we apply the proposed precoder design in the fingerprint embedding authentication framework, where the goal is to minimize the probability of detection of the authentication tag at an eavesdropper. In simulation results, we show the superiority of the proposed precoder in both secrecy rate and the authentication probability considering moderate and large number of antenna massive MIMO scenarios.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

ROBO-AO KEPLER PLANETARY CANDIDATE SURVEY. III. ADAPTIVE OPTICS IMAGING OF 1629 KEPLER EXOPLANET CANDIDATE HOST STARS

The Robo-AO Kepler Planetary Candidate Survey is observing every Kepler planet candidate host star with laser adaptive optics imaging to search for blended nearby stars, which may be physically associated companions and/or responsible for transit false positives. In this paper, we present the results of our search for stars nearby 1629 Kepler planet candidate hosts. With survey sensitivity to objects as close as ∼0.″15, and magnitude differences Δm ⩽6, we find 223 stars in the vicinity of 206 target KOIs; 209 of these nearby stars have not been previously imaged in high resolution. We measure an overall nearby-star probability for Kepler planet candidates of 12.6%±0.9% at separations between 0.″15 and 4.″0. Particularly interesting KOI systems are discussed, including 26 stars with detected companions that host rocky, habitable zone candidates and five new candidate planet-hosting quadruple star systems. We explore the broad correlations between planetary systems and stellar binarity, using the combined data set of Baranec et al. and this paper. Our previous 2σ result of a low detected nearby star fraction of KOIs hosting close-in giant planets is less apparent in this larger data set. We also find a significant correlation between detected nearby star fraction and KOI number, suggesting possible variation between early and late Kepler data releases.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2023

Potentially Underestimated Gas Flaring Activities—A New Approach to Detect Combustion Using Machine Learning and NASA’s Black Marble Product Suite

Monitoring changes in greenhouse gas (GHG) emission is critical for assessing climate mitigation efforts towards the Paris Agreement goal. A crucial aspect of science-based GHG monitoring is to provide objective information for quality assurance and uncertainty assessment of the reported emissions. Emission estimates from combustion events (gas flaring and biomass burning) are often calculated based on activity data (AD) from satellite observations, such as those detected from the visible infrared imaging radiometer suite (VIIRS) onboard the Suomi-NPP and NOAA-20 satellites. These estimates are often incorporated into carbon models for calculating emissions and removals. Consequently, errors and uncertainties associated with AD propagate into these models and impact emission estimates. Deriving uncertainty of AD is therefore crucial for transparency of emission estimates but remains a challenge due to the lack of evaluation data or alternate estimates. This work proposes a new approach using machine learning (ML) for combustion detection from NASA's Black Marble product suite and explores the assessment of potential uncertainties through comparison with existing detections. We jointly characterize combustion using thermal and light emission signals, with the latter improving detection of probable weaker combustion with less distinct thermal signatures. Being methodologically independent, the differences in ML-derived estimates with existing approaches can indicate the potential uncertainties in detection. The approach was applied to detect gas flares over the Eagle Ford Shale, Texas. We analyzed the spatio-temporal variations in detections and found that approximately 79.04% and 72.14% of the light emission-based detections are missed by ML-derived detections from VIIRS thermal bands and existing datasets, respectively. This improvement in combustion detection and scope for uncertainty assessment is essential for comprehensive monitoring of resulting emissions and we discuss the steps for extending this globally.

gas flaring↗
DOE OSTI2022

Computational Imaging for Intelligence in Highly Scattering Aerosols (Final Report)

Natural and man-made degraded visual environments pose major threats to national security. The random scattering and absorption of light by tiny particles suspended in the air reduces situational awareness and causes unacceptable down-time for critical systems and operations. To improve the situation, we have developed several approaches to interpret the information contained within scattered light to enhance sensing and imaging in scattering media. These approaches were tested at the Sandia National Laboratory Fog Chamber facility and with tabletop fog chambers. Computationally efficient light transport models were developed and leveraged for computational sensing. The models are based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes. After the new model was experimentally validated, statistical approaches for detection, localization, and imaging of objects hidden in fog were developed and demonstrated. A binary hypothesis test and the Neyman-Pearson lemma provided the highest theoretically possible probability of detection for a specified false alarm rate and signal-to-noise ratio. Maximum likelihood estimation allowed estimation of the fog optical properties as well as the position, size, and reflection coefficient of an object in fog. A computational dehazing approach was implemented to reduce the effects of scatter on images, making object features more readily discernible. We have developed, characterized, and deployed a new Tabletop Fog Chamber capable of repeatably generating multiple unique fog-analogues for optical testing in degraded visual environments. We characterized this chamber using both optical and microphysical techniques. In doing so we have explored the ability of droplet nucleation theory to describe the aerosols generated within the chamber, as well as Mie scattering theory to describe the attenuation of light by said aerosols, and correlated the aerosol microphysics to optical properties such as transmission and meteorological optical range (MOR). This chamber has proved highly valuable and has supported multiple efforts inclusive to and exclusive of this LDRD project to test optics in degraded visual environments. Circularly polarized light has been found to maintain its polarization state better than linearly polarized light when propagating through fog. This was demonstrated experimentally in both the visible and short-wave infrared (SWIR) by imaging targets made of different commercially available retroreflective films. It was found that active circularly polarized imaging can increase contrast and range compared to linearly polarized imaging. We have completed an initial investigation of the capability for machine learning methods to reduce the effects of light scattering when imaging through fog. Previously acquired experimental long-wave images were used to train an autoencoder denoising architecture. Overfitting was found to be a problem because of lack of variability in the object type in this data set. The lessons learned were used to collect a well labeled dataset with much more variability using the Tabletop Fog Chamber that will be available for future studies. We have developed several new sensing methods using speckle intensity correlations. First, the ability to image moving objects in fog was shown, establishing that our unique speckle imaging method can be implemented in dynamic scattering media. Second, the speckle decorrelation over time was found to be sensitive to fog composition, implying extensions to fog characterization. Third, the ability to distinguish macroscopically identical objects on a far-subwavelength scale was demonstrated, suggesting numerous applications ranging from nanoscale defect detection to security. Fourth, we have shown the capability to simultaneously image and localize hidden objects, allowing the speckle imaging method to be effective without prior object positional information. Finally, an interferometric effect was presented that illustrates a new approach for analyzing speckle intensity correlations that may lead to more effective ways to localize and image moving objects. All of these results represent significant developments that challenge the limits of the application of speckle imaging and open important application spaces. A theory was developed and simulations were performed to assess the potential transverse resolution benefit of relative motion in structured illumination for radar systems. Results for a simplified radar system model indicate that significant resolution benefits are possible using data from scanning a structured beam over the target, with the use of appropriate signal processing.

58 GEOSCIENCES↗
DOE OSTI2017

Correlated fission data measurements with DANCE and NEUANCE

To enhance the capabilities of the DANCE array, a new detector array NEUANCE was developed to enable simultaneous measurements of prompt fission neutrons and γ rays. NEUANCE was designed and constructed using 21 stilbene organic scintillator crystals. It was installed in the central cavity of the DANCE array. Signals from the 160 BaF 2 detectors of DANCE and the 21 detectors of NEUANCE were merged into a newly designed high-density high-throughput data acquisition system. The excellent pulse shape discrimination properties of stilbene enabled detection of neutrons with energy thresholds as low as 30–40 keVee. A fission reaction tagging method was developed using a NEUANCE γ-ray or neutron signal. The probability of detecting a neutron from the spontaneous fission of 252 Cf using NEUANCE is 47%. New correlated data for prompt fission neutrons and prompt fission rays were obtained for 252 Cf using this high detection efficiency experimental setup. In conclusion, average properties of prompt fission neutron emission as a function of prompt fission γ-ray quantities were also obtained, suggesting that neutron and γ-ray emission in fission are correlated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Pulse-shape discrimination against low-energy Ar-39 beta decays in liquid argon with 4.5 tonne-years of DEAP-3600 data

The DEAP-3600 detector searches for the scintillation signal from dark matter particles scattering on a 3.3 tonne liquid argon target. The largest background comes from 39 Ar beta decays and is suppressed using pulse-shape discrimination (PSD). We use two types of PSD estimator: the prompt-fraction, which considers the fraction of the scintillation signal in a narrow and a wide time window around the event peak, and the log-likelihood-ratio, which compares the observed photon arrival times to a signal and a background model. We furthermore use two algorithms to determine the number of photons detected at a given time: (1) simply dividing the charge of each PMT pulse by the mean single-photoelectron charge, and (2) a likelihood analysis that considers the probability to detect a certain number of photons at a given time, based on a model for the scintillation pulse shape and for afterpulsing in the light detectors. The prompt-fraction performs approximately as well as the log-likelihood-ratio PSD algorithm if the photon detection times are not biased by detector effects. We explain this result using a model for the information carried by scintillation photons as a function of the time when they are detected.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Production of Neutrons by Transport of a GCR Solar Minimum Spectrum through Shielding - Paper 112

The requirements for radiation instrumentation in space can be quite different from those used for terrestrial applications. For example, most neutron instruments used for dosimetry applications used on Earth are sensitive to fission neutron energies and lower, and as such are only useful for neutron energies below 20 to 50 MeV. In space, neutrons are created by galactic cosmic ray (GCR) and solar energetic particle (SEP) interactions in materials, and as such can attain TeV energies and higher. The purpose of this study is to determine the significance of the flux of high energy neutrons in space, and to what degree neutron instruments in space must be sensitive to those high energy neutrons. PHITS transport code calculations of secondary neutron production through various thicknesses of aluminum and water shielding indicate that a significant fraction of the neutron flux and neutron effective dose comes from neutrons above 20 MeV. Measurement of high energy neutrons in space is a difficult task, especially given that the measurement will take place in a mixed radiation field where any signal from an incident neutron must be separated from signals generated by gamma rays, electrons and charged hadrons. Conventional neutron detection methodology dictates that the ability to detect high energy neutrons with a sufficient efficiency depends on the mass of the neutron detector, to first order. The more mass a neutron detector has, the higher the probability of detecting a high energy neutron. However, adding mass comes at a premium in space, often adding costs that prohibit the implementation of a new design with more mass. Thus, to accurately measure the effective dose to humans in space from secondary neutron irradiation, it requires novel methodologies that can stretch the limits of low-mass neutrons detectors, such as developing versatile response functions that are well characterized and can function over a wide range of very different neutron energy spectra. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

Detection of the Earth with the SETI microwave observing system assumed to be operating out in the galaxy

This paper estimates the maximum range at which radar signals from the Earth could be detected by a search system similar to the NASA Search for Extraterrestrial Intelligence Microwave Observing Project (SETI MOP) assumed to be operating out in the galaxy. Figures are calculated for the Targeted Search, and for the Sky Survey parts of the MOP, both operating, as currently planned, in the second half of the decade of the 1990s. Only the most powerful terrestrial transmitters are considered, namely, the planetary radar at Arecibo in Puerto Rico, and the ballistic missile early warning systems (BMEWS). In each case the probabilities of detection over the life of the MOP are also calculated. The calculation assumes that we are only in the eavesdropping mode. Transmissions intended to be detected by SETI systems are likely to be much stronger and would of course be found with higher probability to a greater range. Also, it is assumed that the transmitting civilization is at the same level of technological evolution as ours on Earth. This is very improbable. If we were to detect another technological civilization, it would, on statistical grounds, be much older than we are and might well have much more powerful transmitters. Both factors would make detection by the NASA MOP a much more likely outcome.

NASA Center ARC↗
DOE OSTI2015

GeV γ-ray emission detected by Fermi-lat probably associated with the thermal composite supernova remnant Kesteven 41 in a molecular environment

Hadronic emission from supernova remnant (SNR)–molecular cloud (MC) association systems has been widely regarded as a probe of shock-accelerated cosmic-ray protons. Here, we report on the detection of a γ-ray emission source with a significance of 24σ in 0.2–300 GeV, projected to lie to the northwest of the thermal composite SNR Kesteven 41, using 5.6 years of Fermi-Large Area Telescope (LAT) observation data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1980

Evidence for hot gaseous coronae around the Magellanic Clouds

High-dispersion IUE far-UV spectra were obtained for five stars in the LMC and two stars in the SMC. At Magellanic Cloud velocities, all the spectra exhibit very strong interstellar lines of Al III, Si IV, and C IV, in addition to the usual lower ionization stage lines associated with H I region absorption. In two stars interstellar N V is also detected at the 50 mA level. From a consideration of the strength, width, and radial velocity of these high ionization stage lines, it is argued that regions of hot halo gas have probably been detected in front of the Magellanic Clouds. The regions detected exhibit absorption characteristics very similar to that of the Milky Way corona described previously by Savage and de Boer (1979). A cloud detected in the line of sight to HD 5980 in the SMC at a radial velocity of 300 km/s is of unknown origin.

De Boer, K. S.↗