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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

THE FERMI –GBM THREE-YEAR X-RAY BURST CATALOG

The Fermi Gamma-ray Burst Monitor (GBM) is an all-sky gamma-ray monitor well known in the gamma-ray burst (GRB) community. Although GBM excels in detecting the hard, bright extragalactic GRBs, its sensitivity above 8 keV and its all-sky view make it an excellent instrument for the detection of rare, short-lived Galactic transients. In 2010 March, we initiated a systematic search for transients using GBM data. We conclude this phase of the search by presenting a three-year catalog of 1084 X-ray bursts. Using spectral analysis, location, and spatial distributions we classified the 1084 events into 752 thermonuclear X-ray bursts, 267 transient events from accretion flares and X-ray pulses, and 65 untriggered gamma-ray bursts. All thermonuclear bursts have peak blackbody temperatures broadly consistent with photospheric radius expansion (PRE) bursts. We find an average rate of 1.4 PRE bursts per day, integrated over all Galactic bursters within about 10 kpc. These include 33 and 10 bursts from the ultra-compact X-ray binaries 4U 0614+09 and 2S 0918-549, respectively. We discuss these recurrence times and estimate the total mass ejected by PRE bursts in our Galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Feature Selection and Inferential Procedures for Video Data [Slides]

With the rise of electronic and high-dimensional data, new and innovative feature detection and statistical methods are required to perform accurate and meaningful statistical analysis of these datasets that provide unique statistical challenges. In the area of feature detection, much of the recent feature detection research in the computer vision community has focused on deep learning methods, which require large amounts of labeled training data. However, in many application areas, training data is very limited and often difficult to obtain. We develop methods for fast, unsupervised, precise feature detection for video data based on optical flows, edge detection, and clustering methods. We also use pretrained neural networks and interpretable linear models to extract features using very limited training data. In the area of statistics, while high-dimensional data analysis has been a main focus of recent statistical methodological research, much focus has been on populations of high-dimensional vectors, rather than populations of high-dimensional tensors, which are three-dimensional arrays that can be used to model dependent images, such as images taken of the same person or ripped video frames. Our feature detection method is a non-model-based method that fusses information from dense optical flow, raw image pixels, and frame differences to generate detections. Our hypothesis testing methods are based on the assumption that dependent images are concatenated into a tensor that follows a tensor normal distribution, and from this assumption, we derive likelihood-ratio, score, and regression-based tests for one- and multiple-sample testing problems. Our methods will be illustrated on simulated and real datasets. We conclude this report with comments on the relationship between feature detection and hypothesis testing methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Microbial mats in playa lakes and other saline habitats: Early Mars analog?

Microbial mats are cohesive benthic microbial communities which inhabit various Terra (Earth-based) environments including the marine littoral and both permanent and ephemeral (playa) saline lakes. Certain geomorphological features of Mars, such as the Margaritifer Sinus, were interpreted as ancient, dried playa lakes, presumably formed before or during the transition to the present Mars climate. Studies of modern Terran examples suggest that microbial mats on early Mars would have had the capacity to survive and propagate under environmental constraints that would have included irregularly fluctuating regimes of water activity and high ultraviolet flux. Assuming that such microbial communities did indeed inhabit early Mars, their detection during the Mars Rover Sample Return (MRSR) mission depends upon the presence of features diagnostic of the prior existence of these communities or their component microbes or, as an aid to choosing suitable landing, local exploration or sampling sites, geomorphological, sedimentological or chemical features characteristic of their playa lake habitats. Examination of modern Terran playas (e.g., the Lake Eyre basin) shows that these features span several orders of magnitude in size. While stromatolites are commonly centimeter-meter scale features, bioherms or fields of individuals may extend to larger scales. Preservation of organic matter (mats and microbes) would be favored in topographic lows such as channels or ponds of high salinity, particularly those receiving silica-rich groundwaters. These areas are likely to be located near former zones of groundwater emergence and/or where flood channels entered the paleo-playa. Fossil playa systems which may aid in assessing the applicability of this particular Mars analog include the Cambrian Observatory Hill Beds of the Officer Basin and the Eocene Wilkins Peak Member of the Green River Formation.

Bauld, John↗
NASA NTRS2001

Feasibility Study of Radiometry for Airborne Detection of Aviation Hazards

Radiometric sensors for aviation hazards have the potential for widespread and inexpensive deployment on aircraft. This report contains discussions of three aviation hazards - icing, turbulence, and volcanic ash - as well as candidate radiometric detection techniques for each hazard. Dual-polarization microwave radiometry is the only viable radiometric technique for detection of icing conditions, but more research will be required to assess its usefulness to the aviation community. Passive infrared techniques are being developed for detection of turbulence and volcanic ash by researchers in this country and also in Australia. Further investigation of the infrared airborne radiometric hazard detection approaches will also be required in order to develop reliable detection/discrimination techniques. This report includes a description of a commercial hyperspectral imager for investigating the infrared detection techniques for turbulence and volcanic ash.

Gimmestad, Gary G.↗
DOE OSTI2019

The importance and challenges of detecting changes in forest mortality rates

Abstract Tree mortality rates determine forest health, community dynamics, and terrestrial carbon stocks. Climate change is predicted to increase global forest mortality, and some studies have observed recent changes in mortality rates. Assessing shifts in mortality and identifying their causes is challenged by the low mortality rates of trees and the limited scale at which tree mortality is typically assessed. Detecting changes in mortality and assigning mechanisms to those changes may not be feasible unless there are exceptionally large and persistent shifts in forest mortality rates. Here, we combine simulations and life‐history theory to explore how a doubling in mortality might result in population decline, mean life expectancy, and carbon carrying capacity of forests. Using a simulated forest, we also identify that the sampling strategy and effort required to detect a doubling in stem mortality is extensive. We recommend increased efforts at monitoring mortality and a better incorporation of life‐history theory, community composition, and application of changepoint detection statistics in mortality analyses.

McMahon, Sean M.↗
NASA NTRS1990

Satellite ozone measurements and the detection of trends

Due to the international scientific community's concern with the problem of anthropogenic gas-caused depletion of the ozone layer, an international observational program has been established to conduct stratospheric studies for at least a decade. These observations, which will be performed both by the Space Shuttle and the Upper Atmosphere Research Satellite, will encompass the energy input by solar UV irradiance, source and intermediate gases in ozone chemistry, and the global distributions of these ozone-affecting gases by winds.

Hilsenrath, Ernest↗
DOE OSTI2019

Optimization of uranium and plutonium separations using TEVA and UTEVA cartridges for MC-ICP-MS analysis of environmental swipe samples

We report that the analysis of environmental swipe samples for ultra-trace uranium (U) and plutonium (Pu) determinations is essential in the nuclear safeguards community. While mass spectrometry techniques for U and Pu detection continually improve, established separation methods are seldom reevaluated. Currently, actinide separations within the forensics community predominantly employ either Eichrom TEVA® or UTEVA® resins. The direct optimization of U and Pu separations utilizing both resins has not been widely reported. Here, several methods were explored with goals of increasing analyte recovery, acquiring cleaner blanks, and improving the separation efficiency of ultra-trace levels of U and Pu from environmental swipe samples. Finally, the optimized separation methodology of U and Pu was examined using certified reference materials and archived environmental swipe samples.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2015

Development of new Polysiloxane Based Liquid Scintillators

In the last decade, attention toward neutron detection has been growing in the scientific community, driven by new requirements in different fields of application ranging from homeland security to medical and material analysis, from research physics, to nuclear energy production. So far neutron detection, with particular attention to fast neutrons, has been mainly based on organic liquid scintillators, owing to their good efficiency and pulse shape discrimination (PSD) capability. Most of these liquids have however some main drawbacks given by toxicity, flammability, volatility and sensitivity to dissolved oxygen that limits the duration and the quality of their performances with worse handiness and increased costs. Phenyl-substituted polysiloxanes could address most of these issues, being characterized by low toxicity, low volatility and low flammability. Their optical properties can be tailored by changing the phenyl distribution and concentration thus allowing to increase the solubility of organic dyes, to modify the fluorescence spectra and to vary the refractive index of the medium. Furthermore, polysiloxanes have been recently exploited for the production of plastic scintillators with very good chemical and thermal stability and very good radiation hardness and the development of polysiloxane liquid scintillators could allow to combine these interesting properties with the supremacy of liquid scintillators as regarding PSD over plastics. For these reasons, the properties of several phenyl-substituted polysiloxane with different phenyl amounts and different viscosities have been investigated, with particular attention to the scintillation response and the pulse shape discrimination capability, and the results of the investigation are reported in this work. More in details, the scintillation light yield towards gamma rays ({sup 60}Co and {sup 137}Cs) of several polysiloxane liquids has been analyzed and compared with the light yield of a commercial non-toxic liquid scintillator (EJ309). The results have been related to the optical characterization of these materials, especially as regarding the fluorescence response, and the best performing material (1,1,5,5-Tetraphenyl 1,3,3,5-Tetramethyl Trisiloxane) showed a scintillation light-yield only slightly lower than EJ309, proving to be a promising candidate for the production of an efficient polysiloxane based liquid scintillator. The results as regarding the neutron-gamma pulse shape discrimination capability of the best performing materials are also reported in this work and the scintillation decay time of these materials are compared to the results of fluorescence lifetime analysis. PSD tests have been performed at CN accelerator in Legnaro National Laboratories with a 2.2 MeV pulsed neutron beam using TOF procedure and the pulses have been analyzed in order to evidence the PSD capability of every sample. The reported results pave the way to the development of a new promising class of non-toxic liquid scintillating materials for neutron detection, with good light output and interesting PSD characteristics. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2001

Deep UV Native Fluorescence Imaging of Antarctic Cryptoendolithic Communities

An interdisciplinary team at the Jet Propulsion Laboratory Center for Life Detection has embarked on a project to provide in situ chemical and morphological characterization of Antarctic cryptoendolithic microbial communities. We present here in situ deep ultraviolet (UV) native fluorescence and environmental scanning electron microscopy images transiting 8.5 mm into a sandstone sample from the Antarctic Dry Valleys. The deep ultraviolet imaging system employs 224.3, 248.6, and 325 nm lasers to elicit differential fluorescence and resonance Raman responses from biomolecules and minerals. The 224.3 and 248.6 nm lasers elicit a fluorescence response from the aromatic amino and nucleic acids. Excitation at 325 nm may elicit activity from a variety of biomolecules, but is more likely to elicit mineral fluorescence. The resultant fluorescence images provide in situ chemical and morphological maps of microorganisms and the associated organic matrix. Visible broadband reflectance images provide orientation against the mineral background. Environmental scanning electron micrographs provided detailed morphological information. The technique has made possible the construction of detailed fluorescent maps extending from the surface of an Antarctic sandstone sample to a depth of 8.5 mm. The images detect no evidence of microbial life in the superficial 0.2 mm crustal layer. The black lichen component between 0.3 and 0.5 mm deep absorbs all wavelengths of both laser and broadband illumination. Filamentous deep ultraviolet native fluorescent activity dominates in the white layer between 0.6 mm and 5.0 mm from the surface. These filamentous forms are fungi that continue into the red (iron-rich) region of the sample extending from 5.0 to 8.5 mm. Using differential image subtraction techniques it is possible to identify fungal nuclei. The ultraviolet response is markedly attenuated in this region, apparently from the absorption of ultraviolet light by iron-rich particles coating the filaments. Below 8.5 mm the filamentous morphology of the upper layers gives way to punctate 1-2 micron particles evidencing fluorescent activity following excitation at both deep ultraviolet wavelengths.

Storrie-Lombardi, M. C.↗
DOE OSTI2018

Carbon Amendments Alter Microbial Community Structure and Net Mercury Methylation Potential in Sediments

ABSTRACT Neurotoxic methylmercury (MeHg) is produced by anaerobic Bacteria and Archaea possessing the genes hgcAB , but it is unknown how organic substrate and electron acceptor availability impacts the distribution and abundance of these organisms. We evaluated the impact of organic substrate amendments on mercury (Hg) methylation rates, microbial community structure, and the distribution of hgcAB + microbes with sediments. Sediment slurries were amended with short-chain fatty acids, alcohols, or a polysaccharide. Minimal increases in MeHg were observed following lactate, ethanol, and methanol amendments, while a significant decrease (∼70%) was observed with cellobiose incubations. Postincubation, microbial diversity was assessed via 16S rRNA amplicon sequencing. The presence of hgcAB + organisms was assessed with a broad-range degenerate PCR primer set for both genes, while the presence of microbes in each of the three dominant clades of methylators ( Deltaproteobacteria , Firmicutes , and methanogenic Archaea ) was measured with clade-specific degenerate hgcA quantitative PCR (qPCR) primer sets. The predominant microorganisms in unamended sediments consisted of Proteobacteria , Firmicutes , Bacteroidetes , and Actinobacteria . Clade-specific qPCR identified hgcA + Deltaproteobacteria and Archaea in all sites but failed to detect hgcA + Firmicutes . Cellobiose shifted the communities in all samples to ∼90% non- hgcAB -containing Firmicutes (mainly Bacillus spp. and Clostridium spp.). These results suggest that either expression of hgcAB is downregulated or, more likely given the lack of 16S rRNA gene presence after cellobiose incubation, Hg-methylating organisms are largely outcompeted by cellobiose degraders or degradation products of cellobiose. These results represent a step toward understanding and exploring simple methodologies for controlling MeHg production in the environment. IMPORTANCE Methylmercury (MeHg) is a neurotoxin produced by microorganisms that bioacummulates in the food web and poses a serious health risk to humans. Currently, the impact that organic substrate or electron acceptor availability has on the mercury (Hg)-methylating microorganisms is unclear. To study this, we set up microcosm experiments exposed to different organic substrates and electron acceptors and assayed for Hg methylation rates, for microbial community structure, and for distribution of Hg methylators. The sediment and groundwater was collected from East Fork Poplar Creek in Oak Ridge, TN. Amendment with cellobiose (a lignocellulosic degradation by-product) led to a drastic decrease in the Hg methylation rate compared to that in an unamended control, with an associated shift in the microbial community to mostly nonmethylating Firmicutes . This, along with previous Hg-methylating microorganism identification methods, will be important for identifying strategies to control MeHg production and inform future remediation strategies.

16S↗
NASA NTRS2011

PMA-PhyloChip DNA Microarray to Elucidate Viable Microbial Community Structure

Since the Viking missions in the mid-1970s, traditional culture-based methods have been used for microbial enumeration by various NASA programs. Viable microbes are of particular concern for spacecraft cleanliness, for forward contamination of extraterrestrial bodies (proliferation of microbes), and for crew health/safety (viable pathogenic microbes). However, a "true" estimation of viable microbial population and differentiation from their dead cells using the most sensitive molecular methods is a challenge, because of the stability of DNA from dead cells. The goal of this research is to evaluate a rapid and sensitive microbial detection concept that will selectively estimate viable microbes. Nucleic acid amplification approaches such as the polymerase chain reaction (PCR) have shown promise for reducing time to detection for a wide range of applications. The proposed method is based on the use of a fluorescent DNA intercalating agent, propidium monoazide (PMA), which can only penetrate the membrane of dead cells. The PMA-quenched reaction mixtures can be screened, where only the DNA from live cells will be available for subsequent PCR reaction and microarray detection, and be identified as part of the viable microbial community. An additional advantage of the proposed rapid method is that it will detect viable microbes and differentiate from dead cells in only a few hours, as opposed to less comprehensive culture-based assays, which take days to complete. This novel combination approach is called the PMA-Microarray method. DNA intercalating agents such as PMA have previously been used to selectively distinguish between viable and dead bacterial cells. Once in the cell, the dye intercalates with the DNA and, upon photolysis under visible light, produces stable DNA adducts. DNA cross-linked in this way is unavailable for PCR. Environmental samples suspected of containing a mixture of live and dead microbial cells/spores will be treated with PMA, and then incubated in the dark. Thereafter, the sample is exposed to visible light for five minutes, so that the DNA from dead cells will be cross-linked. Following this PMA treatment step, the sample is concentrated by centrifugation and washed (to remove excessive PMA) before DNA is extracted. The 16S rRNA gene fragments will be amplified by PCR to screen the total microbial community using PhyloChip DNA microarray analysis. This approach will detect only the viable microbial community since the PMA intercalated DNA from dead cells would be unavailable for PCR amplification. The total detection time including PCR reaction for low biomass samples will be a few hours. Numerous markets may use this technology. The food industry uses spore detection to validate new alternative food processing technologies, sterility, and quality. Pharmaceutical and medical equipment companies also detect spores as a marker for sterility. This system can be used for validating sterilization processes, water treatment systems, and in various public health and homeland security applications.

Venkateswaran, Kasthuri J.↗
DOE OSTI2014

The application of wavelet shrinkage denoising to magnetic Barkhausen noise measurements

The application of Magnetic Barkhausen Noise (MBN) as a non-destructive method of defect detection has proliferated throughout the manufacturing community. Instrument technology and measurement methodology have matured commensurately as applications have moved from the R and D labs to the fully automated manufacturing environment. These new applications present a new set of challenges including a bevy of error sources. A significant obstacle in many industrial applications is a decrease in signal to noise ratio due to (i) environmental EMI and (II) compromises in sensor design for the purposes of automation. The stochastic nature of MBN presents a challenge to any method of noise reduction. An application of wavelet shrinkage denoising is proposed as a method of decreasing extraneous noise in MBN measurements. The method is tested and yields marked improvement on measurements subject to EMI, grounding noise, and even measurements in ideal conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Multi-Level Anomaly Detection on Time-Varying Graph Data

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating probabilities at finer levels, and these closely related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. To illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.

anomaly detection↗
NASA NTRS2017

Ensuring Interoperability Between Unmanned Aircraft Detect-and-Avoid and Manned Aircraft Collision Avoidance

The Unmanned Aircraft Systems (UAS) community in the United States has identified the need for a collision avoidance region in which UAS Detect-and-Avoid (DAA) vertical guidance is restricted to preclude interoperability issues with manned aircraft collision avoidance system vertical resolution advisories (RAs). This paper documents the process by which the collision avoidance region was defined. Three candidate definitions were evaluated on 1.3 million simulated pairwise encounters between UAS and manned aircraft covering a wide range of horizontal and vertical closure rates, angles, and miss distances. Each definition was evaluated with regard to UAS DAA interoperability with manned aircraft collision avoidance in terms of how well it achieved: 1) the primary objective of restricting DAA vertical guidance prior to RAs when the aircraft are close, and 2) the secondary objective of avoiding unnecessary restrictions of DAA vertical guidance at DAA alerts when the aircraft are further apart. The collision avoidance region definition that fully achieves the primary objective and best achieves the secondary objective was recommended to and accepted by the UAS community in the United States. By this definition, UAS and manned aircraft are in the collision avoidance region where DAA vertical guidance is restricted when the time to closest point of approach (CPA) is less than 50 seconds and either the time to co-altitude is less than 50 seconds or the current vertical separation is less than 800 feet.

unmanned aircraft systems; collision avoidance; in↗
DOE OSTI2017

Novel Short-Circuit Detection in Li-ion Battery Architectures

Industry and the battery research community don’t have accurate and affordable methods to predict catastrophic battery failures. Recently we published a new method of early detection of nascent internal shorts that are precursors to catastrophic failure. This present work was performed to determine the methods short detection capability within battery architectures consisting of two parallel strings with up to four cells in the string. It was found that detection sensitivity is a function of the number of healthy versus compromised cells in the architecture and placement of the measuring device. The method allows one to locate shorted cells without disconnecting cells or loads from the battery architecture.

25 ENERGY STORAGE↗