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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 721 records · Page 40

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NASA NTRS1987

The relationship between low activity comets and more active comets

Low activity comets were observed to see if they are normal, or if they show intrinsic differences. The comets were selected because they have no C2 or C3 emissions and sometimes no emissions were detected at all. It is shown that the low activity comets are intrinsically different from normal comets in that they are depleted in C2 and C3 relative to the observed CN, or that they are without any emissions at small heliocentric distances. Possible causes for the differences between the two groups of comets are suggested. Observational effects are discounted, since the same observational set-up and reduction procedure was used in all cases. Discrepancies may be due to differences at the time of formation, or during evolution, or a combination of both.

Cochran, A. L.↗

DOE OSTI2025

LaBr 3 : Ce self-activation analysis for measuring fast neutron fields

Measurement of the fast neutron production rate in deuterium–tritium (D–T) fusion reactions is important for applications such as active interrogation, fusion diagnostics, and borehole logging. Such measurements are typically performed by neutron activation analysis of metal foils, especially copper. Copper foil activation analysis requires efficiency and energy calibrations of the detector used to measure the foil, and it relies on the detection of 511 keV gamma rays, which are prominent in the active background when neutrons are being produced. Alternatives, such as 79m Br produced by inelastic neutron scattering on 79 Br, are limited by short half-life, low-energy gamma emission, and inability to selectively measure D–T neutrons. This work describes a novel alternative approach to measure ≳10 MeV neutron fields based on self-activation analysis of a LaBr 3 :Ce detector. The activity of 78 Br, the activation product of the 79 Br(n,2n) 78 Br reaction, is used to determine the neutron flux and infer the neutron production rate. We experimentally demonstrate the method with a cylindrical LaBr 3 :Ce crystal with a diameter and height of 3.81 cm that was placed at an ~18 cm distance from the neutron production point, at a 90° angle with respect to the deuteron beam in a D–T neutron generator. Operating voltage and current of the generator were adjusted to evaluate the technique’s performance over a nominal generator output range of approximately (1 - 9) x 10 7 n/s. The neutron output obtained from LaBr 3 :Ce activation agrees to within three standard deviations of the output obtained using copper activation. The self-activation technique can be conveniently employed in a variety of applications to simplify measurements of fast neutrons produced in D–T fusion reactions.

Active interrogationLaBr3↗

NASA NTRS2014

Sao Paulo Lightning Mapping Array (SP-LMA): Network Assessment and Analyses for Intercomparison Studies and GOES-R Proxy Activities

A 12 station Lightning Mapping Array (LMA) network was deployed during October 2011 in the vicinity of Sao Paulo, Brazil (SP-LMA) to contribute total lightning measurements to an international field campaign [CHUVA - Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)]. The SP-LMA was operational from November 2011 through March 2012 during the Vale do Paraiba campaign. Sensor spacing was on the order of 15-30 km, with a network diameter on the order of 40-50km. The SP-LMA provides good 3-D lightning mapping out to 150 km from the network center, with 2-D coverage considerably farther. In addition to supporting CHUVA science/mission objectives, the SP-LMA is supporting the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), on NOAA's Geostationary Operational Environmental Satellite-R (GOES-R: scheduled for a 2015 launch). These proxy data will be used to develop and validate operational algorithms so that they will be ready to use on "day1" following the GOES-R launch. As the CHUVA Vale do Paraiba campaign opportunity was formulated, a broad community-based interest developed for a comprehensive Lightning Location System (LLS) intercomparison and assessment study, leading to the participation and/or deployment of eight other ground-based networks and the space-based Lightning Imaging Sensor (LIS). The SP-LMA data is being intercompared with lightning observations from other deployed lightning networks to advance our understanding of the capabilities/contributions of each of these networks toward GLM proxy and validation activities. This paper addresses the network assessment including noise reduction criteria, detection efficiency estimates, and statistical and climatological (both temporal and spatially) analyses for intercomparison studies and GOES-R proxy activities.

Bailey, J. C.↗

NASA NTRS2023

Damage Detection of a Pressure Vessel with Smart Sensing and Deep Learning

Structural Health Monitoring plays a crucial role in ensuring the safety and reliability of critical infrastructure, including pressure vessels involved in various applications. This research reports the damage detection of a pressure box employed in space habitat that operates in harsh environment where both structural failure and bolt joint loosening may occur. These failure modes are extremely hard to model based on first principles. We explore proper sensing mechanism and the associated inverse analysis algorithm that can elucidate the health condition of the pressure box. It is identified that piezoelectric impedance based active interrogation can provide necessary information for damage detection in such a system. Concurrently, deep learning technique leveraging spatial convolutional neural network is synthesized to analyze the raw data acquired and identify different types of damage. By training the deep learning model on a dataset of healthy and various damage scenarios, we can achieve high accuracy in identifying the presence of damage and its type. This research provides a data-driven methodology for structural damage detection using deep learning and has the potential to be extended to various systems with different failure modes.

Yang Zhang↗

NASA NTRS2021

X-ray Quasi-Periodic Eruptions from Two Previously Quiescent Galaxies

Quasi-Periodic Eruptions (QPEs) are extreme high-amplitude bursts of X-ray radiation recurring every few hours and originating near the central supermassive black holes in galactic nuclei. It is currently unknown what triggers these events, how long they last and how they are connected to the physical properties of the inner accretion flows. Previously, only two such sources were known, found either serendipitously or in archival data, with emission lines in their optical spectra classifying their nuclei as hosting an actively accreting supermassive black hole. Here we present the detection of QPEs in two further galaxies, obtained with a blind and systematic search over half of the X-ray sky. The optical spectra of these galaxies show no signature of black hole activity, indicating that a pre-existing accretion flow typical of active nuclei is not required to trigger these events. Indeed, the periods, amplitudes and profiles of the newly discovered QPEs are inconsistent with current models that invoke radiation-pressure driven accretion disk instabilities. Instead, QPEs might be driven by an orbiting compact object. Furthermore, their observed properties require the mass of the secondary object to be much smaller than the main body and future X-ray observations may constrain possible changes in the period due to orbital evolution. This scenario could make QPEs a viable candidate for the electromagnetic counterparts of the so-called extreme mass ratio inspirals, with considerable implications for multi-messenger astrophysics and cosmology.

R Arcodia↗

NASA NTRS2012

Particle Filtering for Model-Based Anomaly Detection in Sensor Networks

A novel technique has been developed for anomaly detection of rocket engine test stand (RETS) data. The objective was to develop a system that postprocesses a csv file containing the sensor readings and activities (time-series) from a rocket engine test, and detects any anomalies that might have occurred during the test. The output consists of the names of the sensors that show anomalous behavior, and the start and end time of each anomaly. In order to reduce the involvement of domain experts significantly, several data-driven approaches have been proposed where models are automatically acquired from the data, thus bypassing the cost and effort of building system models. Many supervised learning methods can efficiently learn operational and fault models, given large amounts of both nominal and fault data. However, for domains such as RETS data, the amount of anomalous data that is actually available is relatively small, making most supervised learning methods rather ineffective, and in general met with limited success in anomaly detection. The fundamental problem with existing approaches is that they assume that the data are iid, i.e., independent and identically distributed, which is violated in typical RETS data. None of these techniques naturally exploit the temporal information inherent in time series data from the sensor networks. There are correlations among the sensor readings, not only at the same time, but also across time. However, these approaches have not explicitly identified and exploited such correlations. Given these limitations of model-free methods, there has been renewed interest in model-based methods, specifically graphical methods that explicitly reason temporally. The Gaussian Mixture Model (GMM) in a Linear Dynamic System approach assumes that the multi-dimensional test data is a mixture of multi-variate Gaussians, and fits a given number of Gaussian clusters with the help of the wellknown Expectation Maximization (EM) algorithm. The parameters thus learned are used for calculating the joint distribution of the observations. However, this GMM assumption is essentially an approximation and signals the potential viability of non-parametric density estimators. This is the key idea underlying the new approach.

Solano, Wanda↗

NASA NTRS2018

Evolution of H2O Production in Comet C/2012 S1 (ISON) as Inferred from Forbidden Oxygen and OH Emission

We present H2O production rates for comet C/2012 S1 (ISON) derived from observations of [O I] and OH emission during its inbound leg, covering a heliocentric distance range of 1.8–0.44 AU. Our production rates are in agreement with previous measurements using a variety of instruments and techniques and with data from the various observatories greatly differing in their projected fields of view. The consistent results across all data suggest the absence of an extended source of H2O production, for example sublimation of icy grains in the coma, or a source with spatial extent confined to the dimensions of the smallest projected field of view (in this case < 1000 km). We find that ISON had an active area of around 10 sq km for heliocentric distances Rh > 1.2 AU, which then decreased to about half this value from Rh = 1.2–0.9 AU. This was followed by a rapid increase in active area at about Rh = 0.6 AU, corresponding to the first of three major outbursts ISON experienced inside of 1 AU. The combination of a detected outburst in the light curve and rapid increase in active area likely indicates a major nucleus fragmentation event. The 5–10 sq km active area observed outside of Rh = 0.6 AU is consistent with a 50–100% active fraction for the nucleus, larger than typically observed for cometary nuclei. Although the absolute value of the active area is somewhat dependent on the thermal model employed, the changes in active area observed are consistent among models. The conclusion of a 50–100+% active fraction is robust for realistic thermal models of the nucleus. However the possibility of a contribution of a spatially unresolved distribution of icy grains cannot be discounted. As our [OI]-derived H2O production rates are consistent with values derived using other methods, we conclude that the contribution of O2 photodissociation to the observed [O I] emission is at most 5–10% that of the contribution of H2O for ISON. This is consistent with the expected contribution of O2 photodissociation if O2/H2O ∼ 4%, meaning [O I] emission can still be utilized as a reliable proxy for H2O production in comets as long as O2/H2O ≲ 4%, similar to the abundance measured by the ROSINA instrument on Rosetta at comet 67P/Churyumov–Gerasimenko.

Coma↗

NASA NTRS1994

Thunderstorm Hypothesis Reasoner

THOR is a knowledge-based system which incorporates techniques from signal processing, pattern recognition, and artificial intelligence (AI) in order to determine the boundary of small thunderstorms which develop and dissipate over the area encompassed by KSC and the Cape Canaveral Air Force Station. THOR interprets electric field mill data (derived from a network of electric field mills) by using heuristics and algorithms about thunderstorms that have been obtained from several domain specialists. THOR generates two forms of output: contour plots which visually describe the electric field activity over the network and a verbal interpretation of the activity. THOR uses signal processing and pattern recognition to detect signatures associated with noise or thunderstorm behavior in a near real time fashion from over 31 electrical field mills. THOR's AI component generates hypotheses identifying areas which are under a threat from storm activity, such as lightning. THOR runs on a VAX/VMS at the Kennedy Space Center. Its software is a coupling of C and FORTRAN programs, several signal processing packages, and an expert system development shell.

Mulvehill, Alice M.↗

NASA NTRS2007

More About Software for No-Loss Computing

A document presents some additional information on the subject matter of "Integrated Hardware and Software for No- Loss Computing" (NPO-42554), which appears elsewhere in this issue of NASA Tech Briefs. To recapitulate: The hardware and software designs of a developmental parallel computing system are integrated to effectuate a concept of no-loss computing (NLC). The system is designed to reconfigure an application program such that it can be monitored in real time and further reconfigured to continue a computation in the event of failure of one of the computers. The design provides for (1) a distributed class of NLC computation agents, denoted introspection agents, that effects hierarchical detection of anomalies; (2) enhancement of the compiler of the parallel computing system to cause generation of state vectors that can be used to continue a computation in the event of a failure; and (3) activation of a recovery component when an anomaly is detected.

Edmonds, Iarina↗

NASA NTRS2018

Analysis of Observed Contamination Through SAGE III's First Year on Orbit

SAGE III is a payload on the International Space Station that conducts measurements of ozone and other atmospheric constituents through the use of a moderate resolution spectrometer with an operating wavelength range of 290 nm to 1550 nm. Because of the optically sensitive nature of the payload, a suite of eight Thermoelectric Quartz Crystal Microbalances (TQCMs) were included to monitor the operating environment. During the rst year of operation, the SAGE III TQCMs were instrumental in detecting several periods of higher contamination and localizing their sources. A clear window made from quartz crystal covers the instrument assembly's aperture. Under nominal operating conditions, this window is only open during science gathering activities. However, if the rates of contamination accumulation are detected to be above the background rate, the window will be kept closed during science gathering to protect the optically sensitive instrument mirror. An analysis of the signal transmissions through the window for the wavelengths of 290 nm to 1550 nm has been conducted to determine any possible degradation of the window and potential in uence on science data collected to date, and established a baseline for future analysis.

Thompson, Michael P.↗

DOE OSTI2024

Precision Measurements of the Neutron Magnetic Form Factor to High Momentum Transfer using Durand's Method

Protons and neutrons, collectively known as nucleons, along with electrons, constitute the funda- mental building blocks of the visible universe. Understanding their internal structure is crucial for addressing key scientific questions about our origin and existence. Elastic electron-nucleon scatter- ing provides insights into the spatial distributions of charge and current within nucleons through their electromagnetic form factors. Accurate knowledge of these form factors over a broad range of Q2, the squared four-momentum transfer in the scattering process, reveals details about the nucleon’s internal structure. However, high-Q2 data of the nucleon electromagnetic form factor is scarce due to the challenges associated with such measurements. This thesis reports preliminary results from high-precision measurements of the neutron magnetic form factor (Gn M ) to unprecedented Q2 using Durand’s method, also known as the “ratio” method. Systematic errors are greatly reduced by extracting Gn M from the ratio of neutron-coincident (D(e, e'n)) to proton-coincident (D(e, e'p)) quasi-elastic electron scattering from deuteron. The scattered electrons were detected in the BigBite spectrometer, which features multiple Gas Elec- tron Multiplier (GEM) layers with large active area for high-precision tracking at very high rates. Simultaneous nucleon detection was performed by the Super BigBite spectrometer, which utilizes a dipole magnet with large solid angle acceptance at forward angles and a novel hadron calorimeter with very high and comparable detection efficiencies for both protons and neutrons. This setup could handle very high luminosity, making high-Q2 measurements feasible. Data were collected at five Q2 points: 3, 4.5, 7.4, 9.9, and 13.6 (GeV/c)2. Preliminary results are reported for all, with the lowest two Q2 points in good agreement with existing world data, while the higher points significantly extend the Q2 range in which Gn M is known accurately. The precision of the highest Q2 point is expected to remain unmatched for years to come.

Datta, Provakar↗

NASA NTRS2017

Improved Calibration through SMAP RFI Change Detection

Anthropogenic Radio-Frequency Interference (RFI) drove both the SMAP (Soil Moisture Active Passive) microwave radiometer hardware and Level 1 science algorithm designs to use new technology and techniques for the first time on a spaceflight project. Care was taken to provide special features allowing the detection and removal of harmful interference in order to meet the error budget. Nonetheless, the project accepted a risk that RFI and its mitigation would exceed the 1.3-K error budget. Thus, RFI will likely remain a challenge afterwards due to its changing and uncertain nature. To address the challenge, we seek to answer the following questions: How does RFI evolve over the SMAP lifetime? What calibration error does the changing RFI environment cause? Can time series information be exploited to reduce these errors and improve calibration for all science products reliant upon SMAP radiometer data? In this talk, we address the first question.

Passive L-band radiometer↗

NASA NTRS1980

Microwave approaches in hydrology

The microwave approaches for remote sensing of soil moisture centent, snowpack properties, surface water area, and the detection of precipitation over land are discussed. Both active (radar) and passive (radiometry) approaches are considered, and the advantages of microwave sensing are pointed out, including all-weather capability, especially at the longer wavelengths, and greater penetration depth with optical or infrared sensors. Results obtained from ground-based, aircraft, and spacecraft platforms show that microwave systems can monitor the moisture content in the surface soil layer (5 cm thick), and that passive microwave systems can discriminate between light and heavy snowcover, detect the presence of liquid water in the snow, and qualitatively estimate snow water equivalent.

Schmugge, T. J.↗

NASA NTRS2012

Detection of Chemical Precursors of Explosives

Certain selected chemicals associated with terrorist activities are too unstable to be prepared in final form. These chemicals are often prepared as precursor components, to be combined at a time immediately preceding the detonation. One example is a liquid explosive, which usually requires an oxidizer, an energy source, and a chemical or physical mechanism to combine the other components. Detection of the oxidizer (e.g. H2O2) or the energy source (e.g., nitromethane) is often possible, but must be performed in a short time interval (e.g., 5 15 seconds) and in an environment with a very small concentration (e.g.,1 100 ppm), because the target chemical(s) is carried in a sealed container. These needs are met by this invention, which provides a system and associated method for detecting one or more chemical precursors (components) of a multi-component explosive compound. Different carbon nanotubes (CNTs) are loaded (by doping, impregnation, coating, or other functionalization process) for detecting of different chemical substances that are the chemical precursors, respectively, if these precursors are present in a gas to which the CNTs are exposed. After exposure to the gas, a measured electrical parameter (e.g. voltage or current that correlate to impedance, conductivity, capacitance, inductance, etc.) changes with time and concentration in a predictable manner if a selected chemical precursor is present, and will approach an asymptotic value promptly after exposure to the precursor. The measured voltage or current are compared with one or more sequences of their reference values for one or more known target precursor molecules, and a most probable concentration value is estimated for each one, two, or more target molecules. An error value is computed, based on differences of voltage or current for the measured and reference values, using the most probable concentration values. Where the error value is less than a threshold, the system concludes that the target molecule is likely. Presence of one, two, or more target molecules in the gas can be sensed from a single set of measurements.

Li, Jing↗

DOE OSTI2024

Potential applications of microbial genomics in nuclear non-proliferation

As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as “characteristic communities of microorganisms” found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1999

The Soft X-Ray Variability and Spectrum of 1H0419-577 from a Long EUVE Observation

The active galaxy associated with the hard X-ray source 1H0419-577 was observed with EUVE (Extreme Ultraviolet Explorer Satellite) for about 25 days to obtain a long, contiguous light curve and an EUV spectrum. An EUV source was detected which was about as bright as the AGN (Active Galactic Nuclei) and was later identified as an AM Her type system. The AGN showed variations as large as a factor of two over 5-10 day time scales and occasionally varied by 20-30% in less than 0.5day. The spectrum is dominated by a continuum that is poorly fit by a simple power law. There are possible emission lines without positive identifications but the lines are likely to be spurious.

Marshall, H. L.↗

NASA NTRS1991

Design and testing of an active quenching circuit for an avalanche photodiode photon detector

The photon-detection capabilities of avalanche photodiodes (APDs) operating above their theoretical breakdown voltages are described, with particular attention given to the needs and methods of quenching an avalanche once breakdown has occurred. A brief background on the motives of and previous work with this mode of operation is presented. Finally, a description of the design and testing of an active quenching circuit is given. Although the active quenching circuit did not perform as expected, knowledge was gained as to the signal amplitudes necessary for quenching and the need for a better model for the above-breakdown circuit characteristics of the Geiger-mode APD.

Arbel, D.↗

NASA NTRSDate not supplied

Electrochemical Life Detection Methods for Ocean World Exploration

Ubiquitous across terrestrial life is cellular machinery that allows chemical energy flow by facilitating and regulating electron-transfer and chemical modification pathways. Key classes of energy transport molecules enable this movement of electrons for a variety of biological purposes. Additionally, biological enzymes function to add or remove functional groups such asphosphate moieties to redox biomolecules. Presumably, extraterrestrial life is likely to rely on similar energy transport mechanisms. With the search for life in our solar system focused on the icy satellites of Jupiter and Saturn, Europa and Enceladus, developing instrumentation capable of measuring electrochemical redox signatures representative of biomolecules or enzymatic activity in seawater appears a promising and novel means of life detection. Here, we report our adaptation of the Mars Phoenix Wet Chemistry Laboratory (WCL) electroanalytical voltammetry capabilities to assay life-critical redox molecules in synthetic seawater representative of a saline alkaline solution similar to what has been predicted from the Cassini mission data of Enceladus’ sub-surface ocean. In addition, we employ a well-established electrochemical assay that indicates phosphatase activity by comparing substrate and product redox signatures. Our study demonstrated a 10 nM limit of detection for biological redox molecules and a 3 aM limit of detection for alkaline phosphatase in seawater. Incorporation of these methods into next generation WCL payloads aimed at ocean world life detection will enable the search for biological redox-active species and enzymatic activity as indicators of life.

planetary instruments↗