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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Faster Array Training and Rapid Analysis for a Sensor Array Intended for an Event Monitor in Air

Environmental monitoring, in particular, air monitoring, is a critical need for human space flight. Both monitoring and life support systems have needs for closed loop process feedback and quality control for environmental factors. Monitoring protects the air environment and water supply for the astronaut crew and different sensors help ensure that the habitat falls within acceptable limits, and that the life support system is functioning properly and efficiently. The longer the flight duration and the farther the destination, the more critical it becomes to have carefully monitored and automated control systems for life support. There is an acknowledged need for an event monitor which samples the air continuously and provides near real-time information on changes in the air. Past experiments with the JPL ENose have demonstrated a lifetime of the sensor array, with the software, of around 18 months. We are working on a sensor array and new algorithms that will incorporate transient sensor responses in the analysis. Preliminary work has already showed more rapid quantification and identification of analytes and the potential for faster training time of the array. We will look at some of the factors that contribute to demonstrating faster training time for the array. Faster training will decrease the integrated sensor exposure to training analytes, which will also help extend sensor lifetime.

sensing array↗
NASA NTRS1978

Gamma ray lines from novae

Activities identify the mechanisms responsible for the eruptions characterizing cataclysmic variables are concerned with close binary systems, the properties of which are dominated by the presence of mass transfer from a late-type star onto a white dwarf via an accretion disk. Theories for the outbursts vary in their identification of the eruption mechanism with either gravitational or nuclear energy sources. Existing models for the dwarf novae invoke a dynamical instability in the envelope of the red star which triggers episodic Roche lobe overflow and a concomitant increase in the rate of mass transfer and the outbursts are associated with an increase in the accretion luminosity liberated in the disk. The most successful theoretical models for common nova events involve thermonuclear runaways proceeding in accreted hydrogen envelopes on the white dwarf components of these systems. The characteristics of such runaway events, which can give rise to detectable gamma ray fluxes are discussed. Salient features of existing runaway models are reviewed. Gamma fluxes from Na-22 decay, positron annihilation, and shock induction are predicted.

Truran, J. W.↗
NASA NTRS1984

The formation of stellar systems from interstellar molecular clouds

The observational and theoretical study of regions of continuing star formation promises greater insight into the physical conditions and events associated with the formation of the solar system, and elucidates the role played by star formation in the evolutionary cycle which seems to dominate interstellar material's processing by successive generations of stars in the spiral galaxies. Novel astronomical methods incorporated by the new facilities scheduled for development in the 1980s may yield substantial advancements in star formation process theory; most significant among these efforts will be the identification and examination of the elusive protostellar collapse phase of both star and planetary system formation.

Gehrz, R. D.↗
NASA NTRS2007

System for Secure Integration of Aviation Data

The Aviation Data Integration System (ADIS) of Ames Research Center has been established to promote analysis of aviation data by airlines and other interested users for purposes of enhancing the quality (especially safety) of flight operations. The ADIS is a system of computer hardware and software for collecting, integrating, and disseminating aviation data pertaining to flights and specified flight events that involve one or more airline(s). The ADIS is secure in the sense that care is taken to ensure the integrity of sources of collected data and to verify the authorizations of requesters to receive data. Most importantly, the ADIS removes a disincentive to collection and exchange of useful data by providing for automatic removal of information that could be used to identify specific flights and crewmembers. Such information, denoted sensitive information, includes flight data (here signifying data collected by sensors aboard an aircraft during flight), weather data for a specified route on a specified date, date and time, and any other information traceable to a specific flight. The removal of information that could be used to perform such tracing is called "deidentification." Airlines are often reluctant to keep flight data in identifiable form because of concerns about loss of anonymity. Hence, one of the things needed to promote retention and analysis of aviation data is an automated means of de-identification of archived flight data to enable integration of flight data with non-flight aviation data while preserving anonymity. Preferably, such an automated means would enable end users of the data to continue to use pre-existing data-analysis software to identify anomalies in flight data without identifying a specific anomalous flight. It would then also be possible to perform statistical analyses of integrated data. These needs are satisfied by the ADIS, which enables an end user to request aviation data associated with de-identified flight data. The ADIS includes client software integrated with other software running on flight-operations quality-assurance (FOQA) computers for purposes of analyzing data to study specified types of events or exceedences (departures of flight parameters from normal ranges). In addition to ADIS client software, ADIS includes server hardware and software that provide services to the ADIS clients via the Internet (see figure). The ADIS server receives and integrates flight and non-flight data pertaining to flights from multiple sources. The server accepts data updates from authorized sources only and responds to requests from authorized users only. In order to satisfy security requirements established by the airlines, (1) an ADIS client must not be accessible from the Internet by an unauthorized user and (2) non-flight data as airport terminal information system (ATIS) and weather data must be displayed without any identifying flight information. ADIS hardware and software architecture as well as encryption and data display scheme are designed to meet these requirements. When a user requests one or more selected aviation data characteristics associated with an event (e.g., a collision, near miss, equipment malfunction, or exceedence), the ADIS client augments the request with date and time information from encrypted files and submits the augmented request to the server. Once the user s authorization has been verified, the server returns the requested information in de-identified form.

Kulkarni, Deepak↗
NASA NTRS1973

Combustion detector

A device has been developed for generating a rapid response signal upon the radiation-emitting combustion reaction of certain gases in order to provide a means for the detection and identification of such reaction and concurrently discriminate against spurious signals. This combustion might be the first stage of a coal mine explosion process, and thereby this device could provide a warning of the impending explosion in time to initiate quenching action. This device has the capability of distinguishing between the light emitted from a combustion reaction and the light emitted by miners' lamps, electric lamps, welding sparks or other spurious events so that the quenching mechanism is triggered only when an explosion-initiating combustion occurs.

Trimpi, R. L.↗
NASA NTRS2012

Polarimetric Signatures of Initiating Convection During MC3E

One of the goals of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was to provide constraints for space-based rainfall retrieval algorithms over land. This study used datasets collected during the 2011 field campaign to combine radiometer and ground-based radar polarimetric retrievals in order to better understand hydrometeor type, habit and distribution for initiating continental convection. Cross-track and conically scanning nadir views from the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) were compared with ground-based polarimetric radar retrievals along the ER-2 flight track. Polarimetric signatures for both airborne radiometers and ground-based radars were well co-located with deep convection to relate radiometric signatures with low-level polarimetric radar data for hydrometeor identification and diameter estimation. For the time period of study, Z(sub DR) values indicated no presence of hail at the surface. However, the Z(sub DR) column extended well above the melting level into the mixed phase region, suggesting a possible source of frozen drop embryos for the future formation of hail. The results shown from this study contribute ground truth datasets for GPM PR algorithm development for convective events, which is an improvement upon previous stratiform precipitation centered framework.

Emory, Amber↗
NASA NTRS2024

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗
NASA NTRS2002

Estimating the Single-Trial Characteristics of Event-Related Responses: Evaluation of the MCERP Algorithm

Single-trial event-related responses collected during the course of an experiment are typically averaged before analysis resulting in a rather crude picture of event-related brain dynamics. It has been quite clear for some time that these responses exhibit trial-to-trial variability: however, the computational techniques necessary to deal with such responses in noisy conditions have not been available. To this end we have developed the multiple-component, event-related potential model (mcERP), which assumes that the each event-related response consists of a sum of multiple evoked components each described by a stereotypical waveshape. These waveshapes are allowed to vary in amplitude and onset latency from trial to trial, which allows us to capture, to first-order, the trial-dependent variations in event-related brain dynamics. We have constructed many sets of synthetic data designed to simulate intracortical recordings from a 15 channel, linear-array multielectrode implanted acutely in V1 of an awake-behaving macaque undergoing visual stimulation with a red light flash. This synthetic data was used to characterize the performance of the mcERP algorithm. First we quantified the degree to which such trial-to-trial variability aids in the identification of multiple components, and we demonstrate that amplitude variability is a more important factor in component separation than latency variability. Second, we quantified the behavior of the algorithm under two distinct signal-to-noise ratio (SNR) conditions: Gaussian noise independently present in each channel, and highly correlated (1/f distributed), far-field noise presented identically in each channel of the array. The mcERP algorithm was found to be robust to noise accurately identifying all component waveshapes and their associated single-trial characteristics down to SNR levels of -20dB for Gaussian noise and -7dB for 1/f far-field noise. Comparisons of the performance of this algorithm with factor analysis (FA) and independent component analysis (ICA) will be described by Knuth et al. (SFN abstracts, 2002). In addition, the advantages of application of mcERP to real data will be described by Shah et al, (these abstracts, 2002: SFN abstracts, 2002).

Knuth, K. H.↗
NASA NTRS2011

Risk Acceptance Personality Paradigm: How We View What We Don't Know We Don't Know

The purpose of integrated hazard analyses, probabilistic risk assessments, failure modes and effects analyses, fault trees and many other similar tools is to give managers of a program some idea of the risks associated with their program. All risk tools establish a set of undesired events and then try to evaluate the risk to the program by assessing the severity of the undesired event and the likelihood of that event occurring. Some tools provide qualitative results, some provide quantitative results and some do both. However, in the end the program manager and his/her team must decide which risks are acceptable and which are not. Even with a wide array of analysis tools available, risk acceptance is often a controversial and difficult decision making process. And yet, today's space exploration programs are moving toward more risk based design approaches. Thus, risk identification and good risk assessment is becoming even more vital to the engineering development process. This paper explores how known and unknown information influences risk-based decisions by looking at how the various parts of our personalities are affected by what they know and what they don't know. This paper then offers some criteria for consideration when making risk-based decisions.

Massie, Michael J.↗
NASA NTRS1985

A silicon surface barrier telescope for solar particles identification

From the results three conclusions can be made: (1) the detector system described and tested is capable of good charge resolution from He to Al although beyond Ne the statistic is very poor; (2) in the high gain mode, isotopic resolution has been achieved for Li-6/Li-7 Be-7/Be-9; (3) the much higher yield of He over He and of Be-9 over Be-10 in these types of nuclear reactions prevents obtaining experimental evidence of those isotopes, although it is believed that, at least He-3/He-4 can be resolved under other more favorable conditions (i.e., solar He-3-rich events).

Sequeiros, J.↗
NASA NTRSDate not supplied

Trustworthy Machine Learning for Damage Identification in Composites

A challenging opportunity in structural health monitoring of composite materials is using machine learning (ML) methods to classify acoustic emissions (AE) according to the damage mechanism that emitted the signal. Although a wide variety of ML frameworks have been developed, there is a distinct lack of ground truth datasets which has precluded any direct assessment of their accuracy. Here, we present a novel ground truth dataset gathered on simplified unidirectional SiC/SiC composite structures. Herein, AE is collected from minicomposites which are loaded to targeted percentages of the ultimate tensile stress. These minicomposites are then volumetrically imaged with XCT and individual damage events, along with the mechanism, are correlated to AE. We explore the signal features that allow for mechanism discrimination, along with the feasibility of both unsupervised and supervised frameworks for use in the online monitoring of composite structures.

Machine learning, acoustic emission, ceramic matri↗
NASA NTRS1996

Ion Acceleration in Solar Flares

Solar flares are among the most energetic and interesting phenomena in the Solar system, releasing up to 1032 ergs of energy on timescales of several tens of seconds to several tens of minutes. Much of this energy is in the form of suprathermal electrons and ions, which remain trapped at the Sun and produce a wide variety of radiations, as well as escape into interplanetary space, where they can be directly observed. The radiation from trapped particles consists in general of (1) continuum emission; (2) narrow gamma-ray nuclear deexcitation lines; and (3) high-energy neutrons observed in space or by ground-based neutron monitors. The particles that escape into space consist of both electrons and ions, which often have compositions quite different than that of the ambient solar atmosphere. Flares thus present many diagnostics of the particle acceleration mechanism(s), the identification of which is the ultimate goal of flare research. Moreover, flares in fact offer the only opportunity in astrophysics to study the simultaneous energization of both electrons and ions. Hopefully, an understanding of flares with their wealth of diagnostic data will lead to a better understanding of particle acceleration at other sites in the Universe. It is now generally accepted that flares are roughly divided into two classes: impulsive and gradual. Gradual events are large, occur high in the corona, have long-duration soft and hard X-rays and gamma rays, are electron poor, are associated with Type II radio emission and coronal mass ejections (CMEs), and produce energetic ions with coronal abundance ratios. Impulsive events are more compact, occur lower in the corona, produce short-duration radiation, and exhibit dramatic abundance enhancements in the energetic ions. Their He-3/He-4 ratio is - 1, which is a huge increase over the coronal value of about 5 x 10(exp -4), and they also posses smaller but still significant enhancements of Ne, Mg, Si, and Fe relative to He-4, C, N, and O. Specifically, above about 1 MeV nucleon(exp -1), the ratio of Fe to O is about 8 times larger than in the corona or in gradual flares, while the ratio of Ne, Mg, and Si to O is about 3 times higher; He-4, C, N, and 0 are not enchanced with respect to each other. In addition to these elemental enhancements, Ne and Mg have isotopic enhancements as well. The general scenario that has emerged from these (and other) observations is that energetic particles in gradual events are accelerated by a CME-driven shock, while those particles in impulsive events are accelerated by another mechanism(s).

Miller, James A.↗
NASA NTRS2009

Symbolic Processing Combined with Model-Based Reasoning

A computer program for the detection of present and prediction of future discrete states of a complex, real-time engineering system utilizes a combination of symbolic processing and numerical model-based reasoning. One of the biggest weaknesses of a purely symbolic approach is that it enables prediction of only future discrete states while missing all unmodeled states or leading to incorrect identification of an unmodeled state as a modeled one. A purely numerical approach is based on a combination of statistical methods and mathematical models of the applicable physics and necessitates development of a complete model to the level of fidelity required for prediction. In addition, a purely numerical approach does not afford the ability to qualify its results without some form of symbolic processing. The present software implements numerical algorithms to detect unmodeled events and symbolic algorithms to predict expected behavior, correlate the expected behavior with the unmodeled events, and interpret the results in order to predict future discrete states. The approach embodied in this software differs from that of the BEAM methodology (aspects of which have been discussed in several prior NASA Tech Briefs articles), which provides for prediction of future measurements in the continuous-data domain.

James, Mark↗
NASA NTRS2011

Discovery and Identification of Dimethylsilanediol as a Contaminant in ISS Potable Water

In September 2010, analysis of ISS potable water samples was undertaken to determine the contaminant(s) responsible for a rise of total organic carbon (TOC) in the Water Processor Assembly (WPA) product water. As analysis of the routine target list of organic compounds did not reveal the contaminant, efforts to look for unknown compounds were initiated, resulting in discovery of an unknown peak in the gas chromatography/mass spectrometry (GC/MS) analysis for glycols. A mass spectrum of the contaminant was then generated by concentrating one of the samples and analyzing it by GC/MS in full-scan mode. Although a computer match of the compound identity could not be obtained with the instrument database, a search with a more up-to-date mass spectral library yielded a good match with dimethylsilanediol (DMSD). Inductively coupled plasma/mass spectrometry (ICP/MS) analyses showed abnormally high silicon levels in the samples, confirming that the unknown compound(s) contained silicon. DMSD was then synthesized to confirm the identification and provide a standard to develop a calibration curve. Further confirmation was provided by external direct analysis in real time time of flight (DART TOF) mass spectrometry. To routinely test for DMSD in the future, a quantitative method was needed. A preliminary GC/MS method was developed and archived samples from various locations on ISS were analyzed to determine the extent of the contamination and provide data for troubleshooting. This paper describes these events in more detail as well as problems encountered in routine GC/MS analyses and the subsequent development of high performance liquid chromatography and LC/MS/MS methods for measuring DMSD.

Rutz, Jeffrey A.↗
NASA NTRS1988

Earth orbital variations and vertebrate bioevolution

Cause of the Pleistocene-Holocene transition mammalian extinctions at the end of the last age is the subject of debate between those advocating human predation and climate change. Identification of an ambient air temperature (AAT)-uterine blood flow (UBF) coupling phenomenon supports climate change as a factor in the extinctions, and couples the extinctions to earth orbital variations that drive ice age climatology. The AAT-UBF phenomenon couples mammalian bioevolution directly to climate change via effects of environmental heat upon blood flow to the female uterus and damage to developing embryos. Extinctions were in progress during climatic warming before the Younger Dryas event, and after, at times when the AAT-UBF couple would have been operative; however, impact of a sudden short-term cooling on mammals in the process of adapting to smaller size and relatively larger S/V would have been severe. Variations in earth's orbit, and orbital forcing of atmospheric CO2 concentrations, were causes of the succession of Pleistocene ice ages. Coincidence of mammalian extinctions with terminations of the more intense cold stages links mammalian bioevolution to variations in earth's orbit. Earth orbital variations are a driving source of vertebrate bioevolution.

Mclean, Dewey M.↗
NASA NTRS2017

Stratospheric Intrusion-Influenced Ozone Air Quality Exceedences Investigated in MERRA-2

Ozone near the surface is harmful to human health and is a result of the photochemical reaction with both man-made and natural precursor pollutant sources. Therefore, in order to reduce near surface ozone concentrations, communities must reduce anthropogenic pollution sources. However, the injection of stratospheric ozone into the troposphere, known as a stratospheric intrusion, can also lead to concentrations of ground-level ozone exceeding air quality standards. Stratospheric intrusions are dynamical atmospheric features, however, these intrusions have been misrepresented in models and reanalyses until recently, as the features of a stratospheric intrusion are best identified in horizontal resolutions of approximately 50 km or smaller. NASA's Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis is a publicly-available high-resolution dataset (~50 km) with assimilated ozone that characterizes stratospheric ozone on the same spatiotemporal resolution as the meteorology. We show that stratospheric intrusions that impact surface air quality are well represented in the MERRA-2 reanalysis. This is demonstrated through a case study analysis of stratospheric intrusion events which were identified by the United States Environmental Protection Agency (EPA) to impact surface ozone air quality in spring 2012 in Colorado. The stratospheric intrusions are identified in MERRA-2 by the folding of the dynamical tropopause under the jet stream and subsequent isentropic descent of dry, O3-rich stratospheric air towards the surface where ozone air quality exceedences were observed. The MERRA-2 reanalysis can support air quality agencies for more rapid identification of the impact of stratospheric air on ground-level ozone.

Knowland, K. Emma↗
NASA NTRS1976

Lunar motion analysis and laser data management

Work completed in lunar motion analysis and laser data management during the period July 1, 1971 - September 30, 1975 was reported. In this context, analysis refers to theoretical or numerical studies involving real or potential applications of such observations to improvement of the physical model, and data management refers to the process by which observed photon events are turned into observations and are made available to potential users. The data analysis work included: (1) bringing to operational status of computer programs for the numerical integration of the lunar orbit motion and for the application of lunar laser time delays for the improvement of the parameters of the physical model, (2) program improvement and program integrity, (3) three-dimensional ephemeris, and (4) miscellaneous independent studies. The data management work included: (1) data identification, (2) observatory interfaces, and (3) data distribution.

Mulholland, J. D.↗
NASA NTRS1995

Long term microparticle impact fluxes on LDEF determined from optical survey of Interplanetary Dust Experiment (IDE) sensors

Many of the IDE metal-oxide-silicon (MOS) capacitor-discharge impact sensors remained active during the entire Long Duration Exposure Facility (LDEF) mission. An optical survey of impact sites on the active surfaces of these sensors has been extended to include all sensors from the low-flux sides of LDEF (i.e. the west or trailing side, the earth end, and the space end) and 5-7 active sensors from each LDEF's high-flux sides (i.e. the east or leading side, the south side, and the north side). This survey was facilitated by the presence of a relatively large (greater than 50 micron diameter) optical signature associated with each impact site on the active sensor surfaces. Of the approximately 4700 impacts in the optical survey data set, 84% were from particles in the 0.5 to 3 micron size range. An estimate of the total number of hypervelocity impacts on LDEF from particles greater than 0.5 micron diameter yields a value of approximately 7 x 10(exp 6). Impact feature dimensions for several dozen large craters on MOS sensors and germanium witness plates are also presented. Impact fluxes calculated from the IDE survey data closely matched surveys of similar size impacts (greater than or equal to 3 micron diameter craters in Al, or marginal penetrations of a 2.4 micron thick Al foil) by other LDEF investigators. Since the first year IDE data were electronically recorded, the flux data could be divided into three long term time periods: the first year, the entire 5.8 year mission, and the intervening 4.8 years (by difference). The IDE data show that there was an order of magnitude decrease in the long term microparticle impact flux on the trailing side of LDEF, from 1.01 to 0.098 x 10(exp -4) m(exp 2)/s, from the first year in orbit compared to years 2-6. The long term flux on the leading edge showed an increase from 8.6 to 11.2 x 10(exp -4) m(exp -2)/s over this same time period. (Short term flux increases up to 10,000 times the background rate were recorded on the leading side during LDEF's first year in orbit.) The overall east/west ratio was 44, but during LDEF's first year in orbit the ratio was 8.5, and during years 2-6 the ratio was 114. Long term microparticle impact fluxes on the space end decreased from 1.12 to 0.55 x 10(exp -4) m(exp -2)/s from the first year in orbit compared to years 2-6. The earth end showed the opposite trend with an increase from 0.16 to 0.38 x 10(exp -4) m(exp -2)/s. Fluxes on rows 6 and 12 decreased from 6.1 to 3.4 and 6.7 to 3.7 x 10(exp -4) m(exp -2)/s, respectively, over the same time periods. This resulted in space/earth microparticle impact flux ratios of 7.1 during the first year and 1.5 during years 2-6, while the south/north, space/north and space/south ratios remained constant at 1.1, 0.16 and 0.17, respectively, during the entire mission. This information indicates the possible identification of long term changes in discrete microparticle orbital debris component contributions to the total impact flux experienced by LDEF. A dramatic decrease in the debris population capable of striking the trailing side was detected that could possibly be attributed to the hiatus of western launch activity experienced from 1986-1989. A significant increase in the debris population that preferentially struck the leading side was also observed and could possibly be attributed to a single breakup event that occurred in September of 1986. A substantial increase in the microparticle debris population that struck the earth end of LDEF, but not the space end, was also detected and could possibly be the result of a single breakup event at low altitude. These results point to the importance of including discrete orbital debris component contribution changes in flux models in order to achieve accurate predictions of the microparticle environment that a particular spacecraft will experience in earth orbit. The only reliable, verified empirical measurements of these changes are reported in this paper. Further time-resolved in-situ measurements of these debris populations are needed to accurately assess model predictions and mitigation practices.

Simon, C. G.↗