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NASA NTRS1980

Aspect dependence and frequency spectrum of electrical discharges on the P78-2 (SCATHA) satellite

The satellite charging at high altitudes (SCATHA) P78-2 satellite payload includes a charging electrical effects analyzer (CEEA) which measures the characteristics of electrical discharges in both the frequency and time domain. Pulses are detected in response to commands during electron and ion beam operations and during natural discharge events. The pulse analyzer measures the shape of pulses on four sensors and is the primary CEEA diagnostic for the natural discharges. Only five discharges were found in the data at a time when the pulse analyzer was in mode with sufficient time resolution to resolve the frequency components in the waveform.

Koons, H. C.↗

NASA NTRS1983

Node Synchronization for the Viterbi Decoder

At very low signal to noise ratios such as those that Voyager 2 will encounter at Uranus, the performance of the Reed-Solomon/Viterbi concatenated coding system could be seriously degraded by loss of node synchronization by the Viterbi decoder. This problem is described and now it can be almost completely avoided with a simple outboard hardware ""node synchronizer''. This device makes statistical decisions about node sync based on the hard quantized undecoded data stream. In a worst case Voyager-like environment, our method will detect and correct a true loss of node sync (thought to be a very rate event) within several hundred bits; many of these false alarms for our technique is on the order several years.

Lorden, G.↗

NASA NTRS1984

Node synchronization for the Viterbi decoder

At very low signal to noise ratios such as those that Voyager 2 will encounter at Uranus, the performance of the Reed-Solomon/Viterbi concatenated coding system could be seriously degraded by loss of node synchronization by the Viterbi decoder. This problem is described and now it can be almost completely avoided with a simple outboard hardware 'node synchronizer'. This device makes statistical decisions about node sync based on the hard quantized undecoded data stream. In a worst case Voyager-like environment, our method will detect and correct a true loss of node sync (thought to be a very rare event) within several hundred bits; many of these false alarms for our technique is on the order several years. Previously announced in STAR as N83-28028

Lorden, G.↗

NASA NTRS1985

The Nagoya cosmic-ray muon spectrometer 3, part 2: Track detector

The twelve wide gap spark chambers were utilized as the track detectors of the Nagoya cosmic-ray muon spectrometer not only to obtain the precise locations of particles, but also to get some information about the correspondences between segments of trajectories. The area of each chamber is 150 x 70 sq cm and the width of a gap is 5 cm. The gas used is He at the atmospheric pressure. Each three pairs of them are placed on both sides of the deflection magnet. All images of sparks for each event are projected through the mirror system and recorded by two cameras stereoscopically. The mean detection efficiency of each chamber is 95 + or - 2% and the spacial resolution (jitter and drift) obtained from the prototype-experiment is 0.12 mm. Maximum detectable momentum of the spectrometer is estimated at about 10 TeV/c taking into account these characteristics together with the effects of the energy loss and multiple Coulomb scattering of muons in the iron magnet.

Shibata, S.↗

NASA NTRS2005

Development of an Autonomous Lidar Instrument for Use on a UAV Platform in Support of Homeland Security

Researchers at NASA's Goddard Space Flight Center have developed an autonomous aerosol backscatter lidar instrument for use on the high-altitude ER-2 aircraft (for more information please visit http://cpl.gsfc.nasa.gov). Work is currently underway to transfer this instrument to a UAV platform such as Global Hawk. While the NASA applications are Earth science and satellite validation, there is clearly a Homeland Security application for such an instrument. One novel concept is to have a fleet of UAVs stationed around the country, each UAV having a payload including a lidar instrument. In the event of attack, the appropriate UAV(s) could be launched for purposes of, e.g., plume detection and tracking that are critical for decision support. While the existing lidar instrument is not directly capable of biological species discrimination, it is capable of plume tracking and thus can demonstrate to DHS the capabilities and utility of such instruments. Using NASA funding we will have an instrument ready to fly on Global Hawk by end of 2005. We would like to find partners, either within private industry or within DHS who would be willing to contribute aircraft access and flight hours for a demonstration flight. Longer-term partnerships to develop more advanced and more capable types of lidar instruments are also desirable. In this presentation we will detail the existing ER-2 lidar instrument and show measurement results, show the progress made on adapting to the Global Hawk platform, present concepts for DHS uses of such instruments, and openly pursue partnership opportunities.

McGill, Matthew↗

NASA NTRS2021

Local Ultrasonic Resonance Spectroscopy of Lithium Metal Batteries for Aerospace Applications

As next-generation aircraft and vehicles continue to develop, so do their associated energy demands. Lithium metal batteries are a leading candidate to fulfill this energy requirement, but these batteries are prone to internal dendrite defects that can lead to catastrophic thermal runaway events. Current battery management systems are capable of mitigating such risks, but are unable to detect such defects until thermal runaway has already begun. Various nondestructive evaluation (NDE) techniques, particularly ultrasonic NDE, can directly monitor internal battery parameters giving them the potential to detect critical defects prior to catastrophic failure. However, most of the current battery NDE research has focused on improved battery state-of-charge (SOC) and stateof- health (SOH) monitoring with little emphasis on critical defect detection. Thus, a measurement technique sensitive to subtle battery defects is needed. In addition, the complex mechanics of ultrasound in porous, thin, multilayered batteries prompt the use of physics-based simulation to guide inspections. In this work, an ultrasonic NDE technique has been developed utilizing frequency domain analysis of local battery resonances to detect the presence of battery defects. This technique is a practical extension of local ultrasonic resonance spectroscopy (LURS) – which previously required non-contact laser ultrasonics – to measurements with piezoelectric contact and immersion scan transducers. To extend the technique to work with piezoelectric transducers, ultrasonic battery measurements were compared to a sans-battery calibration measurement. Then, a linear systems deconvolution was used to eliminate the transfer functions of extraneous factors such as the transducer and electronics, leaving only the frequency-dependent battery reflection coefficient. The LURS technique was first validated on stainless steel and aluminum plates, producing reflection coefficients in line with analytical and numerical finite element modeling (FEM) results. Functioning Li-metal pouch cells were then seeded with lithium chip defects prior to LURS measurements. The presence of these defects is shown to cause a measurable shift in the battery’s through-thickness local resonances. 2D, frequency-domain poroelastic models of ultrasonic propagation in a single-cell lithium metal pouch battery were created and corroborated these findings. Thus, this work has both extended and proven the feasibility of the LURS technique in the detection of local battery defects.

Ultrasound↗

NASA NTRS2022

Lightning Over Central Canada: Skill Assessment for Various Land-Atmosphere Model Configurations and Lightning Indices Over a Boreal Study Area

Current lightning predictions are uncertain because they rely on empirical diagnostic relationships and often use coarse-scale climate scenario simulations in which deep convection is parameterized. Previous studies demonstrated that simulations with convection permitting resolutions improve lightning predictions compared to coarser-grid simulations using convection parameterizations for different geographical locations but not over the boreal zone. In this study, lightning simulations with the NASA Unified-Weather Research and Forecasting (NU-WRF) model are evaluated over a domain including the Great Slave Lake in Canada, for six lightning seasons. The simulations are performed at convection parameterized (9 km) and convection-permitting (3 km) resolution using the Goddard 4ICE and the Thompson microphysics schemes. Four lightning indices are evaluated against observations from the Canadian Lightning Detection Network, in terms of spatiotemporal frequency distribution, spatial pattern, daily climatology, and an event-based overall skill assessment. The Thompson scheme is, regardless of the spatial resolution, superior to the Goddard 4ICE scheme in predicting daily climatology but worse in predicting the spatial patterns of lightning occurrence. Results indicate that lightning estimation benefits from modeling at convection-permitting resolution, in particular for the ice based lightning indices. In contrast, the product of convective available potential energy and precipitation rate proved to be the most robust index that was largely invariant to varying spatial resolution. Finally, this study reveals issues of the models to reproduce the observed spatial pattern of lightning well, which might be related to an insufficient representation of land surface heterogeneity, including peatlands, in the study area.

Jonas Mortelmans↗

NASA NTRSDate not supplied

Predicting Adverse Events and their Precursors in Aviation Using Multi-Class Multiple-Instance Learning

In recent years, there has been a rapid growth in the application of machine learning techniques that leverage aviation data collected from commercial airline operations to improve safety. Anomaly detection and predictive maintenance have been the main targets for machine learning applications. However, this paper focuses on the identification of precursors, which is a relatively newer application. Precursors are events correlated with adverse events that happen prior to the adverse event itself. Therefore, precursor mining provides many benefits including understanding the reasons behind a safety incident and the ability to identify signatures, which can be tracked throughout a flight to alert the operators of an potential upcoming adverse event. This work proposes using the multiple-instance learning (MIL) framework, a weakly supervised learning task, combined with a carefully designed Multi-Head Convolutional Neural Networks-Recurrent Neural Networks (MHCNN-RNN) architecture to predict different type of adverse events for any given flights and identify their precursors with little to no post-processing.Results obtained show that the MHCNN-RNN is able to accurately forecast high speed and high path angle events during the approach, and that it is also capable of determining the aircraft’s parameters that are correlated to these events. These parameters can be considered precursors to the events.

multiple instance learning↗

NASA NTRS1999

SRAM Based Re-programmable FPGA for Space Applications

An SRAM (static random access memory)-based reprogrammable FPGA (field programmable gate array) is investigated for space applications. A new commercial prototype, named the RS family, was used as an example for the investigation. The device is fabricated in a 0.25 micrometers CMOS technology. Its architecture is reviewed to provide a better understanding of the impact of single event upset (SEU) on the device during operation. The SEU effect of different memories available on the device is evaluated. Heavy ion test data and SPICE simulations are used integrally to extract the threshold LET (linear energy transfer). Together with the saturation cross-section measurement from the layout, a rate prediction is done on each memory type. The SEU in the configuration SRAM is identified as the dominant failure mode and is discussed in detail. The single event transient error in combinational logic is also investigated and simulated by SPICE. SEU mitigation by hardening the memories and employing EDAC (error detection and correction) at the device level are presented. For the configuration SRAM (CSRAM) cell, the trade-off between resistor de-coupling and redundancy hardening techniques are investigated with interesting results. Preliminary heavy ion test data show no sign of SEL (single event latch-up). With regard to ionizing radiation effects, the increase in static leakage current (static I(sub CC)) measured indicates a device tolerance of approximately 50krad(Si).

Wang, J. J.↗

NASA NTRS2016

Preliminary Results From a Heavily Instrumented Engine Ice Crystal Icing Test in a Ground Based Altitude Test Facility

Preliminary results from the heavily instrumented ALF502R-5 engine test conducted in the NASA Glenn Research Center Propulsion Systems Laboratory are discussed. The effects of ice crystal icing on a full scale engine is examined and documented. This same model engine, serial number LF01, was used during the inaugural icing test in the Propulsion Systems Laboratory facility. The uncommanded reduction of thrust (rollback) events experienced by this engine in flight were simulated in the facility. Limited instrumentation was used to detect icing on the LF01 engine. Metal temperatures on the exit guide vanes and outer shroud and the load measurement were the only indicators of ice formation. The current study features a similar engine, serial number LF11, which is instrumented to characterize the cloud entering the engine, detect/characterize ice accretion, and visualize the ice accretion in the region of interest. Data were acquired at key LF01 test points and additional points that explored: icing threshold regions, low altitude, high altitude, spinner heat effects, and the influence of varying the facility and engine parameters. For each condition of interest, data were obtained from some selected variations of ice particle median volumetric diameter, total water content, fan speed, and ambient temperature. For several cases the NASA in-house engine icing risk assessment code was used to find conditions that would lead to a rollback event. This study further helped NASA develop necessary icing diagnostic instrumentation, expand the capabilities of the Propulsion Systems Laboratory, and generate a dataset that will be used to develop and validate in-house icing prediction and risk mitigation computational tools. The ice accretion on the outer shroud region was acquired by internal video cameras. The heavily instrumented engine showed good repeatability of icing responses when compared to the key LF01 test points and during day-to-day operation. Other noticeable observations are presented.

Enigine Icing↗

NASA NTRS1997

Bayesian Blocks: A New Method to Analyze Photon Counting Data

A Bayesian analysis of photon-counting data leads to a new time-domain algorithm for detecting localized structures (bursts), revealing pulse shapes, and generally characterizing intensity variations. The raw counting data -- time-tag events (TTE), time-to-spill (TTS) data, or binned counts -- is converted to a maximum likelihood segmentation of the observation into time intervals during which the photon arrival rate is perceptibly constant -- i.e. has a fixed intensity without statistically significant variations. The resulting structures, Bayesian Blocks, can be thought of as bins with arbitrary spacing determined by the data. The method itself sets no lower limit to the time scale on which variability can be detected. We have applied the method to RXTE data on Cyg X-1, yielding information on this source's short-time-scale variability.

Scargle, Jeffrey D.↗

NASA NTRS2022

Observations of Particle Number Size Distributions and New Particle Formation in Six Indian Locations

Atmospheric new particle formation (NPF) is a crucial process driving aerosol number concentrations in the atmosphere; it can significantly impact the evolution of atmospheric aerosol and cloud processes. This study analyses at least 1 year of asynchronous particle number size distributions from six different locations in India. We also analyze the frequency of NPF and its contribution to cloud condensation nuclei (CCN) concentrations. We found that the NPF frequency has a considerable seasonal variability. At the measurement sites analyzed in this study, NPF frequently occurs in March–May (pre-monsoon, about 21 % of the days) and is the least common in October–November (post-monsoon, about 7 % of the days). Considering the NPF events in all locations, the particle formation rate (J_(SDS)) varied by more than 2 orders of magnitude (0.001–0.6 /cu.cm s) and the growth rate between the smallest detectable size and 25 nm (GR_(SDS-25 nm)) by about 3 orders of magnitude (0.2–17.2 nm/h). We found that JSDS was higher by nearly 1 order of magnitude during NPF events in urban areas than mountain sites. GRSDS did not show a systematic difference. Our results showed that NPF events could significantly modulate the shape of particle number size distributions and CCN concentrations in India. The contribution of a given NPF event to CCN concentrations was the highest in urban locations (4.3 × 10^(3) /cu.cm per event and 1.2 × 10^(3)/cu.cm per event for 50 and 100 nm, respectively) as compared to mountain background sites (2.7 × 10^(3)/cu.cm per event and 1.0 × 10^(3)/cu.cm per event, respectively). We emphasize that the physical and chemical pathways responsible for NPF and factors that control its contribution to CCN production require in situ field observations using recent advances in aerosol and its precursor gaseous measurement techniques.

particle number size distributions↗

NASA NTRSDate not supplied

Development of Machine Learning-Derived Microbiological and Immune Signatures: Applications in Adaptive Risk Assessment of Infectious Disease During Spaceflight

Infectious diseases represent an urgent risk for spaceflight with consequences ranging from loss in crew performance to crew incapacitation or loss of life should an outbreak occur. The resident environmental microbiome on the International Space Station has been monitored through routine surveillance over almost twenty years, beginning with culture-based microbial detection which has advanced to molecular methods in recent years. This has created a wealth of data that we have begun mining to define the microbial ecology of the ISS. Summarized here is our analysis of data from the historical microbial population defined by culture-based monitoring from the past two decades, organized by their likelihood to cause disease into clinical categories. As expected, many residents of the normal microflora in environments where people work and live were detected. However, some known pathogens were also detected. As the spaceflight environment can predispose humans to infection, crew health records were used to source additional data for the set to uncover clinical relevance. Data mining was performed on crew health records to capture adverse health events that may be related to infectious disease. Machine learning, specifically Random Forest analysis, was used to analyze the microbial and crew health datasets. The symptom categories were not explained by the ranked bacteria, due to lack of sufficient data for some categories and due to poor ranking of the pathogens for others. Poor ranking of the bacteria could be due to the clinical symptoms being linked to other disease-causing factors, such as allergy or viral infection. These findings suggest a lack of relationship between bacteria detected on surfaces in the ISS and historical health events experienced by astronauts.

Kristyn Hoffman↗

NASA NTRS2009

Determining the Detection Efficiency and Background Level of ATIC Electron Observation from Flight Data

Observations of Cosmic-ray electrons are difficult due to the large flux of cosmic ray hadrons. The event selection efficiency and background levels can be estimated from flight data for the ATIC instrument. This reduces the dependence upon Monte Carlo simulations, which show differences between different codes, thereby reducing the systematic errors resulting from analyses that only use simulations. This paper discusses some of the methods used in the ATIC analysis to determine the detection efficiency and background level for the flight data.

Chang, J.↗

NASA NTRS2014

Integration of RGB "Dust" Imagery to Operations at the Albuquerque Forecast Office

The NASA/Short‐term Prediction, Research, and Transition (SPoRT) Program has been providing unique Red‐Green‐Blue (RGB) composite imagery to its operational partners since 2005. In the early years of activity these RGB products were related to a True Color RGB, showing what one's own eyes would see if looking down at earth from space, as well as a Snow‐Cloud RGB (i.e. False Color), separating clouds from snow on the ground. More recently SPoRT has used the EUMETSAT Best Practices standards for RGB composites to transition a wide array of imagery for multiple uses. A "Dust" RGB product has had particular use at the Albuquerque, New Mexico WFO. Several cases have occurred where users were able to isolate dust plume locations for mesoscale and microscale events during day and night time conditions. In addition the "Dust" RGB can be used for more than just detection of dust as it is sensitive to the changes in density due to atmospheric moisture content. Hence low‐level dry boundaries can often be discriminated. This type of imagery is a large change from the single channel imagery typically used by operational forecast staff and hence, can be a challenge to interpret. This presentation aims to discuss the integration of such new imagery into operational use as well as the benefits assessed by the Albuquerque WFO over several documented events.

Fuell, Kevin↗

NASA NTRS2014

Integration of RGB "Dust" Imagery to Operations at the Albuqueque Forecast Office

Fuell, Kevin↗

NASA NTRS1994

Gamma-ray constraints on supernova nucleosynthesis

Gamma-ray spectroscopy holds great promise for probing nucleosynthesis in individual supernova explosions via short-lived radioactivity, and for measuring current global Galactic supernova nucleosynthesis with longer-lived radioactivity. It was somewhat surprising that the former case was realized first for a Type II supernova, when both Co-56 and Co-57 were detected in SN 1987A. These provide unprecedented constraints on models of Type II explosions and nucleosynthesis. Live Al-26 in the Galaxy might come from Type II supernovae, and if it is eventually shown to be so, can constrain massive star evolution, supernova nucleosynthesis, and the Galactic Type II supernova rate. Type Ia supernovae, thought to be thermonuclear explosions, have not yet been detected in gamma-rays. This is somewhat surprising given current models and recent Co-56 detection attempts. Ultimately, gamma-ray measurements can confirm their thermonuclear nature, probe the nuclear burning conditions, and help evaluate their contributions to Galactic nucleosynthesis. Type Ib/c supernovae are poorly understood. Whether they are core collapse or thermonuclear events might be ultimately settled by gamma-ray observations. Depending on details of the nuclear processing, any of these supernova types might contribute to a detectable diffuse glow of Fe-60 gamma-ray lines. Previous attempts at detection have come very close to expected emission levels. Remnants of any type of age less that a few centuries might be detectable as individual spots of Ti-44 gamma-ray line emission. It is in fact quite surprising that previous surveys have not discovered such spots, and the constraints on the combination of nucleosynthesis yields and supernova rates are very interesting. All of these interesting limits and possibilities mean that the next mission, International Gamma-Ray Astrophysics Laboratory (INTEGRAL), if it has sufficient sensitivity, is very likely to lead to the realization of much of the great potential of gamma-ray spectroscopy for understanding supernovae.

Leising, Mark D.↗

NASA NTRS1985

The Pioneer Venus Orbiter event of February 11, 1982 - Of cometary of solar origin?

On February 11, 1982, an unusual cusp-shaped temporal variation in the interplanetary magnetic field was detected by the Pioneer Venus orbiter. While variations of the helium content of the solar wind were detected on the preceding day, these changes had no obvious relationship to the occurrence of the cusp-shaped temporal variation in the IMF on February 11. In fact the solar wind the content was quite nominal on February 11. The magnetic variations were also quite unlike those previously reported to be magnetic clouds. Moreover, the scale size of the disturbance had to be smaller than 4 x 10 to the 6th km and thus of cometary dimensions rather than of dimensions usually found in solar initiated events. Thus, there seems to be no need to alter the original interpretation that the observations of Pioneer Venus on February 11, 1982 were consistent with the passage of a comet close to Venus.

Russell, C. T.↗