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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 307 records · Page 17

Comparison of Ground-Based 3-Dimensional Lightning Mapping Observations with Satellite-Based LIS Observations in Oklahoma: Comparison of LMS and LIS Lightning Mapping

3-dimensional lightning mapping observations obtained during the MEaPRS program in central Oklahoma during June, 1998 have been compared with observations of the discharges from space, obtained by NASA's Lightning Imaging Sensor (LIS) on the TRMM satellite. Excellent spatial and temporal correlations were observed between the two sets of observations. Most of the detected optical events were associated with intracloud discharges that developed into the upper part of the storm. Cloud-to-ground discharges that were confined to mid- and lower-altitudes tended not to be detected by LIS. Extensive illumination tended to occur in impulsive bursts toward the end or part way through intracloud flashes and appeared to be produced by energetic K-changes that typically occur at these times.

Thomas, Ronald J.↗

Single-Event Effect Testing of the Linear Technology LTC6103HMS8#PBF Current Sense Amplifier

The LTC6103HMS8#PBF (henceforth abbreviated as LTC6103) current sense amplifier from Linear Technology was tested for both destructive and non-destructive single-event effects (SEE) using the heavy-ion cyclotron accelerator beam at Lawrence Berkeley National Laboratory (LBNL) Berkeley Accelerator Effects (BASE) facility. During testing, the input voltages and output currents were monitored to detect single event latch-up (SEL) and single-event transients (SETs).

single-event effects (SEE)↗

Space-Based Remote Imaging Spectroscopy of the Aliso Canyon CH4 Superemitter

The Aliso Canyon gas storage facility near Porter Ranch, California, produced a large accidental CH4 release from October 2015 to February 2016. The Hyperion imaging spectrometer on board the EO-1 satellite successfully detected this event, achieving the first orbital attribution of CH4 to a single anthropogenic superemitter. Hyperion measured shortwave infrared signatures of CH4 near 2.3 microns at 0.01 micron spectral resolution and 30 meter spatial resolution. It detected the plume on three overpasses, mapping its magnitude and morphology. These orbital observations were consistent with measurements by airborne instruments. We evaluate Hyperion instrument performance, draw implications for future orbital instruments, and extrapolate the potential for a global survey of CH4 superemitters.

Thompson, D. R.↗

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗

Measurements of the reaction e/+/e/-/ yielding gamma-gamma at center-of-mass energies in the range 6.2-7.4 GeV

The cross section for the pair-annihilation reaction e(+)e(-) yields gamma-gamma were measured at center-of-mass energies in the range 6.2-7.4 GeV and at production angles close to 90 deg. The experimental apparatus consisted of two identical spectrometers which were set to view the luminous region at SPEAR-II from opposite directions at an azimuthal angle of 45 deg. In each spectrometer there was a NaI(TI) crystal 20 radiation lengths thick and 30 in. in diameter to measure the gamma-ray energies. Annihilation events were detected by an electronic trigger which required only the observation in coincidence of more than 0.2 GeV in each NaI(TI) crystal within + or - 15 nsec of the crossing beams. The observed rates of pair-annihilation events were found to be in agreement with those expected from quantum electrodynamics (QED) at all the center-of-mass energies used.

Hilger, E.↗

Hypermut 3: identifying specific mutational patterns in a defined nucleotide context that allows multistate characters

Abstract Motivation The detection of APOBEC3F- and APOBEC3G-induced mutations in virus sequences is useful for identifying hypermutated sequences. These sequences are not representative of viral evolution and can therefore alter the results of downstream sequence analyses if included. We previously published the software Hypermut, which detects hypermutation events in sequences relative to a reference. Two versions of this method are available as a webtool. Neither of these methods consider multistate characters or gaps in the sequence alignment. Results Here, we present an updated, user-friendly web and command-line version of Hypermut with functionality to handle multistate characters and gaps in the sequence alignment. This tool allows for straightforward integration of hypermutation detection into sequence analysis pipelines. As with the previous tool, while the main purpose is to identify G to A hypermutation events, any mutational pattern and context can be specified. Availability and implementation Hypermut 3 is written in Python 3. It is available as a command-line tool at https://github.com/MolEvolEpid/hypermut3 and as a webtool at https://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermutv3.html.

59 BASIC BIOLOGICAL SCIENCES↗

Calculating the Motion and Direction of Flux Transfer Events with Cluster

We use multi-point timing analysis to determine the orientation and motion of flux transfer events (FTEs) detected by the four Cluster spacecraft on the high-latitude dayside and flank magnetopause during 2002 and 2003. During these years, the distances between the Cluster spacecraft were greater than 1000 km, providing the tetrahedral configuration needed to select events and determine velocities. Each velocity and location will be examined in detail and compared to the velocities and locations determined by the predictions of the component and antiparallel reconnection models for event formation, orientation, motion, and acceleration for a wide range of spacecraft locations and solar wind conditions.

Collado-Vega, Yaireska M.↗

Calculating the Motion and Direction of Flux Transfer Events with Cluster

For many years now, the interactions of the solar wind plasma with the Earth's magnetosphere has been one of the most important problems for Space Physics. It is very important that we understand these processes because the high-energy particles and also the solar wind energy that cross the magneto sphere could be responsible for serious damage to our technological systems. The solar wind is inherently a dynamic medium, and the particles interaction with the Earth's magnetosphere can be steady or unsteady. Unsteady interaction include transient processes like bursty magnetic reconnection. Flux Transfer Events (FTEs) are magnetopause signatures that usually occur during transient times of reconnection. They exhibit bipolar signatures in the normal component of the magnetic field. We use multi-point timing analysis to determine the orientation and motion of ux transfer events (FTEs) detected by the four Cluster spacecraft on the high-latitude dayside and flank magnetopause during 2002 and 2003. During these years, the distances between the Cluster spacecraft were greater than 1000 km, providing the tetrahedral configuration needed to select events and determine velocities. Each velocity and location will be examined in detail and compared to the velocities and locations determined by the predictions of the component and antiparallel reconnection models for event formation, orientation, motion, and acceleration for a wide range of spacecraft locations and solar wind conditions.

Collado-Vega, Y. M.↗

Wideband noise observed at ground level in the auroral region

A sideband noise event was detected at ground level from the Andoya Rocket Range in Norway in January 1989. The signals were observed on four commercial communication receivers (tuned to 159, 515, 905, and 1200 kHz), an ionosonde (200-kHz to 3.5-MHz interference-free observations) and a riometer (32.5 MHz). The event, which occurred during a period of magnetic disturbance near magnetic midnight, was the only one observed during nearly 3 weeks of operations. This low frequency-of-occurrence is attributed partly to high local noise levels. The ease with which this event was identified on the ionograms produced by the local ionosonde suggests that routine ionosonde recordings should be inspected in search for such events. Such an effort would enhance existing research directed toward developing techniques for identifying quiet communication channels and help to identify the origin and frequency-of-occurrence of high-latitude wideband noise events.

Benson, Robert F.↗

GRUMDN: A Multi-Task Model for Predicting Human Patterns-of-Life from Stay Transition Data

Understanding human patterns-of-life (PoL) is essential towards ensuring safe and secure indoor facility environment as well as outdoor urban environment. Prediction of human movement in between places of interest is vital in understanding human PoL. Movement between spaces maybe represented and detected in one of the two forms: 1) trajectories: locations measured at regular time intervals by mobile sensors, bluetooth or GPS sensors; or 2) stay transitions: semantic PoI (points of interest) and stay duration data measurable by eventbased sensors that collect data when a check-in or check-out event is detected. Stay transition data provides a more compressed data format compared to trajectories data, especially in situations with longer stay durations, while preserving the information necessary for PoL analysis. Now as introduced briefly in the paper, our deployed end application (Digital Twin of a facility with non-player characters, besides the interactive user in virtual reality) needed a well-performing and validated AI/ML model for simulating high quality stay transitions behavior. In this study we thus primarily present our findings with developing and validating that model, which is a multi-task neural network for stay transition prediction. The neural network consists of two heads, for corresponding two tasks of stay category prediction and stay duration prediction. We evaluated gated recurrent units and multi-layer perceptrons of varying network sizes for stay category prediction; while mixture density networks, noisy generator-only networks, and generative adversarial networks of varying network sizes for stay duration prediction. We have then evaluated four multi-task models, constructed by combining these specialized models, on their ability to predict stay transition data. We tested our models on datasets from two different cases: 1) a simulation-generated dataset of indoor movement within the HFIR (high flux isotope reactor) nuclear reactor facility at Oak Ridge National Laboratory (ORNL); and 2) the GeoLife human mobility dataset of outdoor urban movement available in literature. Our results indicate that GRUMDN, which combines gated recurrent units (GRU) for stay category prediction task, and mixture density networks (MDN) for stay duration prediction task, did overall outperform other multitask models and the current state-of-the-art.

Gunaratne, Chathika [ORNL] (ORCID:0000000225088745↗

Method and apparatus for assessing cardiovascular risk

The method for assessing risk of an adverse clinical event includes detecting a physiologic signal in the subject and determining from the physiologic signal a sequence of intervals corresponding to time intervals between heart beats. The long-time structure of fluctuations in the intervals over a time period of more than fifteen minutes is analyzed to assess risk of an adverse clinical event. In a preferred embodiment, the physiologic signal is an electrocardiogram and the time period is at least fifteen minutes. A preferred method for analyzing the long-time structure variability in the intervals includes computing the power spectrum and fitting the power spectrum to a power law dependence on frequency over a selected frequency range such as 10.sup.-4 to 10.sup.-2 Hz. Characteristics of the long-time structure fluctuations in the intervals is used to assess risk of an adverse clinical event.

Albrecht, Paul↗

Tanami Blazars in the IceCube Pev Neutrino Fields

The IceCube Collaboration has announced the discovery of a neutrino flux in excess of the atmospheric background. Owing to the steeply falling atmospheric background spectrum, events at PeV energies most likely have an extraterrestrial origin. We present the multiwavelength properties of the six radio-brightest blazars that are positionally coincident with these events using contemporaneous data of the TANAMI blazar sample, including high-resolution images and spectral energy distributions. Assuming the X-ray to γ-ray emission originates in the photoproduction of pions by accelerated protons, the integrated predicted neutrino luminosity of these sources is high enough to explain the two detected PeV events.

TANAMI↗

The Atacama Cosmology Telescope: Systematic Transient Search of Single Observation Maps

We conduct a systematic search for astrophysical transients using data from the Atacama Cosmology Telescope. The data were taken from 2017 to 2022 in three frequency bands spanning 77 to 277 GHz. In this paper, we present a pipeline for transient detection using single-observation maps where each pixel of a map contains one observation with an integration time of approximately 4 minutes. We detect 34 transient events at 27 unique locations. All but two of the transients are associated with Galactic stars and exhibit a wide range of properties. We also detect an event coincident with the classical nova YZ Ret and one event consistent with a flaring active galactic nucleus. We notably do not detect any reverse shock emission from gamma-ray bursts, a nondetection that may be in tension with current models.

79 ASTRONOMY AND ASTROPHYSICS↗

Highland Lakes Water Resources: Using NASA Earth Observations to Improve Detection Systems for Harmful Algal Events in the Highland Lakes in Central Texas

Beginning in 2019, harmful algal events in Austin, Texas, caused canine deaths in the Lady Bird Lake and Lake Travis reservoirs. These reservoirs are part of the larger Highland Lakes chain, managed by the Lower Colorado River Authority (LCRA) and the City of Austin Department of Watershed Protection (CoA DWP), which fulfill municipal, commercial, and agricultural water demands. Given the recent increase in favorable algal event conditions in central Texas, the LCRA and CoA DWP partnered with NASA DEVELOP to improve algal event early-warning systems through the application of remote sensing and machine learning. An Earth observation-based algal monitoring system will assist the responsible agencies in predicting algal conditions and communicating hazards to the public. The NASA DEVELOP team utilized Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data to produce products including chlorophyll-a concentrations, cyanobacteria detections, turbidity, and water surface temperature. Chlorophyll-a concentrations were retrieved with a pre-trained machine learning model (mixture density network) and spectral indices, while the other products were derived from spectral indices. In situ field data were used to validate and quantify uncertainties for each product. The validations show strong correlations for chlorophyll-a and water surface temperature. Time series analyses of chlorophyll-a concentrations show peaks in the severe drought years (2015 and 2016). This project's resulting products enable monitoring of environmental proxies relevant to algal event presence in the Highland Lakes chain and will ultimately support water management, decision making, and risk communication.

Kaitlynn Hietpas↗

Radio Frequency Sensor: Very High Frequency Radio Frequency Lightning Detection in Geostationary Orbit

Abstract The Radio Frequency Sensor (RFS), a new radio frequency lightning detector, was launched into geosynchronous orbit in December 2021, and first collected data in January 2022. RFS is a specialized software‐defined radio receiver that detects, records, and reports impulsive broadband radio‐frequency (RF) signatures from lightning in the very high frequency (VHF; 30–300 MHz) range. Its vantage point from a Western hemisphere geosynchronous orbit provides unique opportunities to study evolution of RF lightning signatures over the durations of thunderstorms over the Americas and Pacific Ocean. Its overlapping view with the Geostationary Lightning Mappers (GOES‐16 & 17) enables additional comparisons between the sources of optical emissions and associated VHF emissions that were not possible with previous sensors. We find that RFS preferentially detects bright VHF signals called transionospheric pulse pairs (trans‐ionospheric pulse pairs (TIPPs)). It is estimated that more than 85% of the RFS‐detected lightning events are TIPPs. This paper presents initial results from the first year and a half of on‐orbit operation.

54 ENVIRONMENTAL SCIENCES↗

Advanced Ge detectors for gamma-ray astronomy

Externally segmented coaxial detectors are fabricated for high efficiency in detecting gamma rays from cosmic sources with good sensitivities. The external background is reduced by enclosing the Ge detector array inside a thick active shield. The outer electrode of the coaxial detectors is subdivided into five segments, and internal beta activity is rejected by operating the segmented detector in a multisegment mode. The multisegment mode requires that events be detected in two or more segments before they are recorded. The full-energy-peak (FEP) efficiency of the unit is tested as a function of the incident gamma-ray energy and of the discriminator threshold of the segments. Measurements of beta-rejection and FEP efficiency are compared with Monte Carlo calculations, and good agreement is noted.

Varnell, Larry S.↗

Permanent GPS Geodetic Array in Southern California

The southern California Permanent GPS Geodetic Array (PGGA) was established in the spring of 1990 to evaluate continuous Global Positioning System (GPS) measurements as a new too] for monitoring crustal deformation. Southern California is an ideal location because of the relatively high rate of tectonic deformation, the high probability of intense seismicity, the long history of conventional and space geodetic measurements, and the availability of a well developed infrastructure to support continuous operations. Within several months of the start of regular operations, the PGGA recorded far-field coseismic displacements induced by the June 28, 1992 (M(sub w)=7.3), Landers earthquake, the largest magnitude earthquake in California in the past 40 years and the first one to be recorded by a continuous GPS array. Only nineteen months later, on 17 January 1994, the PGGA recorded coseismic displacements for the strongest earthquake to strike the Los Angeles basin in two decades, the (M(sub e)=6.7) Northridge earthquake. At the time of the Landers earthquake, only seven continuous GPS sites were operating in southern California; by the beginning of 1994, three more sites had been added to the array. However, only a pair of sites were situated in the Los Angeles basin. The destruction caused by the Northridge earthquake spurred a fourfold increase in the number of continuous GPS sites in southern California within 2 years of this event. The PGGA is now the regional component of the Southern California Integrated GPS Network (SCIGN), a major ongoing densification of continuous GPS sites, with a concentration in the Los Angeles metropolitan region. Continuous GPS provides temporally dense measurements of surface displacements induced by crustal deformation processes including interseismic, coseismic, postseismic, and aseismic deformation and the potential for detecting anomalous events such as preseismic deformation and interseismic strain variations. Although strain meters yield much higher short-term resolution to a period of about 1 year, a single continuous GPS site is significantly less expensive than a single strain meter and probably has better long-term stability beyond a 1-year period. Compared to less frequent field measurements, continuous GPS provides the means to better characterize the errors in GPS position measurements and thereby obtain more realistic estimates of derived parameters such as site velocities.

Green, Cecil H.↗