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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Gamma-Ray Urgent Archiver for Novel Opportunities (GUANO): Swift/BAT Event Data Dumps on Demand to Enable Sensitive Subthreshold GRB Searches

We introduce a new capability of the Neil Gehrels Swift Observatory to provide event-level data from the Burst Alert Telescope (BAT) on demand in response to transients detected by other instruments. We show that the availability of these data can effectively increase the rate of detections and arcminute localizations of gamma-ray bursts (GRB) like GRB 170817 by >400%. We describe an autonomous spacecraft-commanding pipeline purpose built to enable this science; to our knowledge, this is the first fully autonomous extremely low-latency commanding of a space telescope for scientific purposes. This pipeline has been successfully run in its complete form since 2020 January, and has resulted in the recovery of BAT event data for >800 externally triggered events to date (gravitational waves, GWs; neutrinos; GRBs triggered by other facilities; fast radio bursts; and very high-energy detections), now running with a success rate of ∼90%. We exemplify the utility of this new capability by using the resultant data to (1) set the most sensitive upper limits on prompt 1 s duration short GRB-like emission within ±15 s around the unmodeled GW burst candidate S200114f, and (2) provide an arcminute localization for short GRB 200325A and other bursts. We also show that using data from GUANO to localize GRBs discovered by other instruments, we can increase the net rate of arcminute-localized GRBs by 10%–20% per year. Along with the scientific yield of more sensitive searches for subthreshold GRBs, the new capabilities designed for this project will serve as the foundation for further automation and rapid target of opportunity capabilities for the Swift mission, and have implications for the design of future rapid-response space telescopes.

Aaron Tohuvavohu↗
NASA NTRS2019

The volumetric rate of normal type Ia supernovae in the local Universe discovered by the Palomar Transient Factory

We present the volumetric rate of normal type Ia supernovae (SNe Ia) discovered by the Palomar Transient Factory (PTF). Using strict data-quality cuts, and considering only periods when the PTF maintained a regular cadence, PTF discovered 90 SNe Ia at z ≤ 0.09 in a well-controlled sample over three years of operation (2010–2012). We use this to calculate the volumetric rate of SN Ia events by comparing this sample to simulations of hundreds of millions of SN Ia light curves produced in statistically representative realizations of the PTF survey. This quantifies the recovery efficiency of each PTF SN Ia event, and thus the relative weighting of each event. From this, the volumetric SN Ia rate was found to be r(v) = 2.43 ± 0.29 (stat)(+0.33,−0.19)(sys) × 10^(−5) SNe per yr Mpc^(-3) h(3,70). This represents the most precise local measurement of the SNIa rate. We fit a simple SNIa delay-time distribution model, ∝ t^(−β) , to our PTF rate measurement combined with a literature sample of rate measurements from surveys at higher redshifts. We find β ∼ 1, consistent with a progenitor channel governed by the gravitational inspiral of binary white dwarfs.

C. Frohmaier↗
DOE OSTI2024

Physical discovery in representation learning via conditioning on prior knowledge

Recent advances in electron, scanning probe, optical, and chemical imaging and spectroscopy yield bespoke data sets containing the information of structure and functionality of complex systems. In many cases, the resulting data sets are underpinned by low-dimensional simple representations encoding the factors of variability within the data. The representation learning methods seek to discover these factors of variability, ideally further connecting them with relevant physical mechanisms. However, generally, the task of identifying the latent variables corresponding to actual physical mechanisms is extremely complex. Here, we present an empirical study of an approach based on conditioning the data on the known (continuous) physical parameters and systematically compare it with the previously introduced approach based on the invariant variational autoencoders. The conditional variational autoencoder (cVAE) approach does not rely on the existence of the invariant transforms and hence allows for much greater flexibility and applicability. Interestingly, cVAE allows for limited extrapolation outside of the original domain of the conditional variable. However, this extrapolation is limited compared to the cases when true physical mechanisms are known, and the physical factor of variability can be disentangled in full. We further show that introducing the known conditioning results in the simplification of the latent distribution if the conditioning vector is correlated with the factor of variability in the data, thus allowing us to separate relevant physical factors. We initially demonstrate this approach using 1D and 2D examples on a synthetic data set and then extend it to the analysis of experimental data on ferroelectric domain dynamics visualized via piezoresponse force microscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Gravitational Lenses in UNIONS and Euclid (GLUE). I. A Search for Strong Gravitational Lenses in UNIONS with Subaru, CFHT, and Pan-STARRS Data

We present the results of our pipeline for discovering strong gravitational lenses in the ongoing Ultraviolet Near-Infrared Optical Northern Survey (UNIONS). We successfully train a deep residual convolutional neural network based on CMU-Deeplens architecture, which is designed to detect strong lenses in ground-based imaging surveys. We train on images of real strong lenses and deploy on a sample of 8 million galaxies in areas with full coverage in the g, r, and i filters—the first multiband search for strong gravitational lenses in UNIONS. Following human inspection and grading, we report the discovery of a total of 1346 new strong-lens candidates, of which 146 are Grade A, 199 are Grade B, and 1001 are Grade C. Of these candidates, 283 have lens galaxy spectroscopic redshifts from the Sloan Digital Sky Survey, and an additional 297 have them from the Dark Energy Spectroscopic Instrument Data Release 1. We find 15 of these systems display evidence of both lens and source galaxy redshifts in spectral superposition. We also report the spectroscopic confirmation of seven lensed sources in high-quality systems, all with z > 2.1, using the Keck Near Infrared Echellette Spectrograph and the Gemini Near-Infrared Spectrograph.

Storfer, Christopher J. [University of Hawaii, Hon↗
NASA NTRS2000

Climate and infectious disease: use of remote sensing for detection of Vibrio cholerae by indirect measurement

It has long been known that cholera outbreaks can be initiated when Vibrio cholerae, the bacterium that causes cholera, is present in drinking water in sufficient numbers to constitute an infective dose, if ingested by humans. Outbreaks associated with drinking or bathing in unpurified river or brackish water may directly or indirectly depend on such conditions as water temperature, nutrient concentration, and plankton production that may be favorable for growth and reproduction of the bacterium. Although these environmental parameters have routinely been measured by using water samples collected aboard research ships, the available data sets are sparse and infrequent. Furthermore, shipboard data acquisition is both expensive and time-consuming. Interpolation to regional scales can also be problematic. Although the bacterium, V. cholerae, cannot be sensed directly, remotely sensed data can be used to infer its presence. In the study reported here, satellite data were used to monitor the timing and spread of cholera. Public domain remote sensing data for the Bay of Bengal were compared directly with cholera case data collected in Bangladesh from 1992-1995. The remote sensing data included sea surface temperature and sea surface height. It was discovered that sea surface temperature shows an annual cycle similar to the cholera case data. Sea surface height may be an indicator of incursion of plankton-laden water inland, e.g., tidal rivers, because it was also found to be correlated with cholera outbreaks. The extensive studies accomplished during the past 25 years, confirming the hypothesis that V. cholerae is autochthonous to the aquatic environment and is a commensal of zooplankton, i.e., copepods, when combined with the findings of the satellite data analyses, provide strong evidence that cholera epidemics are climate-linked.

Cholera/epidemiology↗
NASA NTRS2022

Multidecadal Trends in Ozone Chemistry in the Baltimore-Washington Region

Over the past four decades, policy-led reductions in anthropogenic emissions have improved air quality over the Baltimore-Washington region (BWR). Most of the improvements in meeting the ozone air quality metrics (NAAQS) did not occur until the early 2000s despite large reductions in ozone precursors (NOx, CO, and volatile organic compounds (VOCs)) in the prior decades. We use observations of ozone and ozone precursors from satellites, ground-based sites, and the 2011 DISCOVER-AQ aircraft campaign in Maryland to illustrate how ozone chemistry in the BWR evolved between 1972 and 2019. Analysis of weekday vs weekend probability of ozone exceedance indicates the BWR transitioned to the NOx-limited regime by 2000–2003. A data-constrained box model agrees with this transition period and illustrates the key roles of reduced emissions of formaldehyde (HCHO), aromatics, and other VOCs since 1996, which reduced the peak of ozone production at the time of the transition and likely prevented the BWR from experiencing worsening surface air quality as the region transitioned to NOx-limited chemistry. Analysis of satellite observations of tropospheric column HCHO to NO2 analyzed using a new approach for evaluation of chemical regimes derived from DISCOVER-AQ data also provide a consistent depiction of the timing of the transition period that we infer from ground-based observations and the box model. Finally, despite significant improvements in air quality over the past two decades, the BWR still has not met the EPA standard for surface ozone. With predominantly NOx-limited ozone chemistry over the BWR, continued decreases in emission of NOx will slow the rate of ozone production and help improve air quality. We highlight emissions of NO2 from the diesel truck fleet as a worthwhile focus for future policy because emissions from this source appear to influence day-of-week variations in observed NO2, with an accompanying effect on ozone.

Ozone↗
DOE OSTI2024

Data Based Shock Test Specification

It is vital that avionic packages used for testing and certifying the reliability and safety of U.S. nuclear weapons with platform aircraft survive exposure to shock environments during transportation and delivery. The objective of this research was to characterize the response to these transportation shock environments delivering accurate shock test specifications in order to set laboratory programming material and device certification rigor. Responses to shock events were analyzed in the frequency domain via the Shock Response Spectrum (SRS). Shocks were then grouped based on respective behavior of maximum response accelerations which were pseudorandomly resampled and compared to test data to form test specifications based on the MinerPalmgren hypothesis. In addition to discovering significant over testing in current shock specifications, a new systematic, data-driven approach to designing shock specifications was formulated.

42 ENGINEERING↗
DOE OSTI2024

Linking Spatiotemporal Biological Data to Predict Harmful Algal Blooms

Cyanobacterial Harmful Algal Blooms (cHABs) have significant impacts on an affected region’s economy, ecology, and human health. The blooms can release toxins that kill fish and poison water for people and animals. The global adverse effects of cHABs are exacerbated by the consequences of climate change and increased pollution. Though the phenomena are well documented, scientists’ efforts to mitigate the damage are hampered by insufficient predictive models and incomplete granular knowledge of cHAB community structure. With a goal of leveraging bioinformatics and machine learning tools to better understand and predict cHABs, we are first exploring water sample data sets. Using nearly four thousand samples from the National Center for Biotechnology Information Sequence Read Archive (NCBI-SRA) across 16 years with latitude and longitude embedded in the metadata, we mapped the location of the samples onto a Lake Erie shape file. We combined information about location, date, and community taxa in the NCBI samples to discover factors that determine cHAB features. The data are separated into three distinct zones, with the majority pooled at the southwest end of the lake and occurring in 2017. The samples are rich in biological data; our next steps are to carry out whole genome sequence analysis and use the community profiles as part of our predictive machine learning model.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Study on spectral/radiometric characteristics of the Thematic Mapper for land use applications

Progress under the LANDSAT-4 and 5 Image Data Quality Assessment program for the Thematic Mapper is described. An initial screening of LANDSAT-5 data is performed. Tools are developed to allow access to TIPS-format data. Analysis of scan direction related signal droop is resumed with detailed analysis of nighttime data. A new mathematical model is developed to describe the effect. Coherent noise of a lower frequency than previously reported is discovered and analyzed. Coincident LANDSAT-4 TM and MSS data are analyzed to improve understanding of radiometric relationships between similar wavebands in the two sensors.

Malila, W. A.↗
NASA NTRS1981

Analysis of DSN software anomalies

A categorized data base of software errors which were discovered during the various stages of development and operational use of the Deep Space Network DSN/Mark 3 System was developed. A study team identified several existing error classification schemes (taxonomies), prepared a detailed annotated bibliography of the error taxonomy literature, and produced a new classification scheme which was tuned to the DSN anomaly reporting system and encapsulated the work of others. Based upon the DSN/RCI error taxonomy, error data on approximately 1000 reported DSN/Mark 3 anomalies were analyzed, interpreted and classified. Next, error data are summarized and histograms were produced highlighting key tendencies.

Galorath, D. D.↗
NASA NTRSDate not supplied

Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)

The scientific community is faced with a need for greatly improved data sharing, analysis, visualization and advanced collaboration based firmly on open science principles. Recent and upcoming launches of new satellite missions with more complex and voluminous data, as well as the ever more urgent need to better understand the global carbon budget and related ecological processes, provided the immediate rational for the ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP). This highly collaborative joint project of ESA and NASA established a framework between ESA and NASA to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by ESA and NASA EO data users. Presented to the public in October 2021, the current version of MAAP provides a common cloud-based platform with computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of global above-ground biomass. Data from the Global Ecosystem Dynamics Investigation (GEDI) mission on the International Space Station and the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) have been instrumental in the first products of MAAP including the first comprehensive map of Boreal above-ground Biomass and a current Global Biomass Harmonization Activity, but the platform is also being specifically designed to support the forthcoming ESA Biomass mission and incorporate data from the upcoming NASA-ISRO SAR (NISAR) mission. While these missions and the corresponding research which includes airborne, field, and calibration/validation data collection and analyses, provide a wealth of data and information relating to global biomass estimation, they also present data storing, processing and sharing challenges. The NISAR mission alone will produce about 80TB/day. These large data volumes present a challenge that would otherwise place accessibility limits on the scientific community and impact scientific progress. Other challenges being addressed by MAAP include: 1) Enabling researchers to easily discover, process, visualize and analyze large volumes of data from both agencies; 2) Providing a wide variety of data in the same coordinate reference frame to enable comparison, analysis, data evaluation, and data generation; 3) Providing a version-controlled science algorithm development environment that supports tools, co-located data and processing resources; and 4) Addressing intellectual property and sharing challenges related to collaborative algorithm development and sharing of data and algorithms. MAAP products can be explored on the MAAP Dashboard at https://earthdata.nasa.gov/maap-biomass or the joint platform entrance at scimaap.net. MAAP also can be accessed through individual NASA (https://maap-project.org) and ESA (https://esa-maap.org/) landing pages.

cloud computing↗
NASA NTRS2015

Supercomputing in the Age of Discovering Superearths, Earths and Exoplanet Systems

With the Kepler Mission, exoplanet science has entered the era of Big Data and has benefited tremendously from the availability of the NAS (NASA Advanced Supercomputing Division) Pleiades supercomputer. This presentation provides an overview of the history of exoplanet discoveries and highlights the key enabling technologies for Kepler. I provide an overview of the Kepler science pipeline and the algorithms used to analyze the data and detect transiting planets, all of which run routinely on the NAS Pleiades system. The presentation also provides a description of the Blender analysis program used to validate Kepler planet discoveries statistically, and the effort to discover exomoons lurking in Kepler data, both of which also run on Pleiades. Finally, I describe NASA's TESS (Transiting Exoplanet Survey Satellite) Mission, which leverages Kepler heritage to provide a science pipeline similar to that for Kepler and that will also run routinely on the NAS Pleiades supercomputer.

big data↗
NASA NTRS1998

Discover Earth

Discover Earth is a NASA-sponsored project for teachers of grades 5-12, designed to: (1) enhance understanding of the Earth as an integrated system; (2) enhance the interdisciplinary approach to science instruction; and (3) provide classroom materials that focus on those goals. Discover Earth is conducted by the Institute for Global Environmental Strategies in collaboration with Dr. Eric Barron, Director, Earth System Science Center, The Pennsylvania State University; and Dr. Robert Hudson, Chair, the Department of Meteorology, University of Maryland at College Park. The enclosed materials: (1) represent only part of the Discover Earth materials; (2) were developed by classroom teachers who are participating in the Discover Earth project; (3) utilize an investigative approach and on-line data; and (4) can be effectively adjusted to classrooms with greater/without technology access. The Discover Earth classroom materials focus on the Earth system and key issues of global climate change including topics such as the greenhouse effect, clouds and Earth's radiation balance, surface hydrology and land cover, and volcanoes and climate change. All the materials developed to date are available on line at (http://www.strategies.org) You are encouraged to submit comments and recommendations about these materials to the Discover Earth project manager, contact information is listed below. You are welcome to duplicate all these materials.

Steele, Colleen↗
NASA NTRS1988

Evidence for beaming of Jupiter's decametric radiation - Simultaneous observations from Voyagers and ground-based observatories

Incontrovertible evidence is presented for the beaming of the Jovian decametric radiation, based on simultaneous observations at about 22 MHz from one or both of the Voyager spacecraft and one or the other of two ground-based observatories. The data are used to test the hollow-cone beaming models that have been proposed to account both for the long term statistics of the ground-based observations and for the arc structures discovered in the dynamic spectral plots of Voyager data. It is concluded that occurrences of non-Io-related Source A events are determined by the corotation with the inner Jovian magnetosphere of curved-sheet beams, and those of Io-related Source B storms by a similar type of beam that moves with the northern foot of the Io flux tube. Both types of beam can be approximated by hollow-cone beam sectors.

Maeda, Koitiro↗
NASA NTRS1987

Evidence for beaming of Jupiter's decametric radiation - Simultaneous observations from Voyagers and ground-based observatories

The paper presents incontrovertible evidence for the beaming of the Jovian decametric radiation, based on simultaneous observations at about 22 MHz from one or both of the Voyager spacecraft and one or the other of two ground-based observatories. The data are used to test the hollow-cone beaming models that have been proposed to account both for the long-term statistics of the ground-based observations and for the arc structures discovered in the dynamic spectral plots of Voyager data. It is concluded that occurrences of non-Io-related Source A events are determined by the corotation with the inner Jovian magnetosphere of curved-sheet beams, and those of Io-related Source B storms by a similar type of beam that moves with the northern foot of the Io flux tube. Both types of beam can be approximated by hollow-cone beam sectors. Rough measurements of the observed portions of some of the beams have been made.

Maeda, Koitiro↗
NASA NTRS1989

Application of satellite visible band data to high latitude oceans

Freshwater discharge in the Northeast Pacific contains very fine sediments that can be detected using Landsat Thematic Mapper (TM) and Multi-spectral Scanner (MSS) imagery. From the TM data, several new coastal circulation features were discovered in the northern Gulf of Alaska. Flow around a coastal island produces a myriad of dipole eddies which are important to the cross-shelf transport of salt and heat. They also serve as sites to test numerical models to allow a better understanding of coastal flows and eddy formation elsewhere. Detection of these dipole eddies from their sediment distributions has allowed the comparison of different spectral bands from six imaging satellite sensors for their abilities to describe these features. It is concluded that, in addition to the TM sensor's capability, the sediments can be detected with MSS and CZCS sensors, but not with AVHRR or DMSP. As a consequence of this comparison of satellite visible data, it is confirmed that the dipole eddies here exist under low flow conditions (less than 1000 cu m/sec).

Ahlnas, Kristina↗
NASA NTRS1983

Application of Heat Capacity Mapping Mission data to regional geologic analysis for mineral and energy resource evaluation

Heat Capacity Mapping Mission thermal-inertia images of a diversity of terrains and geologic settings were examined in conjunction with topographic, geologic, geophysical, and LANDSAT data. The images were found to have attributes similar to bedrock maps. In the Cascades region, two new features were identified and a method was developed to characterize regional terranes using linear feature data. Two northeast-trending Lineaments were discovered in the Overthrust Belt of Montana and Idaho. The longer of the two extends from the Idaho-Oregon border, through the Idaho batholith and across the Lewis thrust. It coincides, along segments, with mapped faults and an aeromagnetic pattern change. A major lineament crossing the Colorado Plateau and the Southern Rocky Mountians was detected on several thermal-inertial images and evidence was found for the existence of a geologic discontinuity. Vegetation-covered areas in Richfield and the Silver City quadrangle (Arizona and New Mexico) displayed thermal-inertia differences within heavily vegetation areas although no apreciable correlation was found between vegetation cover and thermal inertia. Resistant ridges and knolls have high thermal inertias and thermal-inertia contrasts occurred at lithologic and fault contacts. In the heavy vegetated Pinaleno Mountains, Arizona, a Lithologic unit obscured on LANDSAT MSS data due to the vegetation cover, exhibited a thermal-inertia contrast with its surroundings.

Watson, K.↗
NASA NTRS2004

More Far-Side Deep Moonquake Nests Discovered

As reported last year, we started to reanalyze the seismic data acquired from 1969 to 1977 with a network of stations established on the Moon during the Apollo mission. The reason for the reanalysis was because recent advances in computer technology make it possible to employ much more sophisticated analysis techniques than was possible previously. The primary objective of the reanalysis was to search for deep moonquakes on the far side of the Moon and, if found, to use them to infer the structure of the Moon's deep interior, including a possible central core. The first step was to identify any new deep moonquakes that escaped our earlier search by applying a combination of waveform cross-correlation and single-link cluster analysis, and then to see if any of them are from previously unknown nests of deep moonquakes. We positively identified 7245 deep moonquakes, more than a five-fold increase from the previous 1360. We also found at least 88 previously unknown deep-moonquake nests. The question was whether any of these newly discovered nets were on the far side of the Moon, and we now report that our analysis of the data indicates that some of them are indeed on the far side.

Nakamura, Y.↗