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At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Evaluating the role of green infrastructure features in post-disaster recovery – Case Study of Beaumont, Texas after tropical storm imelda

While green infrastructure (GI) can provide multiple environmental benefits, its role in post-disaster economic and social recovery remains relatively underexplored. This article investigates whether different characteristics of GI, such as size, shape, connectivity, and amenities, affect the resilience of local businesses following Tropical Storm Imelda in Beaumont, Texas. The study utilizes SafeGraph mobility data to analyze foot traffic patterns to local businesses before, during, and after the disaster. FRAGSTATS indices measure GI characteristics (e.g., area, shape index, fractal dimension, proximity) while park features such as sports facilities, playgrounds, water features, and accessibility are cataloged through manual observation. Ordinary Least Squares regression models assess the relationship between park characteristics and post-recovery business performance, controlling for demographic variables including income, race, and poverty levels. Results indicate that certain GI attributes significantly enhance business recovery. Points of interest within walking distance (0.5 miles) of parks demonstrated better post-recovery status compared to those beyond this range. Specifically, parks with larger areas (p < 0.01) and more complex shapes measured by fractal dimension index (p < 0.01) had the strongest positive impact on surrounding businesses' recovery. Interestingly, playgrounds showed a negative correlation with recovery (p < 0.05), likely due to flood damage rendering them unusable during the immediate recovery period. Social vulnerability factors, including higher poverty rates and minority populations, negatively affected recovery outcomes despite park proximity.

Economic resilience↗
NASA NTRS1976

Classification software technique assessment

A catalog of software options is presented for the use of local user communities to obtain software for analyzing remotely sensed multispectral imagery. The resources required to utilize a particular software program are described. Descriptions of how a particular program analyzes data and the performance of that program for an application and data set provided by the user are shown. An effort is made to establish a statistical performance base for various software programs with regard to different data sets and analysis applications, to determine the status of the state-of-the-art.

Jayroe, R. R., Jr.↗
NASA NTRS1982

Comments on the gamma-ray burst catalog of Mazets et al. /1981a/

A correlation has been discovered between the Venera spacecraft locations and the gamma-ray burst positions reported in the KONUS catalog (Mazets et al., 1981a). The reason for the correlation is not clear, but it could be due to spatial selection effects and/or large localization errors for weak or soft bursts. Whatever the cause, it seems likely that this systematic bias might significantly affect catalog results pertaining to gamma burst locations, intensity distributions, and spectra. For example, it can explain why the KONUS galactic latitude distribution is peaked significantly south of the galactic equator. Apparent discrepanices between the KONUS and Los Alamos gamma burst data bases are noted.

Laros, J. G.↗
NASA NTRS2016

DiskDetective.org: Finding Homes for Exoplanets Through Citizen Science

The Disk Detective project is scouring the data archive from the WISE all-sky survey to find new debris disks and protoplanetary disks-the dusty dens where exoplanets form and dwell. Volunteers on this citizen science website have already performed 1.6 million classifications, searching a catalog 8x the size of any published WISE survey. We follow up candidates using ground based telescopes in California, Arizona, Chile, Hawaii, and Argentina. We ultimately expect to increase the pool of known debris disks by approx. 400 and triple the solid angle in clusters of young stars examined with WISE, providing a unique new catalog of isolated disk stars, key planet-search targets, and candidate advanced extraterrestrial civilizations. Come to this talk to hear the news about our latest dusty discoveries and the trials and the ecstasy of launching a new citizen science project. Please bring your laptop or smartphone if you like!

debris disks↗
DOE OSTI2025

Scientific Open-Source Software Is Less Likely to Become Abandoned Than One Might Think! Lessons from Curating a Catalog of Maintained Scientific Software

Scientific software is essential to scientific innovation and in many ways it is distinct from other types of software. Abandoned (or unmaintained), buggy, and hard to use software, a perception often associated with scientific software can hinder scientific progress, yet, in contrast to other types of software, its longevity is poorly understood. Existing data curation efforts are fragmented by science domain and/or are small in scale and lack key attributes. We use large language models to classify public software repositories in World of Code into distinct scientific domains and layers of the software stack, curating a large and diverse collection of over 18,000 scientific software projects. Using this data, we estimate survival models to understand how the domain, infrastructural layer, and other attributes of scientific software affect its longevity. We further obtain a matched sample of non-scientific software repositories and investigate the differences. We find that infrastructural layers, downstream dependencies, mentions of publications, and participants from government are associated with a longer lifespan, while newer projects with participants from academia had shorter lifespan. Against common expectations, scientific projects have a longer lifetime than matched non-scientific open-source software projects. We expect our curated attribute-rich collection to support future research on scientific software and provide insights that may help extend longevity of both scientific and other projects.

Malviya Thakur, Addi [ORNL] (ORCID:000000022681999↗
DOE OSTI2022

Metatransciptomic Analysis Data for Interactive effects of depth and differential irrigation on soil microbiome composition and functioning

RNA was collected from soil at different depths and after three different levels of irrigation T1 100% of normal field irrigation, T4: 18.75% or normal irrigation and T5: unirrigated controls. Total RNA was isolated using the Zymo Quick-RNA fecal/soil microbe miniprep (catalog no. R2040), incorporating the DNase I treatment using Zymo’s DNase I kit (catalog no. E1010). To increase the yield of RNA, we modified the manufacturer’s instructions by first doubling the amount of soil per extraction (from 0.25 g to 0.5 g) and by performing extractions in triplicate before pooling separate extractions together. Certain soil samples (largely those from deeper soil layers) had low yield (< 100 ng per extraction) so additional rounds of extraction were performed to obtain sufficient RNA. RNA concentration was assessed using a Qubit RNA HS assay kit (Thermo Fisher) and RNA quality was determined using an Agilent 2100 BioAnalyzer (Agilent; Santa Clara, CA). The resultant RNA samples were then sequenced by GENEWIZ using Illumina technology (GENEWIZ; South Plainfield, NJ). Sequences were then aligned to a soil metagenome previously obtained from the same site using the Burrows-Wheeler aligner (BWA). SAM files were then converted to raw counts using HTSeq.

Soil microbiome, metatranscriptomics↗
NASA NTRS1977

Results from the Air Force Geophysics Laboratory survey catalog

Results of an IR survey program designed to obtain the spatial and brightness distributions of a representative sample of IR-emitting objects in the 3-30 micron range are analyzed. Small cryogenically cooled telescopes carried above the atmosphere on sounding rockets were employed in the research. Minimization of sky noise and photon background, experimental equipment, and data reduction techniques are discussed.

Price, S. D.↗
NASA NTRSDate not supplied

Flux Comparison of Master-8 and Ordem 3.1 Modelled Space Debris Population

With ESA’s Meteoroid And Space debris Terrestrial Environment Reference (MASTER-8) model and NASA’s Orbital Debris Engineering Model(ORDEM) 3.1, the two premier orbital debris engineering models have been officially released. The two models come with significant enhancements and now represent state-of-the-art orbital debris modelling for their respective agencies. Both models provide the community with estimates of the space debris environment from low Earth orbit (LEO) up to at least geostationary altitude. The MASTER population is an event-based simulation of all known events that generate debris and objects that are part of the U.S. Space Surveillance Network (SSN) catalog, which provides coverage of objects with diameters down to approximately 10cm in LEO and 1 m in geosynchronous Earth orbit (GEO). Different models are used to simulate the artificial objects and their orbit evolution over time. These models are called “sources” since they assign an origin to each individual object and consist of fragments, solid rocket motor (SRM) remainders, sodium-potassium(NaK) droplets, paintflakes, ejecta, and multi-layer insulation (MLI) fragments. The objects from each source are characterized by having individual release mechanisms, as well as orbital distributions, material composition, size, and mass distributions. Dedicated radar and telescope observation data is used to calibrate the model for objects larger than 1 cm in LEO and larger than 10 cm in GEO. For calibrating the small-sized objects, below 1 cm, impact data from returned surfaces are analyzed. Because the >1cm object population is dominated by fragments, the fragmentation event database was updated to include new events, as well as re-evaluate past events. Special attention was drawn to re-evaluating theFengyun-1C anti-satellite test from 2007 and Cosmos-Iridium collision event from 2009 since these events shape the fragment population because of their severity. After 2009, the two largest fragmentations in terms of number of tracked debris are the Briz-M explosion in 2012 and the NOAA-16explosion in 2015. In total, there are 261 confirmed fragmentations in the database up to November 2016.The baseline population for ORDEM 3.1 is based on the U.S. SSN catalog, and observational datasets from radar, in situ, and optical sources provide a foundation from which the model populations are statistically extrapolated to smaller size regions. These regions are not well-covered by the SSN catalog yet may pose the greatest threat to operational spacecraft. The NASA Standard Satellite Breakup Model is used to generate fragments greater than 1mm from collisions and explosions, and these fragment populations are scaled using ground-based radar data. Specific major debris-producing events, including the Fengyun-1C, Iridium 33, and Cosmos2251 debris clouds, and unique populations, such as NaK droplets, were re-examined, modelled, and added to the ORDEM environment separately. Optical measurement data is used to model the GEO population down to 10 cm. The debris environment is propagated using NASA’s LEO-to-GEO Environment Debris model, and future explosions of intact objects and collisions involving objects greater than 10 cm are assessed statistically. The environment from a few millimetres down to 10 𝜇m is modelled using a special degradation model where small particles are generated from intact spacecraft and rocket bodies, then the populations are scaled to fit in situ cratering data from Space Shuttle returned surfaces. Fragments smaller than 10 cm are differentiated based on material density categories, i.e., high-, medium-, and low-density, to better characterize the potential debris risk posed to upper stages and spacecraft. This paper will discuss the MASTER and ORDEM approaches for modelling populations and compare fluxes for specific orbits, including sun-synchronous, ISS-altitude, geosynchronous transfer, and GEO. In the end, a conclusion is drawn towards the importance of having multiple fundamentally different, yet validated, models to estimate the space debris population.

Andre Horstmann↗
DOE OSTI2023

CANVAS: An Adjoint Waveform Tomography Model of California and Nevada

Abstract We present the California‐Nevada Adjoint Simulations (CANVAS) model, an adjoint waveform tomography model of the crust and uppermost mantle of the states of California and Nevada. We used WUS256 (Rodgers et al., 2022, https://doi.org/10.1029/2022jb024549 ) as the starting model and iteratively decreased the minimum period of CANVAS from 30 to 12 s. CANVAS was iterated in two distinct stages: the first stage with source mechanisms from the Global Centroid Moment Tensor (GCMT) catalog and the second stage with inverted moment tensors (MT) using the CANV_WUS model (Doody et al., 2023, https://doi.org/10.1029/2023jb026463 ). We show that updating the MTs with 3D Green's functions improved waveform fits and azimuthal coverage of windowed data used to calculate the gradients. As for the model itself, we improved waveform fits over WUS256, particularly in the dispersed surface waves. CANVAS resolved tectonic features seen in other models and accurately defined the depth to basement of major basins, including the Central Valley and the Ventura Basin. We propose CANVAS as a starting model for crustal tomography models on smaller scales.

58 GEOSCIENCES↗
DOE OSTI2025

Search for continuous gravitational wave signals from luminous dark photon superradiance clouds with LVK O3 observations

Superradiance clouds of kinetically mixed dark photons around spinning black holes can produce observable multimessenger electromagnetic and gravitational wave signals. The cloud generates electric fields of up to a teravolt-per-meter, which leads to a cascade production of charged particles, yielding a turbulent quasiequilibrium plasma around the black hole, and resulting in electromagnetic fluxes ranging from supernova to pulsar-like luminosities. For stellar mass black holes, such systems resemble millisecond pulsars and are expected to emit pulsating radio waves and continuous gravitational waves (CWs) within the LIGO-Virgo-KAGRA (LVK) sensitivity band. We select 44 sources with approximately coincident frequencies or positive frequency drifts from existing pulsar catalogs as potential candidates of long-lasting superradiance clouds around old Galactic black holes. For a subset of 34 sources that are well measured and have not been previously targeted, we perform the first search for CW emission in LVK data from the third observing run. We find no evidence of a CW signal and place 95% confidence level upper limits on the emitted strain amplitude. We interpret these results, together with limits from previous searches, in terms of the underlying dark photon theory by performing an analysis of the expected signals from superradiance clouds from Galactic black holes. Finally, we find that, even for moderately spinning black holes, the absence of an observed CW signal disfavors a discrete set of dark photon masses between about 10 −13 and 10 −12 eV/c 2 and kinetic mixing couplings in the range of 10 −9 –10 −7 , subject to assumptions about the properties of the black hole population and the cloud’s electromagnetic emission.

astronomical black holes↗
DOE OSTI2021

Evaluation of the PhaseNet Model Applied to the IMS Seismic Network

Producing a complete and accurate set of signal detections is essential for automatically building and characterizing seismic events of interest for nuclear explosion monitoring. Signal detection algorithms have been an area of research for decades, but still produce large quantities of false detections and misidentify real signals that must be detected to produce a complete global catalog of events of interest. Deep learning methods have shown promising capabilities in effectively characterizing seismic signals for complex tasks such as identifying phase arrival times. We use the PhaseNet model, a UNet-based Neural Network, trained on local distance data from northern California to predict seismic arrivals on data from the International Monitoring System (IMS) global network. We use an analyst-curated bulletin generated from this data set to compare the performance of PhaseNet to that of the Short-Term Average/Long-Term Average (STA/LTA) algorithm. We find that PhaseNet has the potential of outperforming traditional processing methods and recommend the training of a new model with the IMS data to achieve optimal performance.

58 GEOSCIENCES↗
NASA NTRS1983

Filamentary galaxy clustering - A mapping algorithm

A simple and objective algorithm is presented which not only accurately identifies the filamentary structures in the Shane-Wirtanen galaxy count catalog, but also finds a set of visually less impressive filaments in a static hierarchical model of the clustering conducted by Soneira and Peebles (1978). The statistical properties of the elements in the model, while very similar to those in the data, show a significant excess of long and bright filaments in the data relative to the model. Two possible interpretations of these results are presented and discussed.

Gott, J. R., III↗
NASA NTRS1990

Distribution of galaxies in the Southern Galactic Cap

Observations in the southern galactic hemisphere in the declination range between -17.5 and 2.5 degrees are combined with other available observation. The data set is used to study the spatial distribution of galaxies of a contiguous area of 3.13 sr of the Southern Galactic Cap. An approximately homogeneous magnitude-limited sample of galaxies in the Southern Galactic Cap is constructed from different catalogs. The resulting large scale structure is similar to that of previous surveys in which bright galaxies are distributed on surfaces which intersect at sharp corners and nearly surround voids that are almost empty of galaxies.

Pellegrini, P. S.↗
NASA NTRS1990

Optical observations of space debris

The Johnson Space Center is processing optical data on orbital debris from five sources. The greatest amount of data so far obtianed is from the GEODSS system for which an analysis is presented of 80.9 hours of zenith observations. A total of 622 satellites were found of which 255 have been identified with objects in the USAF Space Command catalog (SCC). When objects in the SCC but which are not seen by GEODSS are accounted for, an SCC completeness factor of 0.46 over all diameters in the 500 to 1100 km height range is found. For objects with diameters between 8 and 30 cm this factor is 0.26. Comparison of GEODSS-derived diameters with RCS-derived diameters yields a revised mean albedo of approximately 0.08.

Henize, Karl G.↗
NASA NTRS1991

Observations of Enhanced Radar Backscatter (ERB) from Millstone Hill

Intense enhancements of the incoherent radar backscatter spectrum from the topside ionosphere were observed with the Millstone Hill UHF radar. Enhancements occurring at the local ion acoustic frequency causing large asymmetries in the measured ion line may be produced by current driven instabilities. These enhancements pose a practical problem for space surveillance systems because their cross section and spectral width are characteristic of satellites. Conversely, their hard target signature complicates the study of naturally occurring ERB events; it is nearly impossible to distinguish them from satellites based on a single measurement. Statistical comparisons of observed coherent echo distributions with predictions from a satellite catalog were used to broadly identify periods of ERB activity. A series of experiments using multiple diagnostics, including satellite instruments, for simultaneous observations have established the association of ERB with large fluxes of soft suprathermal electrons carrying field aligned currents. Zenith data are also presented which show the asymmetric growth of ion acoustic waves directly above Millstone Hill. Details of these results are presented.

Lee, M. C.↗
NASA NTRS2001

Structure and Characteristics of Precipitation Systems Observed by TRMM

Multi-sensor measurements of total lightning (in-cloud plus cloud-to-ground) from the Lightning Imaging Sensor (LIS) aboard the TRMM satellite has been combined with passive microwave ice scattering and precipitation radar reflectivity profile information previously cataloged for precipitation features observed by TRMM. These precipitation features are defined by their surface rainfall or ice scattering signatures, with horizontal scales approx. 100 - 10000 sq km. Additionally, convective scale (approx. 100 sq km) storms are defined by the lightning data. Over the U.S. the national cloud-to-ground lightning observations are used to also determine the ratio of in-cloud to cloud-to-ground lightning, where it is hypothesized these ratios are related to the vertical profile of reflectivity and concentration of precipitation-sized ice. Combining the LIS, TRMM Microwave Imager (TMI), and Precipitation Radar (PR) for these storms allows investigation of the convective structures and convective regimes leading to observed lightning, scattering, and reflectivity signatures. Application of this approach to a global, multi-year data set (1998-2000) furthers our understanding of convective processes in different climatological regimes. The figure shows the distribution of high flash rate storms.

Goodman, Steve↗
NASA NTRS1998

Incorporating the APS Catalog of the POSS I and Image Archive in ADS

The primary purpose of this contract was to develop the software to both create and access an on-line database of images from digital scans of the Palomar Sky Survey. This required modifying our DBMS (called Star Base) to create an image database from the actual raw pixel data from the scans. The digitized images are processed into a set of coordinate-reference index and pixel files that are stored in run-length files, thus achieving an efficient lossless compression. For efficiency and ease of referencing, each digitized POSS I plate is then divided into 900 subplates. Our custom DBMS maps each query into the corresponding POSS plate(s) and subplate(s). All images from the appropriate subplates are retrieved from disk with byte-offsets taken from the index files. These are assembled on-the-fly into a GIF image file for browser display, and a FITS format image file for retrieval. The FITS images have a pixel size of 0.33 arcseconds. The FITS header contains astrometric and photometric information. This method keeps the disk requirements manageable while allowing for future improvements. When complete, the APS Image Database will contain over 130 Gb of data. A set of web pages query forms are available on-line, as well as an on-line tutorial and documentation. The database is distributed to the Internet by a high-speed SGI server and a high-bandwidth disk system. URL is http://aps.umn.edu/IDB/. The image database software is written in perl and C and has been compiled on SGI computers with MIX5.3. A copy of the written documentation is included and the software is on the accompanying exabyte tape.

Humphreys, Roberta M.↗
DOE OSTI2022

Detection of spatial clustering in the 1000 richest SDSS DR8 redMaPPer clusters with nearest neighbor distributions

ABSTRACT Distances to the k-nearest-neighbor (kNN) data points from volume-filling query points are a sensitive probe of spatial clustering. Here, we present the first application of kNN summary statistics to observational clustering measurement, using the 1000 richest redMaPPer clusters (0.1 ≤ z ≤ 0.3) from the SDSS DR8 catalog. A clustering signal is defined as a difference in the cumulative distribution functions (CDFs) of kNN distances from fixed query points to the observed clusters versus a set of unclustered random points. We find that the k = 1, 2-NN CDFs of redMaPPer deviate significantly from the randoms’ across scales of 35 to 155 Mpc, which is a robust signature of clustering. In addition to kNN, we also measure the two-point correlation function for the same set of redMaPPer clusters versus random points, which shows a noisier and less significant clustering signal within the same radial scales. Quantitatively, the χ2 distribution for both the kNN-CDFs and the two-point correlation function measured on the randoms peak at χ2 ∼ 50 (null hypothesis), whereas the kNN-CDFs (χ2 ∼ 300, p = 1.54 × 10−36) pick up a much more significant clustering signal than the two-point function (χ2 ∼ 100, p = 1.16 × 10−6) when measured on redMaPPer. Finally, the measured 3NN and 4NN CDFs deviate from the predicted k = 3, 4-NN CDFs assuming an ideal Gaussian field, indicating a non-Gaussian clustering signal for redMaPPer clusters, although its origin might not be cosmological due to observational systematics. Therefore, kNN serves as a more sensitive probe of clustering complementary to the two point correlation function, providing a novel approach for constraining cosmology and galaxy–halo connection.

79 ASTRONOMY AND ASTROPHYSICS↗