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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Asthma and Particulate Matter Pollution: Insights from Health Survey and Air Quality Monitoring in the Buzzard Point, Washington, DC Neighborhood

Air pollution, climate change, and other environmental factors contribute to increasing asthma in manycities, including Washington, DC. This work provides a case study of how community input, neighborhood-level health surveys, and air quality monitoring can inform the understanding of asthma and air pollution.A partnership between residents, concerned citizens, scientists, and educators has been working for envi-ronmental health in a DC neighborhood located on a major roadway, next to concrete batch plants andclose to several construction projects. A 2016 Community Health and Safety Study by the DC Departmentof Health, Office of Health Equity, recognized this particular neighborhood as more vulnerable to healthimpacts from recent construction in the area, compared with the surrounding areas, due to lower averageincome and higher percentage of seniors and children. This work presents neighborhood health surveysand air quality monitoring data at a more granular, local level than available from DC governmentagencies. The health surveys documented residents’ experiences around air pollution, asthma,and other health concerns. A key finding was evidence that asthma might be undercounted in thisneighborhood; among residents who did not indicate a diagnosis of asthma, many discussed havingsymptoms that could reflect asthma. Air quality monitoring (particulate matter [PM]) did not indicate thatfederal air quality standards have been violated. Real-time PM data, however,illustrated how current PMstandards, such as 1- and 24-hour averages, may fail to capture shorter duration high PM events that areconsistent with resident concerns.

Shizuka Hsieh↗
NASA NTRSDate not supplied

Using Federated Learning to Overcome Data Gravity in Space

Humans intend to take longer missions to outer space. Understanding the impact that space has on human health is paramount to the success of these missions. Controlled experiments with model organisms are run to infer the impact of space conditions on human health, but the data these experiments generate are too large to transfer to Earth for building models. The same is true for space-relevant data generated on Earth. Ideally, these datasets should be combined to improve statistical power and model accuracy without having to transfer data. Federated learning is such a method which trains an algorithm across decentralized computing systems, each of which has their own local copy of training and testing data. In this research, made possible by NASA@Work, the AI for Life in Space group at NASA demonstrates the use of federated learning to train an ensemble of causality inference models on a combination of data residing on the International Space Station (ISS) and in the cloud. Our work leverages CRISP, a causal inference platform developed during the 2020 Frontier Development Lab’s “Astronaut Health Challenge.” We also leverage the OpenFL federated learning library which was collaboratively developed at Intel and UPenn. We used publicly available data from the NASA Ames Life Sciences Data Archive to identify features in ionizing radiation experiments as causal of changes in cardiac blood velocity. This research demonstrates, for the first time, the possibility of running machine learning algorithms on datasets separated by astronomical distances. In this experiment, all the data were generated in terra, half of which were transferred to the ISS and analyzed on the Spaceborne Computer. In the future, our research will leverage federated learning on data generated in situ on the ISS with data generated terrestrially to predict the impact of spaceflight on mammalian female reproductive capacity.

James Casaletto↗
DOE OSTI2024

"Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs"

The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. These "phantom jams" or "stop-and-go waves,"are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment leveraged a heterogeneous fleet of 100 longitudinally-controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this paper. The MegaController is a hierarchical control architecture, which consists of two main layers. The upper layer is called Speed Planner, and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock on-board sensors. The Speed Planner ingests live data feeds provided by third parties, as well as data from our own control vehicles, and uses both to perform the speed assignment. The architecture of the speed planner allows for modular use of standard control techniques, such as optimal control, model predictive control, kernel methods and others, including Deep RL, model predictive control and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers, or only some. Control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars, and electronic selection of ACC set points in others. The proposed architecture allows for the combination of all possible settings proposed above. Most configurations were tested throughout the ramp up to the MegaVandertest.

Lee, Jonathan↗
DOE OSTI2018

Belle II Conditions Database

The Belle II experiment at KEK is preparing for taking first collision data in early 2018. For the success of the experiment it is essential to have information about varying conditions available to systems worldwide in a fast and efficient manner that is straightforward for both the user and maintainer. The Belle II Conditions Database was designed to make maintenance as easy as possible. To this end, a HTTP REST service was developed with industry-standard tools such as Swagger for the API interface development, Payara for the Java EE application server, and the Hazelcast in-memory data grid for support of scalable caching as well as transparent distribution of the service across multiple sites. On the client side, the online and offline software has to be able to obtain conditions data from the Belle II Conditions Database in a robust and reliable way under very different situations. As such the client side interface to the Belle II Conditions Database has been designed with a variety of access mechanisms which allow the software to be used with and without an internet connection. Different methods to access the payload information are implemented to allow for a high level of customization per site and to simplify testing of new payloads locally. Changes to the conditions data are usually handled transparently but users can actively check whether an object has changed or register callback functions to be called whenever a conditions data object is updated. In addition a command line user interface has been developed to simplify inspection and modification of the database contents.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1986

Geodetic measurement of deformation in the central Mojave Desert, California

Data from triangulation and trilateration surveys made during 1934-1982 are used to calculate shear strain rates in the central Mojave Desert of California. For the region between the Helendale and Camp Rock faults the shear strain rate was determined to be 0.16 + or - 0.03 microstrain/yr, with maximum right-lateral shear strain occurring on a plane oriented N41 deg W + or - 5 deg. If this deformation is due to right-lateral motion across the northwest trending local faults, the average shear straining corresponds to a relative displacement of 6.7 + or - 1.3 mm/yr across this portion of the network, accounting for about 12 percent of the predicted 56 mm/yr of relative motion between the North Atlantic and Pacific plates. From the Camp Rock fault eastward across the network there is a transition from significant to very low strain rates. Examination of nine focal mechanisms and their relation to the local geology and the strain data suggests that most of the long-term displacement occurs on the major northwest trending faults oriented nearly along the direction of relative motion between the North American and Pacific plates. Secondary faulting, controlled by a Coulomb-Anderson failure mechanism or by slip on preexisting faults can account for the occurrence of earthquakes on faults of other orientations.

Sauber, Jeanne↗
DOE OSTI2024

Central Asia Seismic Hazard Assessment (CASHA): A Probabilistic Seismic Hazard Assessment for Kazakhstan, Kyrgyzstan and Tajikistan

Probabilistic seismic hazard assessments (PSHA) underpin the calculation of earthquake loads in most building codes around the world. In Central Asia, the building codes are slowly being updated to incorporate some of the contemporary concepts of seismic hazard representation. There is also a regional desire to coordinate hazard assessments and building code modernization. However, some challenges remain. Expertise in the region related to seismic hazard assessments is still largely compartmentalised, requiring a significant amount of training and capacity building in seismic hazard assessment related topics. In addition, there are vast amounts of seismic data (bulletin and waveforms), both from analogue and digital eras, that the region’s countries stored but until recently did not use or share among themselves or with the broader seismological community around the world. Finally, after the collapse of the Soviet Union in the 1990s, many of the countries’ seismic networks suffered a major setback with the lack of attention and budget to update existing equipment and installation of new instruments. In order to address these issues, the United States Department of Energy through Lawrence Livermore National Laboratory (LLNL) initiated a project in 2016 to engage and train local scientists in Central Asia to install new equipment, to enhance the quality of seismic monitoring and reporting, to improve and harmonise the regional earthquake catalogue, and to conduct national probabilistic seismic hazard assessments using the new and improved datasets. To achieve the seismic hazard assessment related goals, a series of workshops were held in Almaty, Kazakhstan; Bishkek, Kyrgyzstan; and Dushanbe, Tajikistan from 2016 until 2020. During the time that the COVID-19 pandemic restricted travel, workshops continued online (22 online workshops were hosted in two years). Finally, in May 2022, an in-person workshop in Istanbul, Turkey brought together all project participants along with civil engineers engaged with building code activities in their respective countries, providing a platform to discuss the implementation of the hazard models into updates of building codes in each country, as well as to discuss model parameters, sensitivity analyses and model results in terms of hazard maps, uniform hazard spectra and hazard deaggregations. The workshops were a combination of lectures and hands-on exercises, and included international participation as well as local scientists and engineers. The workshops served several purposes, including training, coordination of data collection, interactions between local earth scientists and engineers, and brainstorming and knowledge exchange among local and international experts. This report outlines the new earthquake catalogue compilation effort and the PSHA project undertaken in Kyrgyzstan, Tajikistan, and Kazakhstan as part of this initiative. The southern part of this region is tectonically active with moderate to high levels of both shallow crustal seismic activity and occurrence of deeper earthquakes under the Hindu Kush and Pamir mountain ranges. Deeper earthquakes also occur near southwestern Kazakhstan, under the eastern Greater Caucasus and Caspian Sea. Large portions of central and northern Kazakhstan, on the other hand, are in stable continental regions with low levels of seismic activity. This study systematically compiles and improves all available data on local seismicity, active faults, and ground motion attenuation characteristics of the region; and builds a framework to enable a contemporary PSHA to be carried out with the engagement of local scientists. While the project was regional, the seismic hazard assessments are primarily driven by the countries’ own national preferences and understanding of data collection, interpretation, and validation of results.

58 GEOSCIENCES↗
DOE OSTI2017

Defect Genome of Cubic Perovskites for Fuel Cell Applications

Heterogeneities such as point defects, inherent to material systems, can profoundly influence material functionalities critical for numerous energy applications. This influence in principle can be identified and quantified through development of large defect data sets which we call the defect genome, employing high-throughput ab initio calculations. However, high-throughput screening of material models with point defects dramatically increases the computational complexity and chemical search space, creating major impediments toward developing a defect genome. In this paper, we overcome these impediments by employing computationally tractable ab initio models driven by highly scalable workflows, to study formation and interaction of various point defects (e.g., O vacancies, H interstitials, and Y substitutional dopant), in over 80 cubic perovskites, for potential proton-conducting ceramic fuel cell (PCFC) applications. The resulting defect data sets identify several promising perovskite compounds that can exhibit high proton conductivity. Furthermore, the data sets also enable us to identify and explain, insightful and novel correlations among defect energies, material identities, and defect-induced local structural distortions. Finally, such defect data sets and resultant correlations are necessary to build statistical machine learning models, which are required to accelerate discovery of new materials.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS2019

Global seasonal variations of the near-surface relative humidity levels on present-day Mars

We investigate the global seasonal variations of near-surface relative humidity and relevant attributes, like temperature and water vapor volume mixing ratio on Mars using calculations from modelled and measurement data. We focus on 2 AM local time snapshots to eliminate daily effects related to differences in insolation, and to be able to compare calculations based on modelling data from the Laboratoire de Météorologie Dynamique Mars General Circulation Model with the observations of Mars Global Surveyor Thermal Emission Spectrometer. We study the seasonal effects by examining four specific dates in the Martian year, the northern spring equinox, summer solstice, autumn equinox, and winter solstice. We identify three specific zones, where the near-surface relative humidity levels are systematically higher than in their vicinity regardless of season. We find that these areas coincide with low thermal inertia features, which control surface temperatures on the planet, and are most likely covered with unconsolidated fine dust with grain sizes smaller than ∼ 40 μm. By comparing the data of relative humidity, temperature and water vapor volume mixing ratio at three different heights (near-surface, ∼ 4m and ∼ 23m above the surface), we demonstrate that the thermal inertia could play an important role in determining near-surface humidity levels. We also notice that during the night the water vapor levels drop at ∼ 4m above the surface. This, together with the temperature and thermal inertia values, shows that water vapor likely condenses in the near-surface atmosphere and on the ground during the night at the three aforementioned regions. This condensation may be in the form of brines, wettening of the fine grains by adsorption or deliquescence. This study specifies areas of interest on the surface of present day Mars for the proposed condensation, which may be examined by in-situ measurements in the future.

Bernadett Pál↗
DOE OSTI2025

Community Choice Aggregation(CCA) Data Collection Webinar for Status and Trends in the Voluntary Market Report (2024 Data) [Slides]

We have subcontracted LEAN Energy US, to help us improve our CCA data collection effort for the Annual Voluntary Energy Markets Data Report. LEAN Energy US (Local Energy Aggregation Network) is a national 501(c)3 non-profit organization dedicated to accelerating the country's transition to clean and renewable power, supporting competition and customer choice in the energy sector, and maintaining affordable electricity rates. We work in partnership with a range of organizations to actively support the formation and operational success of Community Choice Aggregation (CCA) programs around the country. This webinar, hosted in partnership with LEAN Energy US, is intended to introduce their members to our data collection effort and encourage CCAs in their network to participate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2006

Initiation of the Slow-Rise and Fast-Rise Phases of an Erupting Solar Filament by Localized Emerging Magnetic Field via Microflaring

EUV data from EIT show that a filament of 2001 February 28 underwent a slow-rise phase lasting about 6 hrs, before rapidly erupting in a fast-rise phase. Concurrent images in soft X-rays (SXRs) from Yohkoh/SXT show that a series of three microflares, prominent in SXT images but weak in EIT approx.195 Ang EUV images, occurred near one end of the filament. The first and last microflares occurred respectively in conjunction with the start of the slow-rise phase and the start of the fast-rise phase, and the second microflare corresponded to a kink in the filament trajectory. Beginning within 10 hours of the start of the slow rise, new magnetic flux emerged at the location of the microflaring. This localized new flux emergence and the resulting microflares, consistent with reconnection between the emerging field and the sheared sigmoid core magnetic field holding the filament, apparently caused the slow rise of this field and the transition to explosive eruption. For the first time in such detail, the observations show this direct action of localized emerging flux in the progressive destabilization of a sheared core field in the onset of a coronal mass ejection (CME). Similar processes may have occurred in other recently-studied events, NASA supported this work through NASA SR&T and SEC GI grants.

Sterling, A. C.↗
NASA NTRS1992

Data and information system requirements for Global Change Research

Efforts to develop local information systems for supporting interdisciplinary Global Change Research are described. A prototype system, the Interdisciplinary Science Data and Information System (IDS-DIS), designed to interface the larger archives centers of EOS-DIS is presented. Particular attention is given to a data query information management system (IMS), which has been used to tabulate information of Landsat data worldwide. The use of these data in a modeling analysis of deforestation and carbon dioxide emissions is demonstrated. The development of distributed local information systems is considered to be complementary to the development of central data archives. Global Change Research under the EOS program is likely to result in proliferation of data centers. It is concluded that a distributed system is a feasible and natural way to manage data and information for global change research.

Skole, David L.↗
DOE OSTI2021

Evidence for sub-Chandrasekhar Type Ia supernovae from the last major merger

ABSTRACT We investigate the contribution of sub-Chandrasekhar mass Type Ia supernovae to the chemical enrichment of the Gaia Sausage galaxy, the progenitor of a significant merger event in the early life of the Milky Way. Using a combination of data from Nissen & Schuster, the GALactic Archaeology with HERMES (GALAH) Data Release 3 [with 1D non-local thermal equilibrium (NLTE) abundance corrections], and the Apache Point Observatory Galactic Evolution Experiment (APOGEE) Data Release 16, we fit analytic chemical evolution models to a nine-dimensional chemical abundance space (Fe, Mg, Si, Ca, Cr, Mn, Ni, Cu, and Zn) in particular focusing on the iron-peak elements, Mn and Ni. We find that low [Mn/Fe] $\sim -0.15\, \mathrm{dex}$ and low [Ni/Fe] $\sim -0.3\, \mathrm{dex}$ Type Ia yields are required to explain the observed trends beyond the [α/Fe] knee of the Gaia Sausage (approximately at [Fe/H] $=-1.4\, \mathrm{dex}$). Comparison to theoretical yield calculations indicates a significant contribution from sub-Chandrasekhar mass Type Ia supernovae in this system (from ${\sim} 60\, \mathrm{per\, cent}$ to $100\, \mathrm{per\, cent}$ depending on the theoretical model with an additional ${\pm} 10\, \mathrm{per\, cent}$ systematic from NLTE corrections). We compare to results from other Local Group environments including dwarf spheroidal galaxies, the Magellanic Clouds, and the Milky Way’s bulge, finding the Type Ia [Mn/Fe] yield must be metallicity dependent. Our results suggest that sub-Chandrasekhar mass channels are a significant, perhaps even dominant, contribution to Type Ia supernovae in metal-poor systems, whilst more metal-rich systems could be explained by metallicity-dependent sub-Chandrasekhar mass yields, possibly with additional progenitor mass variation related to star formation history, or an increased contribution from Chandrasekhar mass channels at higher metallicity.

Sanders, Jason L.↗
DOE OSTI2022

EASTERN NORTH ATLANTIC (ENA) CONDENSATION PARTICLE COUNTER (CPC) with the AEROSOL MASK (ENA-AM) for the YEAR 2016

The Eastern North Atlantic (ENA) central facility is periodically affected by episodes of local aerosols. High-concentration aerosol events associated with potential local aerosol sources are sampled by the concentration particle counter (CPC) and can be observed in the high-time-resolution data. In an effort to remove aerosol data that is not regionally representative from the CPC data, an aerosol mask (ENA-AM) has been previously developed and validated during the ACE-ENA campaign (Gallo et al. 2020). The ENA-AM is a standard deviation algorithm based on the statistically different behavior of adjacent data points used to determine periods when the measurements are impacted by local aerosols. This file contains one-minute-time-resolution submicron aerosol particle concentration data sets from the CPC for the year 2016, and the corresponding ENA-AM data sets to remove data points affected by local aerosol sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Computing Bottleneck Structures at Scale for High-Precision Network Performance Analysis

The Theory of Bottleneck Structures is a recently-developed framework for studying the performance of data networks. It describes how local perturbations in one part of the network propagate and interact with others. This framework is a powerful analytical tool that allows network operators to make accurate predictions about network behavior and thereby optimize performance. Previous work implemented a software package for bottleneck structure analysis, but applied it only to toy examples. In this work, we introduce the first software package capable of scaling bottleneck structure analysis to production-size networks. Here, we benchmark our system using logs from ESnet, the Department of Energy's high-performance data network that connects research institutions in the U.S. Using the previously published tool as a baseline, we demonstrate that our system achieves vastly improved performance, constructing the bottleneck structure graphs in 0.21 s and calculating link derivatives in 0.09 s on average. We also study the asymptotic complexity of our core algorithms, demonstrating good scaling properties and strong agreement with theoretical bounds. These results indicate that our new software package can maintain its fast performance when applied to even larger networks. They also show that our software is efficient enough to analyze rapidly changing networks in real time. Overall, we demonstrate the feasibility of applying bottleneck structure analysis to solve practical problems in large, real-world data networks.

benchmark↗
NASA NTRS1999

Composite Fuselage Technology

Work was conducted over a ten-year period to address the central issue of damage in primary load-bearing aircraft composite structure, specifically fuselage structure. This included the three facets of damage resistance, damage tolerance, and damage arrest. Experimental, analytical, and numerical work was conducted in order to identify and better understand the mechanisms that control the structural behavior of fuselage structures in their response to the three aspects of damage. Furthermore, work was done to develop straightforward design methodologies that can be employed by structural designers in preliminary design stages to make intelligent choices concerning the material, layup, and structural configurations so that a more efficient structure with structural integrity can be designed and built. Considerable progress was made towards achieving these goals via this work. In regard to damage tolerance considerations, the following were identified as important effects: composite layup and associated orthotropy/structural anisotropy, specifics of initial local damage mechanisms, role of longitudinal versus hoop stress, and large deformation and associated geometric nonlinearity. Means were established to account for effects of radius and for the nonlinear response. In particular, nondimensional parameters were identified to characterize the importance of nonlinearity in the response of pressurized cylinders. This led to the establishment of a iso-nonlinear-error plot for reference in structural design. Finally, in the case of damage tolerance, the general approach of the original methodology to predict the failure pressure involving extending basic plate failure data by accounting for the local stress intensification was accomplished for the general case by accounting for the mechanisms noted by utilizing the capability of the STAGS finite element code and numerically calculating the local stress intensification for the particular configuration to be considered. For the issue of damage arrest, placement of and configuration of stiffeners (including stiffener curvature), and magnitude and orientation of principal strains due to local bending were found to be key considerations. Means were established to account for stiffener effectiveness quantitatively based on radius, slit size, stiffener curvature' and relative bending stifffiesses involved. Geometric nonlinearity was also found to play an - 24 - important role here. Furthermore, it was determined that damage propagation is controlled by different mechanisms (hoop stress versus flapping stress and the associated factors involved in each) depending upon the direction of damage propagation. This latter item results in an inability to scale these phenomena in one test due to the different factors involved. Finally, the importance of shell curvature and associated instability in response to transverse loading including impact were found to be important considerations in damage resistance. A technique, involving asymmetric meshing of a finite element mesh, was developed to predict this behavior and showed excellent correlation with experimental results. Further details of these ten years of work are presented herein with references made to the fourteen documents produced during this work where full details can be found. Implications of this work are discussed and recommendations made. Although it is clear that there is more work to be done to fully understand composite fuselage technology and specifically the overall issue of damage in primary load-bearing composite structures, important understanding and capability has been extended via this work.

Lagace, Paul A.↗
NASA NTRS1998

SGR 1627-41

BATSE has detected repeated soft gamma-ray bursts consistent with the same (previously unknown) location. We recorded three bursts on June 15.109, 15.296, 15.411 UT (BATSE triggers 6825, 6826, 6827, respectively) with an average duration of about 200 milliseconds. Preliminary spectral analysis of the data indicates that the events are very soft, with power law spectral indices varying between -3.0 and -7.0. BATSE triggered 5 more times, on June 17.873,17.901, 18.004, 18.035, and 18.071 UT (BATSE trigger numbers 6833, 6834, 6835, 6836 and 6837, respectively). The last trigger had a peak count rate of over 300000 counts/sec above background (integrated over 4 detectors between 20-1000 keV, in 1 second interval) and a duration of about 3 seconds. Due to Rs very high peak intensity, deadtime effects prevent us from using it for localization, until we receive more data types. The weighted location of the 7 remaining triggers is centered on R.A. = 16h27ml2.0s and dec = -41 d06.0' with an error radius of about 2 degrees. This location does not correspond to any previously known SGR source; we conclude that we have discovered a new source, SGR1627-41. We have initiated an RXTE ToO and we strongly encourage wide field observations at other wavelengths.

Kouveliotou, Chryssa↗
DOE OSTI2026

Unsupervised Segmentation and Clustering Workflow for Efficient Processing of 4D-STEM and 5D-STEM Data

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables mapping of diffraction information with nanometer-scale spatial resolution, offering detailed insight into local structure, orientation, and strain. However, as data dimensionality and sampling density increase, particularly for in situ scanning diffraction experiments (5D-STEM), robust segmentation of structurally consistent behavior across sequential measurements becomes essential for efficient and physically meaningful analysis. Here, we introduce a clustering framework that identifies crystallographically distinct domains from 4D-STEM datasets. By using local diffraction-pattern similarity as a metric, the method extracts closed contours delineating spatially contiguous regions. This approach produces cluster-averaged diffraction patterns that improve signal quality while reducing data volume by orders of magnitude, enabling rapid and accurate orientation, phase, and strain mapping. We demonstrate the applicability of this approach to in situ liquid-cell 4D-STEM data of gold nanoparticle growth. Our method provides a scalable and generalizable route for spatially coherent segmentation, data compression, and quantitative structure–strain mapping across diverse 4D-STEM modalities. The full analysis code and example workflows are publicly available to support reproducibility and reuse.

4D-STEM↗