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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Generative deep-learning reveals collective variables of Fermionic systems

Complex processes of fermionic systems ranging from protein folding to nuclear fission often follow a low-dimensional reaction path parametrized in terms of a few collective variables. In nuclear theory, variables related to the shape of the nuclear density in a mean-field picture are key to describing the large amplitude collective motion of the neutrons and protons. Exploring the adiabatic energy landscape spanned by these degrees of freedom reveals the possible reaction channels while simulating the dynamics in this reduced space yields their respective probabilities. Unfortunately, this theoretical framework breaks down whenever the systems encounters a quantum phase transition with respect to the collective variables. Here, in this study, we introduce a novel generative deep-learning algorithm designed to build reaction paths that ensure that the many-fermion wave function stays differentiable with respect to the collective variables. This approach is applicable to any fermionic system described by a coherent state. We use the case of potential energy curves in the 16 O nucleus within the Hartree-Fock theory to illustrate its main features.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Collection And Analysis Of Telemetry For The Cyote Heuristic

CATCH CLI focuses on gathering telemetry data, storing it in the Neo4j database, querying for Mitre ATT&CK patterns, and creating STIX 2.1 reports. Key Components: Analysis Modules: Analyze data to detect attack patterns. GoSTOTS Collection Engines: Collect telemetry data. These tools can be used together or individually. Analysis modules rely on data from specific engines to identify attack patterns. Source Code Organization: Engines: CATCH/catch/cmd/collection Modules: CATCH/catch/cmd/analysis CGUI Overview CATCH Graphical User Interface (CGUI) offers a graphical shell to execute CATCH CLI, allowing easy editing of: Analysis Modules Database configurations Profiles (collection and device settings) Neo4j Overview Neo4j is a graph database using the Cypher query language, storing data in JSON. It seamlessly integrates with STIX 2.1 data for: Data Submission: CATCH Collection Engines Data Querying: Analysis Modules CATCH modifies STIX 2.1 data for Neo4j submission and reverts it back during querying. STIG Overview Structured Threat Intelligence Graph (STIG) is a tool for creating, editing, querying, analyzing, and visualizing threat intelligence using STIX 2.1 and storing data in Neo4j. Usage Tools can be run: Manually (CLI): Refer to CATCH documentation User Interface: Run ./cgui/CGUI or go run ./cgui/ Additional Information Logging System: Detailed in the config documentation Further Documentation: Available for CATCH and CGUI

Madsen, MichaelJ. [Idaho National Laboratory (INL)↗
DOE OSTI2021

Dynamically Collected Local Density using Low-Cost Lidar and its Application to Traffic Models

This article demonstrates the use of traffic density observations collected dynamically in the vicinity of probe vehicles. Fixed position sensors cannot capture the longitudinal evolution of local traffic density in the corridor. In this research, dynamic traffic density observations were collected in a naturalistic driving setting that was free of any controlled experiment biases. Speed from global positioning system and space headway from a light detection and ranging module was collected on one arterial and one freeway segment, 2 and 4mi long, respectively. The combined data frequency was approximately 3Hz. Space headway was used to estimate the local density and consequently to identify the density of a specific location in a corridor. Besides, driver behavior was characterized using the relationship between instantaneous speed and local density under different regimes of the Wiedemann car-following model. Macroscopic traffic stream models were used to investigate the relationship between dynamically collected instantaneous speed and local density. Using the longitudinal evolution of density, precise local density across the corridor can be obtained along with the leader and follower trajectories. A method to identify driver behavior across density ranges was developed for different facility types using a microscopic relationship between instantaneous speed and local density. Overall driving behavior on the freeway segment can be represented by translating the instantaneous speed and local density relationship to macroscopic stream models.

Engineering↗
DOE OSTI2022

Perceived Costs and Benefits of ICON Science and Foundational Documents associated with “Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles"

This data package is associated with the publication "Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles" in Earth and Space Science (Goldman et al. 2022; https://doi.org/10.1029/2021EA002099). The manuscript is an introductory article for a special collection of commentary articles across 19 geoscience disciplines that explore the challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross-system transferability of science outcomes. This data package contains data, figures, and R scripts associated with the cost/benefit analysis presented in the manuscript. The writing teams involved in the special collection placed each letter of ICON on a plot with perceived cost on one axis and perceived benefit on the other to summarize their perceptions of pursuing each principle of ICON science. These data were subsequently quantified and analyzed. Files are saved as .csv, .R, and .pdf. This data package also contains (1) the public foundational and instructional documents that enabled the crowdsourced creation of the special collection; (2) file-level metadata (flmd) that lists each file in the data package with a description; (3) data dictionary (dd) that defines column headers that appear in csv files. Files are saved as .pdf and .csv.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Lead isotopic compositions of airborne particulates collected from snow and from dry deposition in the East River Watershed, Colorado and at the Southern Sierra Critical Zone Observatory, California

The data set consists of lead (Pb) isotopic ratios (206Pb/207Pb and 208Pb/207Pb, as well as 206Pb/204Pb, 207Pb/204Pb, 208Pb/204Pb) for particulate samples collected from snow and dry deposition. This was part of a study (O’Day et al. 2020) that was looking at the speciation of phosphorous in splits of these samples to evaluate the flux and bio-availability of phosphorous to the mountain sites in the study. The Pb isotopic data allow sourcing of long-range transported Pb, specifically the fraction of Pb sourced in Asia, and so a comparison of the relative distances of PM sources between the high and low elevation sites. Samples were collected at the East River Watershed, CO (dry deposition collected over Sept.-Oct. 2016, show sampling winter 2017) and at the Southern Sierra Critical Zone Observatory (dry deposition collected over Sept-Nov 2016, July-Sept 2017, June-July 2017). The data includes Pb concentration data, as well as calculated fraction of the Pb sourced in Asia. This data set was published in part in O’Day et al. (2020) Phosphorus Speciation in Atmospherically Deposited Particulate Matter and Implications for Terrestrial Ecosystem Productivity. ES&T, https://dx.doi.org/10.1021/acs.est.9b06150

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Fission TPC FY2020 Report (Mid Q2 FY2021): Preliminary 235 U(n,f)/ 6 Li(n,t)α Cross Section Ratio Analysis & Update on the 239 Pu(n,f) Data Collection

Fission TPC L2 Milestone Description: The fission TPC experimental campaign is in its final stages of collecting high precision (n,f) cross section data aimed at improving our understanding of the 239 Pu fission process. During FY 2019 235 U(n,f)/ 6 Li(n,t) ratio data collection began at WNR/LANSCE. This data is the first step in demonstrating the efficacy of 6 Li(n,t) as a diagnostic standard for a 239 Pu(n,f) ratio measurement. In FY 2020 and FY2021, the NIFFTE Collaboration will analyze 235 U(n,f)/ 6 Li(n,t) data already collected to establish this technique in preparation for 239 Pu(n,f)/ 6 Li(n,t) ratio data. Additionally, the ability to vapor deposit 239 Pu was developed in 2019, greatly improving target quality. As access to experimental facilities allows, 239 Pu/ 235 U and 239 Pu/ 6 Li data will be collected to provide new inputs for evaluation of the 239 Pu(n,f) cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Aerosol Chemical Speciation Monitor (ACSM) Composition-Dependent Collection Efficiency (CDCE) Value-Added Product Report

Aerosol particles influence the Earth’s radiation balance directly by absorbing and scattering light and indirectly by influencing cloud formation, properties, and lifetimes. Measurements of aerosol particle optical properties, mass loading, size distributions, microphysical properties, cloud formation properties, and chemical composition are important for understanding the aerosol life cycle and for validating earth system models that predict these quantities. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Aerosol Observing System (AOS) is a highly instrumented platform that measures many of these aerosol properties in situ. The Aerodyne aerosol chemical speciation monitor (ACSM) is a baseline instrument deployed in the AOS. The ACSM provides a quantitative measurement of aerosol particle chemical composition for non-refractory (operationally defined as components that evaporate on the 600ºC vaporizer) aerosol components in real time. Standard output is the mass concentration of particulate organics, nitrate, sulfate, chloride, and ammonium. One well-known limitation to the accuracy of the ACSM data is in evaluating the fraction of the ambient aerosol particles that are detected by the instrument. This quantity is referred to as the collection efficiency (CE) and is often less than unity. This is attributed to particles rebounding after impaction onto the heated vaporizer rather than being trapped, volatilized rapidly, and detected. Other factors, such as divergence of the aerosol particle beam, may also impact CE, but the particle rebound effect is the dominant factor. Scientists will sometimes assume CE = 0.5 (i.e., one half of sampled particles are detected) for ambient particles collected during field missions. However, parameterizations have been developed that express CE as a function of the measured chemical composition, referred to as the composition-dependent collection efficiency (CDCE). The physical explanation for a CDCE, supported by laboratory studies, is that rebound from the vaporizer is a function of the particle phase, with liquid-like particles “sticking” to the vaporizer and solid-like or crystalline particles “bouncing” from the vaporizer. Thus, particles with compositions are liquids-like under the measurement conditions (e.g., certain organics, acidic particles, particles enriched in nitrate) have CE close to unity while crystalline or solid particles (e.g., deliquesced ammonium sulfate) have lower CE. This value-added product (VAP) implements the procedure described by Middlebrook et al. (2012) to correct the ACSM data for the composition-dependent collection efficiency. Applying this parameterization improves the accuracy of the ACSM data and brings them into better agreement with other co-located aerosol measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Offshore Geologic Carbon Storage Data Collection and Data Gaps Analysis

This is a TRS documenting the Offshore Geologic Carbon Storage Data Collection. It describes the Data Collection web application and its creation as well as an accompanying Data Gaps Assessment. We present an interactive data collection and data gaps analysis to aggregate, understand, and disseminate the data that are publicly available to support offshore GCS in the United States. This data collection and data gaps analysis can be leveraged by stakeholders to understand where GCS may be viable offshore, create GCS project analogs, and address challenges to GCS in offshore environments.

58 GEOSCIENCES↗
DOE OSTI2024

PM2.5 Active Aerosol Collection Field Campaign Report

The long-range transport of aerosols can affect local air quality as well as contribute elements and constituents to mountain watersheds that have potentially positive (e.g., nitrate) and negative (e.g., heavy metals) effects to the local ecosystem. Isotopic analysis of aerosols can be a powerful tool for deconvolving the relative contributions of far-distant and local sources to the composition of collected aerosols. Our field campaign involved the week-long collection of PM2.5 (i.e., particulate matter with an aerodynamic diameter of about 2.5 microns) aerosols on filters, which were returned to the laboratories at Lawrence Berkeley National Laboratory (LBNL) for analysis. The sampling sites were located at the Gothic, Colorado Surface Atmosphere Integrated Field Laboratory (SAIL) Atmospheric Radiation Measurement (ARM) and the Mt. Crested Butte, Colorado SAIL ARM sites. The original intention was to measure the lead (Pb) and strontium (Sr) isotopic compositions of the collected aerosols at high precision to provide constraints on source portioning and attribution, as well as analyze the chemical compositions and nitrogen and carbon isotopic compositions. However, severe blank issues arose that prevented the planned isotopic analyses of Sr, Pb, C, and N and severely affected the analyses of the bulk chemical compositions of the collected aerosols, resulting in the failure of the study. The issue is described in Section 2.0.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Identifying Controlling Variables for Mercury Vapors in Alpha-4 at Y-12: Two Year Data Collection Update

Multiple sensor packages were deployed at Alpha-4 by SRNL, in collaboration with United Cleanup Oak Ridge LLC (UCOR), to monitor mercury vapor concentrations and meteorological parameters. These sensors collected data, inside and outside of the legacy-use facility, for approximately two years. Though data gaps still exist, particularly in colder months, several controlling variables were identified that govern mercury vapor concentrations within Alpha-4. Temperature, barometric pressure gradients, humidity, and wind speed have been identified as controlling variables. A strong positive correlation was seen between mercury vapor concentrations and temperature which generally followed diurnal fluctuations. Temperatures below approximately 10 degrees Celsius did not show any spikes above the PEL, indicating more work can be performed at any time during the winter months – more data should be collected to confirm consistency in this finding. Additionally, spikes in mercury vapor concentrations above that of the permissible exposure limit (PEL; 100 µg/m 3 ) occurred primarily in late afternoon or evening/overnight hours (between 3 PM and 6 AM), which suggests D&D operations might be best scheduled during morning or daytime hours prior to the late afternoon. However, a limited number of spikes did occur outside of the identified window, although this may be attributed to disturbances in air flow and mercury vapor release from work activities performed inside of the Alpha-4 building. The analysis conducted allows for a strong predictive capability for estimating mercury vapor concentrations based upon accurate meteorological parameters. Still, additional data collection, particularly in the winter months, could help to strengthen the predictive power and validate the identified data trends. Further, increased temporal resolution could also help to better characterize the incipient stages of the increases and decreases in the mercury vapor concentration. Continued monitoring support by SRNL at Y-12 is underway at Alpha-4 to further close remaining data gaps and support deactivation and decommissioning work. Within a collaborative effort with UCOR, the SRNL team is collecting mercury vapor data to study the efficacy of a novel mercury suppressant, FerroBlack® which was recently deployed at Alpha-4. In addition, modifications to the current monitoring setup to increase measurement resolution is also being investigated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Facilitating Data Collection of Maintenance Events to Populate the Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety and reliability for hydrogen facilities by implementing component reliability data taxonomies that support hydrogen infrastructure failure rate analysis. The project aims to quantify failure rates of hydrogen components through high-quality data collection and analysis on root causes and maintenance needed. HyCReD provides a common database for cataloging hydrogen component failures which exists for reliability research in many other mature industries [2]. The database fills a gap for the hydrogen community by providing a scientifically rigorous approach to quantitative risk assessment (QRA), prognostic health management (PHM), and reliability-centered maintenance (RCM) analysis. High level results will be aggregated and anonymized to protect company sensitive information; detailed results will be used to help address issues of hydrogen components. These advanced analytics will support accelerated deployment of hydrogen infrastructure by enabling better: design and safety of projects (safety codes and standards development), infrastructure reliability and cost (component failure rates, maintenance protocols), and component R&D needs (robust supply chain). A key to a successful HyCReD implementation is facilitating the ease of reporting and data quality in the database that can be used for analysis. Maintenance data was a previously identified gap in initial efforts to populate and validate the database taxonomies [3]. Collection of maintenance data will be instrumental in identifying failure modes and rates, identifying incipient component failures or reduced performance, cataloging best practices for maintenance routines and methods for prognostic health management, and quantifying the risk and effect of different failure modes. Several key priorities are identified for streamlined data collection to achieve quality and detailed failure data: Applicability, Ease of Use, Accessibility, and Information Security. The HyCReD team has now begun deployment of the database to several companies and groups that have signed non-disclosure agreements to facilitate the data collection of failures in industry hydrogen refueling station infrastructure. This paper will provide an update into the process of HyCReD deployment including the development of a coding guide for facility personnel to reference and ensure data quality and consistency from one station to another as well as implementation of contextually dependent data fields of system taxonomy and formatted entries to provide ease of use. The goal is to communicate the lessons learned from the roll-out to technicians and engineers in the field, and the addition of need for high level of security to protect all stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Surface and Buried Thermal, and RGB Unexploded Ordnance Data Collection

This document provides a description of a data collection campaign of unexploded ordnance (UXOI) set. The dataset captures a controlled UAV imaging campaign designed to support detection of UXO across varied environmental conditions. Data were collected during three campaigns in Norris and Northeast Knoxville, Tennessee, using RGB, and thermal sensors mounted on Parrot UKR. In total, the dataset contains 9925 images, 26 full-motion video, and approximately 81.99 GB of data, collected across late spring/summer conditions, every hour during sunlight, and multiple surface contexts, including tall grass, short grass, gravel, as well as buried in sand, and other gravel mixtures. The collection was designed to capture thermal and visual variability relevant to UXO detection in agricultural land, bare earth, and subsurface. Review of the imagery showed that ordnance was most detectable during periods of changing solar input, especially approximately 10-60 minutes after sunrise, approximately 20-60 minutes after sunset, and 2-3 min after cloud cover interrupted prolonged solar heating. These conditions increased thermal contrast because many ordnance items retained or released heat differently than the surrounding vegetation and ground surface. This dataset provides a useful resource for developing and evaluating airborne UXO detection methods under realistic field conditions. All ordnance used in the study was inert, and thermal behavior may differ from that of live ordnance. In addition, variation in ordnance type, composition, and placement introduced differences in thermal response that should be considered when interpreting results.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Collective Neutrino Oscillations and Heavy-element Nucleosynthesis in Supernovae: Exploring Potential Effects of Many-body Neutrino Correlations

In high-energy astrophysical processes involving compact objects, such as core-collapse supernovae or binary neutron star mergers, neutrinos play an important role in the synthesis of nuclides. Neutrinos in these environments can experience collective flavor oscillations driven by neutrino–neutrino interactions, including coherent forward scattering and incoherent (collisional) effects. Recently, there has been interest in exploring potential novel behaviors in collective oscillations of neutrinos by going beyond the one-particle effective or "mean-field" treatments. Here, we seek to explore implications of collective neutrino oscillations, in the mean-field treatment and beyond, for the nucleosynthesis yields in supernova environments with different astrophysical conditions and neutrino inputs. We find that collective oscillations can impact the operation of the νp-process and r-process nucleosynthesis in supernovae. The potential impact is particularly strong in high-entropy, proton-rich conditions, where we find that neutrino interactions can nudge an initial νp-process neutron-rich, resulting in a unique combination of proton-rich low-mass nuclei as well as neutron-rich high-mass nuclei. We describe this neutrino-induced neutron-capture process as the "νi-process." In addition, nontrivial quantum correlations among neutrinos, if present significantly, could lead to different nuclide yields compared to the corresponding mean-field oscillation treatments, by virtue of modifying the evolution of the relevant one-body neutrino observables.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1974

Electron collection theory for a D-region subsonic blunt electrostatic probe

Blunt probe theory for subsonic flow in a weakly ionized and collisional gas is reviewed, and an electron collection theory for the relatively unexplored case, Deybye length approximately 1, which occurs in the lower ionosphere (D-region), is developed. It is found that the dimensionless Debye length is no longer an electric field screening parameter, and the space charge field effect can be negelected. For ion collection, Hoult-Sonin theory is recognized as a correct description of the thin, ion density-perturbed layer adjacent the blunt probe surface. The large volume with electron density perturbed by a positively biased probe renders the usual thin boundary layer analysis inapplicable. Theories relating free stream conditions to the electron collection rate for both stationary and moving blunt probes are obtained. A model based on experimental nonlinear electron drift velocity data is proposed. For a subsonically moving probe, it is found that the perturbed region can be divided into four regions with distinct collection mechanisms.

Wai-Kwong Lai, T.↗
NASA NTRS1975

ERTS-1 data collection system: Status and performance

The Data Collection System flown on the first Earth Resources Technology Satellite (ERTS-1) relays earth resources data from remotely located in-situ sensors to Goddard Space Flight Center. Data is received at Goddard at least twice each day from every sensor installation and is distributed to users (who operate the sensors and transmitters) by mail and teletype. The system consists of a data formatting and transmitting unit, called the Data Collection Platform (DCP), a receiver and a retransmitter aboard ERTS-1; and receiving, demodulating and decoding equipment located at the Goldstone, California and Goddard data acquisition stations. Data is transmitted from the data acquisition stations to the ERTS Control Center at Goddard, then to the NASA (ERTS) Data Processing Facility (NDPF) where it is processed and distributed to users. Experience to date indicates that the design of the ERTS-1 Data Collection System is adequate for operational use for 50% of the users and, with minor modifications, could meet the requirements of 75%. Some users will have to augment the system by other data collection techniques to meet their operational requirements.

Painter, J. E.↗
NASA NTRS1976

Magellan - A balloon-borne collection technique for large cosmic dust particles

The paper describes a balloon-borne system for collecting large (50 to a few hundred micrometers in the major dimension) solid particles falling through the atmosphere at an altitude of about 30 km which are postulated to be fragments of larger cosmic particles or bodies which disintegrate on entering the atmosphere. The major component of the system is the collection surface - a funnel, 7.2 m in diameter, fabricated from mylar, 12 microns thick, and lightly coated with aluminum. Also described is the sample collector, which collects the particles gathered in the apex of the cone. Two successful flights of short duration using zero-pressure balloons have been achieved. Some examples of particles collected are shown. Mg, Al, Si, S, K, Ca, Ti, and Fe have been detected in these particles by energy dispersive X-ray analysis.

Wlochowicz, R.↗
NASA NTRS1977

United States data collection activities and requirements, volume 1

The potential market for a data collection system was investigated to determine whether the user needs would be sufficient to support a satellite relay data collection system design. The activities of 107,407 data collections stations were studied to determine user needs in agriculture, climatology, environmental monitoring, forestry, geology, hydrology, meteorology, and oceanography. Descriptions of 50 distinct data collections networks are described and used to form the user data base. The computer program used to analyze the station data base is discussed, and results of the analysis are presented in maps and graphs. Information format and coding is described in the appendix.

Hrin, S.↗
NASA NTRS1976

Collection efficiency measurements for solar cell research

A system was established for measuring absolute, spectral collection efficiency that is well suited to solar cell research and development. Determination of spectral collection efficiency involves measurements of the incident photon intensity, the device reflection coefficient, and the cell short circuit current. A monochromatic photon flux is obtained with a high intensity Bausch and Lomb monochromator, and an Epply thermopile detector is used to measure incident intensity. Normal incidence reflectivity measurements are achieved with a prism type beam splitter. The experimental approach is discussed, measurements of the reflectivity of evaporated silver films are considered. Collection efficiency measurements of silicon solar cells are presented, and collection efficiency studies of Cu20 solar cells are discussed.

Hampton, H. L.↗