SEARCH · Search NASA

Results for “Data Characterization”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,333 records · Page 74

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Data used in “Enguehard et al. 2022, Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie”

The package contains the data layers used in “Enguehard et al. 2022, Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie”. Spatial data layers include: topography, wetland vegetation cover, time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. The study aims to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2012

Autonomous Onboard Science Data Analysis for Comet Missions

Coming years will bring several comet rendezvous missions. The Rosetta spacecraft arrives at Comet 67P/Churyumov-Gerasimenko in 2014. Subsequent rendezvous might include a mission such as the proposed Comet Hopper with multiple surface landings, as well as Comet Nucleus Sample Return (CNSR) and Coma Rendezvous and Sample Return (CRSR). These encounters will begin to shed light on a population that, despite several previous flybys, remains mysterious and poorly understood. Scientists still have little direct knowledge of interactions between the nucleus and coma, their variation across different comets or their evolution over time. Activity may change on short timescales so it is challenging to characterize with scripted data acquisition. Here we investigate automatic onboard image analysis that could act faster than round-trip light time to capture unexpected outbursts and plume activity. We describe one edge-based method for detect comet nuclei and plumes, and test the approach on an existing catalog of comet images. Finally, we quantify benefits to specific measurement objectives by simulating a basic plume monitoring campaign.

comets↗

NASA NTRS2023

Characterizing Space Weathering Features in Grains From Asteroid Ryugu

Airless bodies such as asteroids are characterized by a lack of a protective atmosphere to guard against the effects of micrometeorite bombardment and solar wind irradiation. These processes, cumulatively known as space weathering, alter the microstructural and chemical properties of grains on asteroidal surfaces, signatures of which are recognized as vesiculated textures, amorphous grain rims, and fe-bearing nanoparticles. The accumulation of these features also causes changes in the optical properties of the surface regolith, complicating the interpretation of remote sensing data and the characterization of returned samples.

L. E. Melendez↗

NASA NTRS1997

Quantitative Measurement of Oxygen in Microgravity Combustion

A low-gravity environment, in space or in ground-based facilities such as drop towers, provides a unique setting for studying combustion mechanisms. Understanding the physical phenomena controlling the ignition and spread of flames in microgravity has importance for space safety as well as for better characterization of dynamical and chemical combustion processes which are normally masked by buoyancy and other gravity-related effects. Due to restrictions associated with performing measurements in reduced gravity, diagnostic methods which have been applied to microgravity combustion studies have generally been limited to capture of flame emissions on film or video, laser Schlieren imaging and (intrusive) temperature measurements using thermocouples. Given the development of detailed theoretical models, more sophisticated diagnostic methods are needed to provide the kind of quantitative data necessary to characterize the properties of microgravity combustion processes as well as provide accurate feedback to improve the predictive capabilities of the models. When the demands of space flight are considered, the need for improved diagnostic systems which are rugged, compact, reliable, and operate at low power becomes apparent. The objective of this research is twofold. First, we want to develop a better understanding of the relative roles of diffusion and reaction of oxygen in microgravity combustion. As the primary oxidizer species, oxygen plays a major role in controlling the observed properties of flames, including flame front speed (in solid or liquid flames), extinguishment characteristics, flame size and flame temperature. The second objective is to develop better diagnostics based on diode laser absorption which can be of real value in both microgravity combustion research and as a sensor on-board Spacelab as either an air quality monitor or as part of a fire detection system. In our prior microgravity work, an eight line-of-sight fiber optic system measured water vapor mole fractions in the NASA Lewis 2.2-sec Drop Tower. In that system, the laser and all electronics resided at the top of the drop tower and was connected via a fiber optic cable to the rig, on which a 'pitch and catch' set of fiber collimating lenses were used to transmit the laser beam across a jet diffusion flame. This system required eight independent detection/demodulation units and had poor spatial resolution. This research builds on this earlier work, resulting in an improved capability for quantitative, nonintrusive measurement of major combustion species. A vertical cavity surface-emitting diode laser (VCSEL) and a continuous spatial scanning method permit the measurement of temporal and spatial profiles of the concentrations and temperatures of molecular oxygen. High detection sensitivity is achieved with wavelength modulation spectroscopy (WMS). One-g experiments are performed using a slot diffusion flame. Microgravity measurements on a solid fuel (cellulose sheet) system are planned for the NASA Lewis 2.2-second Drop Tower Facility.

Silver, Joel A.↗

NASA NTRS2004

Caltrans Keeps the Spitzer Pipelines Moving

The computer pipelines used to process digital infrared astronomical images from NASA's Spitzer Space Telescope require various input calibration-data files for characterizing the attributes and behaviors of the onboard focal-plane-arrays and their detector pixels, such as operability, dark-current offset, linearity, non- uniformity, muxbleed, droop, and point-response functions. The telescope has three very different science instruments, each with three or four spectral-band-pass channels, depending on the instrument. Moreover, each instrument has various operating modes (e-g., full array or sub-array in one case) and parameters (e.g., integration time). Calibration data that depend on these considerations are needed by pipelines for generating both science products (production pipelines) and higher-level calibration products (calibration pipelines). The calibration files are created in various formats either 'off-line' or by the aforementioned calibration pipelines, depending on the above configuration details. Also, the calibration files are generally applicable to a certain time period and therefore must be selected accordingly for a given raw input image to be correctly processed. All of this complexity in selecting and retrieving calibration files for pipeline processing is handled by a procedural software-program called 'caltrans' . This software, which is implemented in C and interacts with an Informix database, was developed at the Spitzer Science Center (SSC) and is now deployed in SSC daily operations. The software is rule-based, very flexible, and, for efficiency, capable of retrieving multiple calibration files with a single software-execution command.

Spitzer↗

NASA NTRS2004

Systems Characterization of Combustor Instabilities With Controls Design Emphasis

This effort performed test data analysis in order to characterize the general behavior of combustor instabilities with emphasis on controls design. The analysis is performed on data obtained from two configurations of a laboratory combustor rig and from a developmental aero-engine combustor. The study has characterized several dynamic behaviors associated with combustor instabilities. These are: frequency and phase randomness, amplitude modulations, net random phase walks, random noise, exponential growth and intra-harmonic couplings. Finally, the very cause of combustor instabilities was explored and it could be attributed to a more general source-load type impedance interaction that includes the thermo-acoustic coupling. Performing these characterizations on different combustors allows for more accurate identification of the cause of these phenomena and their effect on instability.

Kopasakis, George↗

DOE OSTI2025

Geospatial Data Workflow Orchestration and Architecture

In an era characterized by explosive growth in geospatial data, the selection of appropriate technologies for data storage, processing, and orchestration is critical for organizations aiming to maintain competitive advantages. This white paper provides a comprehensive analysis of how Oak Ridge National Laboratory (ORNL) has effectively employed various cloud technologies, including containerized applications, container orchestrators, and workflow orchestrators, to develop robust geospatial data processing solutions. We explore the fundamental concepts behind these technologies and compare multiple deployment models tailored to diverse use cases. Our findings conclude that while Kubernetes has emerged as the preferred platform for truly scalable and fault-tolerant production workflows, the choice of workflow orchestration tool requires careful consideration of team needs, pipeline complexity, and deployment environments. This paper aims to serve as a strategic guide for organizations leveraging geospatial data, articulating the balance between technology choices and practical implementation to enhance workflow efficacy and scalability.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2024

Key Perseverance Sampling Locations for the Ancient Martian Crust and Implications for Mars Science

Since Feb 2021, the Perseverance rover has collected samples in the Jezero crater. The plan baselined at the 2018 landing site selection, subsequently further developed by the Mars-2020 team, and presented to the Decadal Survey included the exploration and sampling of the Jezero crater rim and the Nili Planum area, a rock record that is important to preserving the science return of the endeavor. Specifically, the science team identified the following prioritized science objectives aligned with community objectives that are not covered by the current sample cache: 1) Investigate the habitable environments with potential biosignatures from a more ancient time interval and from a diverse set of geological environments (incl. exposed subsurface) than the Jezero crater sedimentary deposits (Fig. 2). (2) Determine radioisotopic ages for well-defined craterretaining surfaces and/or the Isidis basin impact event. (3) Characterize ancient aqueous environments to study climate, environmental transitions, and habitability on ancient Mars. (4) Investigate planetary accretion, crustal evolution, and dynamo activity through analysis and sampling of igneous lithologies. (5) Study the geology of basin-forming impacts. In addition, for the Jezero rim and any Jezero ejecta: (6) Analyze Jezero impactites for potentially habitable hydrothermal environments and radioisotopic dating of the Jezero crater formation. From 2018 to now, we used a combination of High Resolution Imaging Experiment (HiRISE) and Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data to further characterize Jezero rim and Nili Planum, culminating in our prioritized sample location recommendations: (1) Monument Valley and (2) Northwest Jezero rim.

Mars sample return↗

NASA NTRS2017

The First Fermi-LAT SNR Catalog and Cosmic Ray Implications

While supernova remnants (SNRs) are widely thought to be powerful cosmic-ray accelerators, indirect evidence comes from a small number of well-studied cases. Here we systematically determine the gamma-ray emission detected by the Fermi Large Area Telescope (LAT) from all known Galactic SNRs, disentangling them from the sea of cosmic-ray generated photons in the Galactic plane. Using LAT data we have characterized the 1-100 GeV emission in 279 regions containing SNRs, accounting for systematic uncertainties caused by source misattribution and instrumental response. We classified 30 sources as SNRs, using spatial overlap with the radio emission position. For all the remaining regions we evaluated upper limits on SNRs' emission. In the First Fermi-LAT SNR Catalog there is a study of the common characteristics of these SNRs, such as comparisons between GeV, radio and TeV quantities. We show that previously satisfactory models of SNRs' GeV emission no longer adequately describe the data. To address the question of cosmic ray (CR) origins, we also examine the SNRs' maximal CR contribution assuming the GeV emission arises solely from proton interactions. Improved breadth and quality of multiwavelength (MW) data, including distances and local densities, and more, higher resolution gamma-ray data with correspondingly improved Galactic diffuse models will strengthen this constraint.

de Palma, F.↗

NASA NTRS2016

The First Fermi-LAT SNR Catalog and Cosmic Ray Implications

While supernova remnants (SNRs) are widely thought to be powerful cosmicray accelerators, indirect evidence comes from a small number of well-studied cases. Here we systematically determine the gamma-ray emission detected by the ermi Large Area Telescope (LAT) from all known Galactic SNRs, disentangling them from the sea of cosmic-ray generated photons in the Galactic plane. Using LAT data we have characterized the 1-100 GeV emission in 279 regions containing SNRs, accounting for systematic uncertainties caused by source misattribution and instrumental response. We classified 30 sources as SNRs, using spatial overlap with the radio emission position. For all the remaining regions we evaluated upper limits on SNRs' emission. In the First Fermi-LAT SNR Catalog there is a study of the common characteristics of these SNRs, such as comparisons between GeV, radio and TeV quantities. We show that previously satisfactory models of SNRs' GeV emission no longer adequately describe the data. To address the question of cosmic ray (CR) origins, we also examine the SNRs' maximal CR contribution assuming the GeV emission arises solely from proton interactions. Improved breadth and quality of multiwavelength (MW) data, including distances and local densities, and more, higher resolution gamma-ray data with correspondingly improved Galactic diffuse models will strengthen this constraint.

de Palma, F.↗

DOE OSTI2015

Compositional analysis of biomass reference materials: Results from an interlaboratory study

Biomass compositional methods are used to compare different lignocellulosic feedstocks, to measure component balances around unit operations and to determine process yields and therefore the economic viability of biomass-to-biofuel processes. Four biomass reference materials (RMs NIST 8491–8494) were prepared and characterized, via an interlaboratory comparison exercise in the early 1990s to evaluate biomass summative compositional methods, analysts, and laboratories. Having common, uniform, and stable biomass reference materials gives the opportunity to assess compositional data compared to other analysts, to other labs, and to a known compositional value. The expiration date for the original characterization of these RMs was reached and an effort to assess their stability and recharacterize the reference values for the remaining material using more current methods of analysis was initiated. We sent samples of the four biomass RMs to 11 academic, industrial, and government laboratories, familiar with sulfuric acid compositional methods, for recharacterization of the component reference values. In this work, we have used an expanded suite of analytical methods that are more appropriate for herbaceous feedstocks, to recharacterize the RMs’ compositions. We report the median values and the expanded uncertainty values for the four RMs on a dry-mass, whole-biomass basis. The original characterization data has been recalculated using median statistics to facilitate comparisons with this data. We found improved total component closures for three out of the four RMs compared to the original characterization, and the total component closures were near 100 %, which suggests that most components were accurately measured and little double counting occurred. Here, the major components were not statistically different in the recharacterization which suggests that the biomass materials are stable during storage and that additional components, not seen in the original characterization, were quantified here.

09 BIOMASS FUELS↗

DOE OSTI2021

bnl/pub-Maffettone_2020_08

The application of the XCA package as first demonstrated in aXiv:2008.00283. ABSTRACT: The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time consuming, error prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications --- rather than absolutes --- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering unprecedented time savings, and is demonstrated on a diverse set of organic and inorganic materials challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

Maffettone, PhillipM [Brookhaven National Lab. (BN↗

DOE OSTI2013

PHOBOS AS A D-TYPE CAPTURED ASTEROID, SPECTRAL MODELING FROM 0.25 TO 4.0 μm

This paper describes the spectral modeling of the surface of Phobos in the wavelength range between 0.25 and 4.0 μm. We use complementary data to cover this spectral range: the OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System on board the ESA Rosetta spacecraft) reflectance spectrum that Pajola et al. merged with the VSK-KRFM-ISM (Videospectrometric Camera (VSK)-Combined Radiometer and Photometer for Mars (KRFM)-Imaging Spectrometer for Mars (ISM) on board the USSR Phobos 2 spacecraft) spectra by Murchie and Erard and the IRTF (NASA Infrared Telescope Facility, Hawaii, USA) spectra published by Rivkin et al. The OSIRIS data allow the characterization of an area of Phobos covering from 86.°8 N to 90° S in latitude and from 126° W to 286° W in longitude. This corresponds chiefly to the trailing hemisphere, but with a small sampling of the leading hemisphere as well. We compared the OSIRIS results with the Trojan D-type asteroid 624 Hektor and show that the overall slope and curvature of the two bodies over the common wavelength range are very similar. This favors Phobos being a captured D-type asteroid as previously suggested. We modeled the OSIRIS data using two models, the first one with a composition that includes organic carbonaceous material, serpentine, olivine, and basalt glass, and the second one consisting of Tagish Lake meteorite and magnesium-rich pyroxene glass. The results of these models were extended to longer wavelengths to compare the VSK-KRFM-ISM and IRTF data. The overall shape of the second model spectrum between 0.25 and 4.0 μm shows curvature and an albedo level that match both the OSIRIS and Murchie and Erard data and the Rivkin et al. data much better than the first model. The large interval fit is encouraging and adds weight to this model, making it our most promising fit for Phobos. Since Tagish Lake is commonly used as a spectral analog for D-type asteroids, this provides additional support for compositional similarities between Phobos and D-type asteroids.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Autonomous Inversion of In Situ Deformation Measurement Data for Injection-Induced Stress Change

Geologic carbon storage (GCS) is likely to play a key part of the global effort to dramatically reduce CO2 emissions and perhaps even reduce atmospheric CO2 concentrations through carbon negative operations. A critical part of effort to commercialize and widely deploy this technology is developing the capability to rapidly assimilate real-time monitoring data into a form that will enable site operators to make decisions to manage the safe and efficient operations. Two of the risks associate with GCS are the risk of inducing fractures in the sealing formations that can create leakage pathways and the risk of inducing earthquakes of sufficient magnitude to cause public concern, property damage, or safety risks. To properly manage these risks the site operator needs to know the initial state of stress, the change in stress induced by injection, and the relationship between operational parameters such as injection rate and pressure and the change in stress. Current methods of estimating the change in stress require choosing the type of constitutive model and the model parameters based on core, log, and geophysical data during the characterization phase, with little feedback from operational observations to validate or refine these choices. These characterization methods interrogate the geologic formations using length scales, loading rates or magnitudes that are quite different from those encountered by the actual storage system. It is shown that errors in the assumed constitutive response, even when informed by laboratory tests on core samples, are likely to be common, large, and underestimate the magnitude of stress change caused by injection. Recent advances in borehole-based strain instruments and borehole and surface-based tilt and displacement instruments have now enabled monitoring of the deformation of the storage system throughout its operational lifespan. This data can enable validation and refinement of the knowledge of the geomechanical properties and state of the system, but brings with it a challenge to transform the raw data into actionable knowledge. We demonstrate a method that uses automatic differentiation and a finite-element based geomechanical model perform a gradient-based deterministic inversion of geomechanical monitoring data. This approach allows autonomous integration of the instrument data without the need for time consuming manual interpretation and selection of updated model parameters. Furthermore, only isotropic linear elasticity is considered in this paper, the approach presented is very flexible as to what type of geomechanical constitutive response can be used. The approach is easily adaptable to nonlinear physics-based constitutive models to account for common rock behaviors such as creep and plasticity. The approach also enables training of machine learning-based constitutive models by allowing back propagation of errors through the finite element calculations. This enables strongly enforcing known physics, such as conservation of momentum and continuity, while allowing data-driven models to learn the truly unknown physics such as the constitutive or petrophysical responses.

Burghardt, Jeffrey A.↗

DOE OSTI2016

Extended magnetic exchange interactions in the high-temperature ferromagnet MnBi

The high-temperature ferromagnet MnBi continues to receive attention as a candidate to replace rare-earth-containing permanent magnets in applications above room temperature. This is due to a high Curie temperature, large magnetic moments, and a coercivity that increases with temperature. The synthesis of MnBi also allows for crystals that are free of interstitial Mn, enabling more direct access to the key interactions underlying the physical properties of binary Mn-based ferromagnets. In this work, we use inelastic neutron scattering to measure the spin waves of MnBi in order to characterize the magnetic exchange at low temperature. Consistent with the spin reorientation that occurs below 140 K, we do not observe a spin gap in this system above our experimental resolution. A Heisenberg model was fit to the spin wave data in order to characterize the long-range nature of the exchange. It was found that interactions up to sixth nearest neighbor are required to fully parametrize the spin waves. Surprisingly, the nearest-neighbor term is antiferromagnetic, and the realization of a ferromagnetic ground state relies on the more numerous ferromagnetic terms beyond nearest neighbor, suggesting that the ferromagnetic ground state arises as a consequence of the long-ranged interactions in the system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Industry-Average Performance for Components and Initiating Events at U.S. Commercial Nuclear Power Plants: 2020 Update

This report documents the quantitative results of the current industry-average performance for components and initiating events (IEs) at U.S. commercial nuclear power plants (NPPs). It represents the third update of the original analysis in NUREG/CR-6928 with data through 2020. Continuous characterization and updating of current industry-average performance with the latest industry data available are important steps in maintaining up-to-date risk models. Typically, data from 1998–2002 were used in NUREG/CR-6928, data from 1998–2010 in the first update, data from 1998–2015 in the second update, and data from 2006–2020 in this update, although many IEs required longer periods for adequate characterization of frequencies in all these analyses. As with NUREG/CR-6928 and previous updates, four types of events are covered in this report: component unreliability (e.g., a pump that fails to start or fails to run), component or train unavailability resulting from test or maintenance outages, special event probabilities covering operational issues (e.g., pump restarts and injection valve re-openings during unplanned demands), and IE frequencies. Results (in the form of beta distributions for failure probabilities upon demand and gamma distributions for rates) are used as inputs to the U.S. Nuclear Regulatory Commission standardized plant analysis risk models covering U.S. commercial NPPs.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Examining the Characteristics of the Cropland Data Layer in the Context of Estimating Land Cover Change

The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) provides spatially explicit information about crop production area and has served as a prevalent data source for characterizing cropland change in the U.S. in the last decade. Understanding the accuracy of the CDL is paramount because of the reliance on it for management and policy making. This study examined the characteristics of the CDL from 2007 to 2017 using comparisons to other USDA datasets. The results showed when examining the cropland area for the same year, the CDL produced comparable trends with other datasets (R 2 > 0.95), but absolute area differed. The estimated area of cropland changes from 2007 to 2012, 2008 to 2012 and 2012 to 2017 varied from weak to moderate correlation between the CDL and the tabular data (R 2 = 0.005~0.63). Differences in area of cropland change varied widely between data sources with the CDL estimating much larger change area. A series of image processing techniques designed to improve the confidence in cropland change estimated using the CDL reduced the area of estimated cropland change. The techniques also, unexpectedly, lowered the correlation in change estimated between the CDL and the tabular datasets. Estimated land cover change area varied widely based on analyses applied and could reverse from increasing to declining area in cropland. Further analyses showed unlikely change scenarios when comparing different year combinations. The authors recommend the CDL only be used for land cover change analysis if the error can be estimated and is within change estimates.

58 GEOSCIENCES↗

NASA NTRS2017

Test and Analysis of Solid Rocket Motor Nozzle Ablative Materials

Asbestos free solid motor internal insulation samples were tested at the MSFC Hyperthermal Facility. Objectives of the test were to gather data for analog characterization of ablative and in-depth thermal performance of rubber materials subject to high enthalpy/pressure flow conditions. Tests were conducted over a range of convective heat fluxes for both inert and chemically reactive sub-sonic free stream gas flow. Instrumentation included use of total calorimeters, thermocouples, and a surface pyrometer for surface temperature measurement. Post-test sample forensics involved measurement of eroded depth, charred depth, total sample weight loss, and documentation of the general condition of the eroded profile. A complete Charring Material Ablator (CMA) style aero-thermal analysis was conducted for the test matrix and results compared to the measured data. In general, comparisons were possible for a number of the cases and the results show a limited predictive ability to model accurately both the ablative response and the in-depth temperature profiles. Lessons learned and modeling recommendations are made regarding future testing and modeling improvements that will increase understanding of the basic chemistry/physics associated with the complicated material ablation process of rubber materials.

Clayton, J. Louie↗