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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Marshall Space Flight Center's Impact Testing Facility Capabilities

Marshall Space Flight Center's (MSFC) Impact Testing Facility (ITF) serves as an important installation for space and missile related materials science research. The ITF was established and began its research in spacecraft debris shielding in the early 1960s, then played a major role in the International Space Station debris shield development. As NASA became more interested in launch debris and in-flight impact concerns, the ITF grew to include research in a variety of impact genres. Collaborative partnerships with the DoD led to a wider range of impact capabilities being relocated to MSFC as a result of the closure of Particle Impact Facilities in Santa Barbara, California, The Particle Impact Facility had a 30 year history in providing evaluations of aerospace materials and components during flights through rain, ice, and solid particle environments at subsonic through hypersonic velocities. The facility's unique capabilities were deemed a 'National Asset' by the DoD, The ITF now has capabilities including environmental, ballistic, and hypervelocity impact testing utilizing an array of air, powder, and two-stage light gas guns to accommodate a variety of projectile and target types and sizes. Relocated test equipment was dated and in need of upgrade. Numerous upgrades including new instrumentation, triggering circuitry, high speed photography, and optimized sabot designs have been implemented. Other recent research has included rain drop demise characterization tests to obtain data for inclusion in on-going model development. Future ITF improvements will be focused on continued instrumentation and performance enhancements. These enhancements will allow further, more in-depth, characterization of rain drop demise characterization and evaluation of ice crystal impact. Performance enhancements also include increasing the upper velocity limit of the current environmental guns to allow direct environmental simulation for missile components. The current and proposed ITF capabilities range from rain to micrometeoroids allowing the widest test parameter range possible for materials investigations in support of space, atmospheric, and ground environments. These test capabilities including hydrometeor, single/multi-particle, ballistic gas guns, exploding wire gun, and light gas guns combined with Smooth Particle Hydrodynamics Code (SPHC) simulations represent the widest range of impact test capabilities in the country.

Evans, Steve↗
DOE OSTI2013

Data communications in a parallel active messaging interface of a parallel computer

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer, the parallel computer including a plurality of compute nodes that execute a parallel application, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources, including receiving in an origin endpoint of the PAMI a data communications instruction, the instruction characterized by an instruction type, the instruction specifying a transmission of transfer data from the origin endpoint to a target endpoint and transmitting, in accordance with the instruction type, the transfer data from the origin endpoint to the target endpoint.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Pursuing Cost Effective Tank Waste Characterization at the Savannah River Site - 16172

The U. S. Department of Energy Office of Environmental Management has tasked the Savannah River National Laboratory (SRNL) with developing strategies and technologies to understand, optimize, scale, and speed up tank waste characterization. This scope is part of a multi-year project with the end goal of implementing programmatic changes that accelerate tank waste processing and tank closure schedules, and at the same time reduce characterization costs, while maintaining data integrity. The project is currently in its second year. During the first year of the project, SRNL completed a series of activities focused on understanding the range of current characterization practices, needs, gaps, risks, and potential alternative approaches. Based on the results, conclusions were drawn regarding aspects of the programs that are most costly and time consuming; particular waste constituents that drive costs, schedule, and program risks; alternative characterization approaches (other than sampling and analysis) that are less expensive and more rapid; new laboratory methods holding the greatest promise for reducing characterization costs and schedule; and in whole, the primary areas where current characterization practices can be improved. SRNL's current scope is focusing on three primary activities: 1) development of a technical basis/strategy for improving the cost effectiveness and schedule of SRNL's tank closure characterization program; 2) design/assembly of hardware, plumbing, and software for automating select radiochemical separation and waste removal processes; and 3) development and testing of alternative radiochemical separation protocols most likely to improve high resource demand/time consuming analysis methods (such as Ra-226, Pa-231, Tc-99/I-129, and/or Y/trivalent actinide separations). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2021. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data.

energy efficiency mobility↗
DOE OSTI2023

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2022. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data. Anyone can create an account and access data at https://livewire.energy.gov/.

energy efficiency↗
DOE OSTI2024

Tunable Solid‐State Properties and Anisotropic Charge Mobility in Hydrogen‐Bonded Diketopyrrolopyrrole Polymers via Automated Device Fabrication and Characterization

The optoelectronic properties of semiconducting polymers and device performance rely on a delicate interplay of design and processing conditions. However, screening and optimizing the relationships between these parameters for reliably fabricating organic electronics can be an arduous task requiring significant time and resources. To overcome this challenge, Polybot is developed—a robotic platform within a self‐driving lab that can efficiently produce organic field‐effect transistors (OFETs) from various semiconducting polymers via high‐throughput blade coating deposition. Polybot not only handles the fabrication process but also can conduct characterization tests on the devices and autonomously analyze the data gathered, thus facilitating the rapid acquisition of data on a large scale. This work leverages the capabilities of this platform to investigate the fabrication of OFETs using hydrogen bonding‐containing semiconducting polymers. Through high‐throughput fabrication and characterization, various data trends are analyzed, and large extents of anisotropic charge mobility are observed in devices. The materials are thoroughly characterized to understand the role of processing conditions in solid state and electronic properties of these organic semiconductors. The findings demonstrate the effectiveness of automated fabrication and characterization platforms in uncovering novel structure–property relationships, facilitating refinement of rational chemical design, and processing conditions, ultimately leading to new semiconducting materials.

automated fabrication and characterization↗
NASA NTRS2002

NASA IKONOS Radiometric Characterization

NASA acquired imagery from the IKONOS satellite as part of its Scientific Data Purchase (SDP) program, which purchases scientific data sets from commercial sources. This viewgraph presentation describes the IKONOS satellite and its sensors, and then gives an overview of characterization efforts undertaken by NASA in cooperation with other government agencies. The characterization included relative radiometric correction, absolute radiometric characterization of data from Lunar Lake Playa, Nevada, and calibration of data from Stennis Space Center, Mississippi.

Pagnutti, Mary↗
NASA NTRS2010

Characterization of Orbital Debris Photometric Properties Derived from Laboratory-Based Measurements

To better characterize and model optical data acquired from ground-based telescopes, the Optical Measurements Center (OMC) at NASA/JSC attempts to emulate illumination conditions seen in space using equipment and techniques that parallel telescopic observations and source-target-sensor orientations. The OMC uses a 75 Watt Xenon arc lamp as a solar simulator, an SBIG CCD camera with standard Johnson/Bessel filters, and a robotic arm to simulate an object's position and rotation. The laboratory uses known shapes, materials suspected to be consistent with the orbital debris population, and three phase angles to best match the lighting conditions of the telescope based data. The fourteen objects studied in the laboratory are fragments or materials acquired through ground-tests of scaled-model satellites/rocket bodies as well as material samples in more/less "flight-ready" condition. All fragments were measured at 10 increments in a full 360 rotation at 6 , 36 , and 60 phase angles. This paper will investigate published color photometric data for a series of orbital debris targets and compare it to the empirical photometric measurements generated in the OMC. Using the data acquired over specific rotational angles through different filters (B, V, R, I), a color index is acquired (B-R, R-I). Using these values and their associated lightcurves, this laboratory data is compared to observational data obtained on the 1 m telescope of the Astronomical Institute of the University of Bern (AUIB), the 0.9 m operated by the Small- and Medium-Aperture Research Telescope System (SMARTS) Consortium and the Curtis-Schmidt 0.6 m Michigan Orbital Debris Space Debris Telescope both located at Cerro Tololo Inter-American Observatory (CTIO). An empirical based optical characterization model will be presented to provide preliminary correlations between laboratory based and telescope-based data in the context of classification of GEO debris objects.

Cowardin, H.↗
DOE OSTI2021

DEEPEN Data Catalog for Magmatic Geothermal Systems in the United States

This data catalog contains information related to the Training Site Analysis for the Geothermica project "DE-risking Exploration of geothermal Plays in magmatic ENvironments (DEEPEN)." The DEEPEN project aims to reduce exploration risk for geothermal fluids in magmatic systems by developing improved an improved framework for interpretation of exploration data using the Play Fairway Analysis (PFA) methodology. The Training Site Analysis performed for DEEPEN leverages existing datasets to develop a customized PFA approach to exploration for multiple geothermal resource types in magmatic systems (conventional hydrothermal resources, supercritical fluid and superheated steam resources, and superhot EGS resources). This data catalog contains links to publicly available data files related to 8 training sites in the United States. US training sites are: the Cascades/Aleutians PFA project; the Hawaii PFA project, the Oregon Cascades PFA project, the Snake River Plain, Idaho PFA project, the Washington State PFA project, Newberry Volcano, Coso Geothermal Field, and the Geysers Geothermal field. This database contains an overview of these training sites, data sources, and links to publicly available exploration datasets. For the five PFA projects, details on exploration data related to PFA components (heat, fluid, permeability, sometimes seal) are provided, including a summary of data weighting methodologies.

15 GEOTHERMAL ENERGY↗
NASA NTRS2010

Cryogenic Absorption Cells Operating Inside a Bruker IFS-125HR: First Results for 13CH4 at 7 Micrometers

New absorption cells designed specifically to achieve stable temperatures down to 66 K inside the sample compartment of an evacuated Bruker IFS-125HR Fourier transform spectrometer (FTS) were developed at Connecticut College and tested at the Jet Propulsion Laboratory (JPL). The temperature stabilized cryogenic cells with path lengths of 24.29 and 20.38 cm were constructed of oxygen free high conductivity (OFHC) copper and fitted with wedged ZnSe windows using vacuum tight indium seals. In operation, the temperature-controlled cooling by a closed-cycle helium refrigerator achieved stability of 0.01 K. The unwanted absorption features arising from cryodeposits on the cell windows at low temperatures were eliminated by building an internal vacuum shroud box around the cell which significantly minimized the growth of cryodeposits. The effects of vibrations from the closed-cycle helium refrigerator on the FTS spectra were characterized. Using this set up, several high-resolution spectra of methane isotopologues broadened with nitrogen were recorded in the 1200-1800 per centimeter spectral region at various sample temperatures between 79.5 and 296 K. Such data are needed to characterize the temperature dependence of spectral line shapes at low temperatures for remote sensing of outer planets and their moons. Initial analysis of a limited number of spectra in the region of the R(2) manifold of the v4 fundamental band of 13CH4 indicated that an empirical power law used for the temperature dependence of the N2-broadened line widths would fail to fit the observed data in the entire temperature range from 80 to 296 K; instead, it follows a temperature-dependence similar to that reported by Mondelain et al. [17,18]. The initial test was very successful proving that a high precision Fourier transform spectrometer with a completely evacuated optical path can be configured for spectroscopic studies at low temperatures relevant to the planetary atmospheres.

Sung, K.↗
NASA NTRS1977

State-of-the-art assessment of electric vehicles and hybrid vehicles

The Electric and Hybrid Vehicle Research, Development, and Demonstration Act of 1976 (PL 94-413) requires that data be developed to characterize the state of the art of vehicles powered by an electric motor and those propelled by a combination of an electric motor and an internal combustion engine or other power sources. Data obtained from controlled tests of a representative number of sample vehicles, from information supplied by manufacturers or contained in the literature, and from surveys of fleet operators of individual owners of electric vehicles is discussed. The results of track and dynamometer tests conducted by NASA on 22 electric, 2 hybrid, and 5 conventional vehicles, as well as on 5 spark-ignition-engine-powered vehicles, the conventional counterparts of 5 of the vehicles, are presented.

Source record↗
NASA NTRS2018

Implementation of J-A Methodology Elastic-Plastic Crack Instability Analysis Capability into the WARP-3D Code

Characterization of the near crack-tip stress/strain fields is the foundation of fracture mechanics. The description of the near tip stress field and the prediction of when fracture occurs is well established for brittle materials that exhibit linear elastic behavior. However, in ductile materials or conditions that violate linear elastic assumptions (Aluminum alloys, Al 2024-T3, Al 2024- T351 etc.), the elastic-plastic crack-tip stress fields are characterized by the Hutchison-Rice-Rosengren (HRR) field. The J-integral is commonly used to characterize amplitude of the HRR field under elastic-plastic conditions. The J-integral has been demonstrated for crack-tip fields that are under high constraint conditions (i.e., small-scale plasticity where the J-dominance is maintained). However, as the external load increases, yielding changes from small- to largescale plasticity and usually a loss of constraint (i.e., reduction in the triaxial stress field along the crack front). The loss of constraint leads to the deviation of the crack-tip stress fields from that given by the HRR field. Hence, the J-dominance will be gradually lost and additional parameter(s) are required to quantify the crack-tip stress fields and predict fracture behavior. The assessment objectives were to: 1) implement a two-parameter (i.e., J-A) fracture criterion into an elastic-plastic three-dimensional (3D) finite element analysis (FEA), 2) validate the implementation by comparison with the A parameter from literature data, 3) conduct material characterization tests to quantify the material behavior and provide fracture data for validation of the J-A fracture criteria, and (4) perform evaluations to establish if the J-A criteria can be used to predict fracture in a ductile metallic material (e.g., aluminum alloys). The A parameter in these criteria is the second parameter in a three-term elastic-plastic asymptotic expansion of the neartip stress behavior. A series of extensive FEAs were performed using WARP3D software package to obtain solutions for the A parameter for different specimen configurations. The methodology needed for the estimation of the A parameter in the asymptotic expansion was developed and implemented using Matlab®. A user material (UMAT) routine was used to model the material stress-strain response using a Ramberg-Osgood power law with a hardening exponent (n) and a material coefficient (alpha). This UMAT routine was successfully implemented in WARP3D software and validated through comparison with the experimental data. Three configurations were extracted from published results: 1) center cracked plate (CCP), 2) single edge-cracked plate (SECP), and 3) double edge-cracked plate (DECP). These configurations and four other configurations (three-hole tension (THT)), three-point bend (3PTB), three-hole compact tension (3PCT), and compact tension (CT)) were analyzed to verify the methodology that was developed and implemented into WARP3D. Solutions of the A parameter were obtained for remote tension loading conditions that started with small-scale yielding and continued into the large-scale plasticity regime. The results indicate that the methodology developed can be used to calculate the elastic-plastic J-A parameters for test specimens with a range of crack geometries, material strain hardening behaviors, and loading conditions. The J-A parameters were implemented as fracture criteria and used to predict the test results. For comparison, other fracture criteria were used to predict the same test results. Major findings include: The A constraint parameter A varies with specimen type and applied load thus accurate determination is crucial in predicting the failure load, and the A parameter is asymptotic as the failure load is approached, making an accurate determination difficult (i.e., small differences in the A parameter can cause large variations in failure load) for materials exhibiting elastic-plastic behavior. The failure predictions from J-A methodology were more accurate than the traditionally used KC and J methods, and have comparable scatter to that observed when using the crack-tip opening angle (CTOA) method. However, the J-A methodology requires considerable effort (expertise level and labor) to implement and to evaluate the A parameter for different specimen types and materials, or to apply this methodology to part-through crack (e.g., 3D problems) structural applications.

Hamm, Kenneth R., Jr.↗
NASA NTRS2010

Cross-Characterization of Aerosol Properties from Multiple Spaceborne Sensors Facilitated by Regional Ground-Based Observations

Aerosol observations from space have become a standard source for retrieval of aerosol properties on both regional and global scales. Indeed, the large number of currently operational spaceborne sensors provides for unprecedented access to the most complete set of complimentary aerosol measurements ever to be available. Nonetheless, this resource remains under-utilized, largely due to the discrepancies and differences existing between the sensors and their aerosol products. To characterize the inconsistencies and bridge the gap that exists between the sensors, we have designed and implemented an online Multi-sensor Aerosol Products Sampling System (MAPSS) that facilitates the joint sampling of aerosol data from multiple sensors. MAPSS consistently samples aerosol products from multiple spaceborne sensors using a unified spatial and temporal resolution, where each dataset is sampled over Aerosol Robotic Network (AERONET) locations together with coincident AERONET data samples. In this way, MAPSS enables a direct cross-characterization and data integration between aerosol products from multiple sensors. Moreover, the well-characterized co-located ground-based AERONET data provides the basis for the integrated validation of these products.

Petrenko, Maksym↗
DOE OSTI2020

Microstructure reconstruction of battery polymer separators by fusing 2D and 3D image data for transport property analysis

A new approach to generate high-fidelity 3D microstructure reconstructions by leveraging resolution and sample volume characteristics from 2D and 3D microscopy methods is presented here. This approach is employed to model the microstructure of a highly orthotropic polypropylene separator used in lithium-ion batteries, which have challenging multi-scale features of fibrils (<100 nm) and lamellae (>100 nm) to resolve in 3D. Phase contrast nano X-ray computed tomographic data are used to reconstruct the lamellae phase, while 2D scanning electron microscopy data are used to characterize sub-100 nm microstructure features such as the thin fibrils that are beyond the effective resolution of X-ray computed tomography. Fibril geometries are reconstructed stochastically based on the 2D higher resolution data, and integrated with the lamellae geometries in 3D space. Transport property analyses are performed to investigate the bias of microstructure models without considering the fibrils. A sensitivity study is also conducted to facilitate understanding of the relationship between microstructure characteristics and transport properties.

25 ENERGY STORAGE↗
DOE OSTI2016

Synthesis and characterization of dihexyldithiocarbamate as a chelating agent in extraction of gold(III)

The use of dialkyldithiocarbamates as chelating agents of transition metals have been developing for decades. Many chelating agents have been synthesized and used in the extraction of the metals. Studies on particular aspects of extraction of the metals, such as the effect of increasing hydrophobicity of chelating agents on the effectiveness of the extraction, have been done. However, despite the many studies on the synthesis and applications of this type of chelating agents, interests in the aspect of molecular structure of the synthesized ligands and of their complexes, have been limited. This study aimed at synthesizing and characterizing dihexylthiocarbamate, and using the ligand for the extraction of gold III). Characterization of the ligand and of its metal complex were done by using elemental analysis, DTG, and spectroscopic methods to include NMR, ({sup 1}H, and {sup 13}C), FTIR, and MS-ESI. Data on the synthesis, characterization, and the application of the ligand as a chelating agent are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Towards developing an analytical procedure of defining the equatorial electrojet for correcting satellite magnetic anomaly data

Analysis of the total magnetic intensity MAGSAT data has identified and characterized the variability of ionospheric current effects as reflected in the geomagnetic field as a function of longitude, elevation, and time (daily as well as monthly variations). This analysis verifies previous observations in POGO data and provides important boundary conditions for theoretical studies of ionospheric currents. Furthermore, the observations have led to a procedure to remove these temporal perturbations from lithospheric MAGSAT magnetic anomaly data based on 'along-the-dip-latitude' averages from dawn and dusk data sets grouped according to longitudes, time (months), and elevation. Using this method, high-resolution lithospheric magnetic anomaly maps have been prepared of the earth over a plus or minus 50 deg latitude band. These maps have proven useful in the study of the structures, nature, and processes of the lithosphere.

Ravat, Dhananjay↗
DOE OSTI2023

Dimensionality reduction using elastic measures

With the recent surge in big data analytics for hyperdimensional data, there is a renewed interest in dimensionality reduction techniques. In order for these methods to improve performance gains and understanding of the underlying data, a proper metric needs to be identified. This step is often overlooked, and metrics are typically chosen without consideration of the underlying geometry of the data. Here, in this paper, we present a method for incorporating elastic metrics into the t-distributed stochastic neighbour embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP). We apply our method to functional data, which is uniquely characterized by rotations, parameterization and scale. If these properties are ignored, they can lead to incorrect analysis and poor classification performance. Through our method, we demonstrate improved performance on shape identification tasks for three benchmark data sets (MPEG-7, Car data set and Plane data set of Thankoor), where we achieve 0.77, 0.95 and 1.00 F1 score, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Data-driven distillation and precision prognosis in traumatic brain injury with interpretable machine learning

Traumatic brain injury (TBI) affects how the brain functions in the short and long term. Resulting patient outcomes across physical, cognitive, and psychological domains are complex and often difficult to predict. Major challenges to developing personalized treatment for TBI include distilling large quantities of complex data and increasing the precision with which patient outcome prediction (prognoses) can be rendered. We developed and applied interpretable machine learning methods to TBI patient data. We show that complex data describing TBI patients' intake characteristics and outcome phenotypes can be distilled to smaller sets of clinically interpretable latent factors. We demonstrate that 19 clusters of TBI outcomes can be predicted from intake data, a ~ 6× improvement in precision over clinical standards. Finally, we show that 36% of the outcome variance across patients can be predicted. These results demonstrate the importance of interpretable machine learning applied to deeply characterized patients for data-driven distillation and precision prognosis.

60 APPLIED LIFE SCIENCES↗