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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Effects of grain size and grain boundary on critical current density of high T(sub c) superconducting oxides

By means of adding impurity elements in high T sub c oxides, the effects were studied of grain size and grain boundary on the critical current density of the following systems: YBa2Cu3O(7-y) and Bi-Pr-Sr-Ca-Cu-O. In order to only change the microstructure instead of the superconductivity of the grains in the samples, the impurity elements were added into the systems in terms of the methods like this: (1) substituting Y with the lanthanide except Pr, Ce, and Tb in YBa2Cu3O(7-y) system to finning down grains in the samples, therefore, the effect can be investigated of the grain size on the critical current density of 1:2:3 compounds; (2) mixing the high T sub c oxides with the metal elements, such as Ag, according to the composition of (high T sub c oxide)1-xAgx to metallize the grain boundaries in the samples, studying the effect of the electric conductivity of the grain boundaries on the critical current density; (3) adding SiO2, PbO2, and SnO2 into the high T sub c oxide to form impurity phases in the grain boundaries, trying to find out the effects of the impurity phases or metalloid grain boundaries on the critical current density of the high T sub c superconductors. The experimental results indicate that in the case of of the presence of the metalloid grain boundaries finning down grains fails to enhance the j sub c, but restrains it strongly, the granular high T sub c superconductors with the small size grains coupled weakly is always the low j sub c system.

Zhao, Y.↗
NASA NTRS1993

Estimating snow grain size using AVIRIS data

Estimates of snow grain size for the near-surface snow layer were calculated for the Tioga Pass region and Mammoth Mountain in the Sierra Nevada, California, using an inversion technique and data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The Tioga Pass and Mammoth Mountain single-band AVIRIS radiance images were atmospherically corrected to obtain surface reflectance. A discrete-ordinate model was used to calculate directional reflectance as a function of snowpack grain size for a wide range of snow grain radii. The resulting radius vs. reflectance curves were each fit using a nonlinear least squares technique which provided a means of transforming surface reflectance in each AVIRIS image to optically equivalent grain size on a per-pixel basis. The model results and grain size estimates derived from the AVIRIS data show that, for solar incidence angles between 0 and 30, the technique provides good estimates of grain size. This work provides the first quantitative estimates for grain size using data acquired from an airborne remote sensing instrument and is an important step in improving our ability to retrieve snow physical properties independent of field measurements.

Nolin, Anne W.↗
NASA NTRSDate not supplied

An Electron Backscatter Diffraction (EBSD)-Based Automated Tool for Ceramic Capacitor Grain Size Analysis

Ceramic capacitors continue to be recurring problem parts for NASA, despite best efforts to screen out potential defects and failures through environmental and electrical testing and nondestructive inspection techniques such as acoustic microscopy. The physical properties of ceramic capacitors necessitates thin dielectric layers capable of withstanding significant electric fields. Any defects in those ceramic layers can result in reduced insulation resistance failure modes including short circuit failures, so the quality and consistency of the dielectric material is critical. The size of the individual ceramic grains in the dielectric material is a critical parameter. However, judging “grain size” is not so simple—in a single capacitor there can be wide variation in grain sizes observed. It is theorized that by studying the grain size distributions of “known good” and “known bad” lots of capacitors, some conclusions could be drawn that would allow us to better predict to the reliability of future lots based on grain size distributions. The initial goal of this effort was to find or develop an automated tool that could inspect a capacitor and return grain size distribution results.

Robert Hodson↗
NASA NTRS1974

Grain size and the evolution of lunar soils

Grain-size data are presented for Apollo-17 soils, and the relationship is considered between grain-size distribution and the processes which pulverize the soil, reconstitute it as agglutinates, and replenish it with fresh material. It is shown that a strong inverse correlation exists between mean grain size and standard deviation and that there is a correlation between grain size and agglutinate content whereby the finest samples have the highest agglutinate content. Two evolutionary sequences are described for the soils in which (1) reworking by micrometeorites predominates over mixing with other soils and (2) mixing predominates over reworking. It is shown that the final result of soil evolution may be a steady-state soil where pulverization by micrometeorites is balanced by agglutination and replenishment of coarser grains. A model is presented for such a soil, and it is argued that its grain-size distribution may depend on regolith thickness.-

Mckay, D. S.↗
DOE OSTI2024

Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO

Abstract Streambed grain sizes control river hydro‐biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo‐driven, artificial intelligence (AI)‐enabled, and theory‐based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground‐truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log‐normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy‐Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined.

58 GEOSCIENCES↗
DOE OSTI2024

Updimensioning strategy derived from synthetic equiaxed grain structures for approximating 3D grain size distributions from 2D visualizations with 1D parameters

We generated synthetic equiaxed grain structures using computer graphics software to explore the relationship between various grain size determination methods and true three-dimensional (3D) grain diameters. Mirroring grain measurement techniques, the synthetic 3D grain structures are imaged as 2D micrographs which are measured to yield 1D grain size parameters. Synthetic grain structures provide data at a mass scale and permit exploration of both polished and fractured surface micrographs, revealing one-to-one correspondence between exposed 2D grain cross-sections and individual 3D grains. Analysis of this correspondence yielded a procedure to approximate 3D equiaxed grain size and volume distributions based on the mode of the 2D fractograph grain size distribution. The 3D approximation procedure is shown to be less susceptible to different imaging conditions that affect small, undiscernible grains compared to the standard planimetric and linear intercept methods, which by design also tend to underestimate the 3D grain diameter. The procedure requires larger sample sizes to lower variance and a deeper analysis which could become more practical with machine learning (ML) models for grain boundary segmentation, which synthetic grain structures can help train. This work lays the foundation for analyzing other grain distributions such as columnar and composite grains in similar depth.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1991

Grain size control of rhenium strip

Ensuring the desired grain size in the pure Re strip employed by the SP-100 space nuclear reactor design entails the establishment of an initial grain size in the as-received strip and the avoidance of excessive grain growth during subsequent fabrication. Pure Re tapered tensile specimens have been fabricated and tested in order to quantify the effects of grain-boundary migration. Grain size could be rendered fine and uniform by means of a rolling procedure that uses rather large reductions between short intermediate anneals. The critical strain regime varies inversely with annealing temperature.

Schuster, Gary B.↗
NASA NTRS1978

Grain size and the evolution of Luna 24 soils

The grain size distribution of six Luna 24 samples has been determined. These samples are characterized by a bimodal distribution which is indicative of soils formed primarily by mixing rather than by reworking. Although agglutinate content decreases with depth, it is not likely that the Luna 24 soils have undergone appreciable in situ reworking. Particle types and abundances in each of four size fractions have been determined petrographically. Mineral fragments are very abundant in all analyzed size fractions. Pyroxene and plagioclase increase slightly in abundance at finer grain sizes, but olivine decreases significantly. Compared with typical mare soils, the Luna 24 trends are anomalous. They are compatible with the hypothesis than many, if not most, of the mineral grains in the 20-250-micron fractions come from coarse-grain rocks having average mineral grain sizes greater than 250 microns. The mineralogy and chemistry of the coarse-grained rocks has not been well characterized, but there is evidence that at least some of them are higher in MgO than the analyzed finer-grained basalts.

Mckay, D. S.↗
NASA NTRS1994

Estimation of grain sizes and mixing ratios of fine powder mixtures of common geologic minerals

Two different approaches for modeling reflectance spectra of intimate mixtures, Hapke's model and the isograin model, are used to estimate grain sizes and mixing ratios of powder mixtures of three geologic minerals: olivine, orthopyroxene, and plagioclase. In Hapke's model, scattering and extinction effiencies are mixed separately, and both models employ semiempirical refractive index spectra for component minerals. Mixing ratios of mixtures of grain size 45-75 micrometers are well estimated by both models assuming a common grain size of 60 micrometers and optimizing the constants for the single-particle scattering. For each model, effective grain size ratios for mineral constituents in mixtures of grain size less than 25 micrometers, are derived successfully that allows mineral abundances to be accurately predicted within approximately 4 wt percent. On the other hand, neither model can accurately predict mineral reflectance spectra for its smaller grain sizes less than 25 and 25-45 micrometers using an absorption coefficient spectrum derived from a larger grain size (45-75 micrometers). The errors in both models are significantly reduced if surface roughness effects of the smaller grain-size fractions are modeled.

Hiroi, Takahiro↗
NASA NTRS1977

Surface finish effects and the strength-grain size relation in SiC

The effect of surface finish on the strength-grain size relation was investigated for dense hot-pressed SiC. Failure initiated predominantly via the propagation of extrinsic machining-induced flaws for the range of grain sizes and machining grit sizes studied. These results are consistent with the region of large-grain-size flaw control as delineated by Prochazka and Charles. The severity of machining-induced flaws, relative to the machining grit size, decreased with increasing machining grit size and decreasing SiC grain size.

Cranmer, D. C.↗
NASA NTRS1983

A brittle to ductile transition in NiAl of a critical grain size

Tensile tests have been carried out on the strongly ordered B2 aluminide NiAl at 400 C to investigate the effect of the grain size on the ductility of the material. It is found that the ductility is very low and essentially independent of the grain size for aggregates of grains larger than about 20 microns; for finer-grained aggregates, the ductility increases sharply with decreasing grain size. Thus, NiAl exhibits a critical grain size below which polycrystalline aggregates are ductile in tension. For all grain sizes, fracture occurs in a brittle manner through a combination of intergranular decohesion and transgranular cleavage.

Schulson, E. M.↗
DOE OSTI2025

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

The effects of grain size on the flow and fracture of long-range ordered alloys

The effects of grain size on the mechanical properties of long-range ordered alloys are examined with reference to the short-term behavior of aluminide intermetallics. It is shown that in those L1(2) alloys which exhibit anomalous thermal strengthening, the grain size affects the magnitude of the strengthening. In some cases it also affects ductility, whereby the tensile elongation and the tensile strength increase as the grain size decreases below a critical point. It is also believed that grain size may affect the partitioning of microalloying elements, such as boron, in Ni3Al.

Schulson, E. M.↗
NASA NTRS1996

Subpixel Snow-Covered-Area and Snow Grain Size From Mixture Analysis with AVIRIS Data

Snow-covered-area (SCA) and snow grain size are crucial inputs to hydrologic and climatologic modeling of alpine and other seasonally snow-covered regions. SCA is necessary to parameterize energy budget calculations in climate models, to determine in which regions point snowmelt models are to be run for distributed snowmelt modeling efforts and to provide a basis from which estimates of snow water equivalent (SWE) may be made. Snow grain size, SWE and snow impurities determine the spectral albedo of snow, which controls the net solar flux at the snowpack surface. Snow albedo is of the utmost importance in snowmelt modeling, yet the difficulty with which grain size, SWE, and impurities are mapped has left the spatial distribution of snow albedo in alpine catchments poorly understood. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been used to estimate sub-pixel snow-covered-area and snow grain size independently. In this paper we present a technique which improves estimates of both snow parameters by treating their mapping simultaneously.

Green Robert O.↗
DOE OSTI2025

Grain size effects on slip band development

Crystallographic slip localizations, known as slip bands, concentrate stress in polycrystals, often leading to the nucleation of damage. Slip band development has been experimentally shown to be sensitive to grain size, tending to develop more frequently and with a greater intensity in large grains. In this work, we investigate the influence of grain size on the propensity for crystallographic slip band development. To this end, we employ the slip band-fast Fourier transform method (SB-FFT). SB-FFT is a 3D, full-field crystal plasticity model that permits the incremental development of discrete crystallographic slip bands according to microstructure and material properties. We present a model Inconel 718 tricrystal to isolate the effect of grain size. Our findings show that slip bands in large grains develop at lower applied strain levels and at a faster rate than slip bands in small grains. The grain size effect is due to a backstress produced by the interaction of the slip band and its neighboring grain. The backstress is most intense at small grain sizes, impeding slip activity within a developing slip band and immediately surrounding the slip band.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Impact of mixed grain size sediment input on braided river Morphodynamics: Insights from experimental and numerical modeling

The rate of sediment supply has significant impacts on river morphology, making it crucial to understand the geomorphic changes and grain size distribution dynamics in rivers. However, the effects of varying grain size sediment input on morphological changes in braided channels remain poorly understood. This study is the first to investigate the bar development and sediment sorting processes in braided channels with non-uniform sediment inputs using both numerical and experimental approaches. We applied a two-dimensional numerical model, Nays2DH to confirm and generalize experimental results. The model reproduced key experiment results, including 1) stream elevation changes, and 2) grain size distribution. Using this validated model, we explored the morphological changes and sorting process in a braided river with sediment inputs. The numerical experiments demonstrate that sediment input controls the elevation of the stream bed and the grain size distribution. Notably, both the elevation and grain-size distribution become relatively stable in downstream of the channel. Additionally, the simulation results suggest that an increased sediment supply leads to greater channel complexity, with bed surface armoring decreasing.

Nays2DH↗