Composition and assembly of a spectral data base for corn and soybean multicrop segments
There are no author-identified significant results in this report.
Trenchard, M. H.↗
SEARCH · Search NASA
Results for “compositional data”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Chemical mixing model studies of lunar orbital geochemical data: Apollo 16 and 17 highlands compositions
Explore the source record for details and available documents.
Spudis, P. D.↗
The EET87513 clast N: A CM2 fragment in an HED polymict breccia
Xenoliths of material resembling carbonaceous chondrites have been found in several HED polymict breccias. Most workers concluded that these clasts are related to CM2 meteorites on the basis of texture, bulk composition, and mineralogy. Data on clast N, a carbonaceous chondrite fragment from the howardite EET87513 large enough (approximately 4x5mm on the surface of the slab from which it was separated) to extract bulk samples for INAA and oxygen isotope analysis and to provide a thin section for electron microprobe, SEM, and TEM analysis is reported. Preliminary data for this clast were previously reported. INAA was performed at Oregon State University and bulk oxygen isotopic composition was determined at the University of Chicago. These data confirm that EET87513 clast N is a fragment of CM2 material.
Buchanan, P. C.↗
Neutron diffraction measurements and modeling of residual strains in metal matrix composites
Neutron diffraction measurements at room temperature are used to characterize the residual strains in tungsten fiber-reinforced copper matrix, tungsten fiber-reinforced Kanthal matrix, and diamond particulate-reinforced copper matrix composites. Results of finite element modeling are compared with the neutron diffraction data. In tungsten/Kanthal composites, the fibers are in compression, the matrix is in tension, and the thermal residual strains are a strong function of the volume fraction of fibers. In copper matrix composites, the matrix is in tension and the stresses are independent of the volume fraction of tungsten fibers or diamond particles and the assumed stress free temperature because of the low yield strength of the matrix phase.
Saigal, A.↗
Mechanical Behavior and Analytical Modeling of Melt-Infiltrated SiC/SiC Woven Composite
The desirable properties in ceramic matrix composites (CMCs), such as high temperature strength, corrosion resistance, high toughness, low density, or good creep resistance have led to increased use of CMCs in high-speed engine structural components and structures that operate in extreme temperature and hostile aero-thermo-chemical environments. Ceramic matrix composites have been chosen for turbine material in the design of 21st century civil propulsion systems to achieve high fuel economy, improved reliability, extended life, and reduced cost. Most commercial CMCs are manufactured using a chemical vapor infiltration (CVI) process. However, a lower cost fabrication known as melt-infiltration process is also providing CMCs marked for use in hot sections of high-speed civil transports. Limited samples of a SiC/SiC melt-infiltrated woven composites are being investigated at room and elevated temperature below and above matrix cracking. These samples show graceful failure and toughness at room temperature with a reduction in strength and modulus at elevated temperatures. A generic finite element model is also being developed to predict monotonic and cyclic loading behavior of the woven composite. Use of the initial test data from the woven composite is being used for the development of the analytical model. This model is the first of a iterative process leading towards the development the model's capability to predict behavior at room and elevated temperature for monotonic and cyclic loading. The purpose of this paper is to report on the material and mechanical findings of the SiC/SiC melt-infiltrated woven composite and progress on the development of the finite element model.
Lang, J.↗
Neural Network Prediction of Failure of Damaged Composite Pressure Vessels from Strain Field Data Acquired by a Computer Vision Method
This effort used a new and novel method of acquiring strains called Sub-pixel Digital Video Image Correlation (SDVIC) on impact damaged Kevlar/epoxy filament wound pressure vessels during a proof test. To predict the burst pressure, the hoop strain field distribution around the impact location from three vessels was used to train a neural network. The network was then tested on additional pressure vessels. Several variations on the network were tried. The best results were obtained using a single hidden layer. SDVIC is a fill-field non-contact computer vision technique which provides in-plane deformation and strain data over a load differential. This method was used to determine hoop and axial displacements, hoop and axial linear strains, the in-plane shear strains and rotations in the regions surrounding impact sites in filament wound pressure vessels (FWPV) during proof loading by internal pressurization. The relationship between these deformation measurement values and the remaining life of the pressure vessels, however, requires a complex theoretical model or numerical simulation. Both of these techniques are time consuming and complicated. Previous results using neural network methods had been successful in predicting the burst pressure for graphite/epoxy pressure vessels based upon acoustic emission (AE) measurements in similar tests. The neural network associates the character of the AE amplitude distribution, which depends upon the extent of impact damage, with the burst pressure. Similarly, higher amounts of impact damage are theorized to cause a higher amount of strain concentration in the damage effected zone at a given pressure and result in lower burst pressures. This relationship suggests that a neural network might be able to find an empirical relationship between the SDVIC strain field data and the burst pressure, analogous to the AE method, with greater speed and simplicity than theoretical or finite element modeling. The process of testing SDVIC neural network analysis and some encouraging preliminary results are presented in this paper. Details are given concerning the processing of SDVIC output data such that it may be used as back propagation neural network (BPNN) input data. The software written to perform this processing and the BPNN algorithm are also discussed. It will be shown that, with limited training, test results indicate an average error in burst pressure prediction of approximately six percent,
Russell, Samuel S.↗
Sea Ice Motion from Wavelet Analysis of Satellite Data
Wavelet analysis of NASA scatterometer (NSCAT) backscatter and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) radiance data can be used to obtain daily sea ice drift information for the Arctic region. This technique provides improved spatial coverage over the existing array of Arctic Ocean buoys and better temporal resolution over techniques utilizing data from satellite synthetic aperture radars. Comparisons with ice motion derived from ocean buoys give good quantitative agreement. Both comparison results from NSCAT and SSM/I are compatible, and the results from NSCAT can definitely complement that from SSM/I when there are cloud or surface effects. Then three sea-ice drift daily results from NSCAT, SSM/I, and buoy data can be merged as a composite map by some data fusion techniques. The ice flow streamlines are highly correlated with surface air pressure contours. Examples of derived ice-drift maps in December 1996 illustrate large-scale circulation reversals over a period of four days. A method for deriving divergence and shear at the large-scale has been developed and comparison between buoys and satellite results shows a good agreement. These calibrated/validated results indicate that NSCAT, SSM/I merged daily ice motion are suitably accurate to identify and closely locate sea ice processes, and to improve our current knowledge of sea ice drift and related processes through the data assimilation of ocean-ice numerical model. For demonstration purpose, the ice velocities derived from satellite data are compared with the ice velocities derived from a coupled ice-ocean interaction model. The comparison reveals that the general circulation patterns of the two are quite similar but the ice velocity differences between the two are quite significant. In order to quantify the wind effects on ice motion, empirical orthogonal functions (EOF) are used in the principal component analysis for both ice motion and pressure field. Some preliminary results of sea-ice motion from QuikScat will also be presented.
Liu, Antony K.↗
Data Driven Optimization of BN Polymer Composites Using Automated Experimentation and Machine Learning
Explore the source record for details and available documents.
machine learning↗
OGO-6 neutral atmospheric composition experiment
The continued analysis of data obtained from the neutral atmospheric composition experiment flown on OGO-V6 is discussed. The effort was directed toward the study of five specific areas of interest for which the OGO-V6 data were especially useful.
Taeusch, D. R.↗
Composition and energy spectra of solar particles
Modern and ancient energetic particles emitted in solar flares are examined. Data cover particle composition and energy spectra.
Price, P. B.↗
Automotive applications for advanced composite materials
A description is presented of nonaerospace applications for advanced composite materials with special emphasis on the automotive applications. The automotive industry has to satisfy exacting requirements to reduce the average fuel consumption of cars. A feasible approach to accomplish this involves the development of composites cars with a total weight of 2400 pounds and a fuel consumption of 33 miles per gallon. In connection with this possibility, the automotive companies have started to look seriously at composite materials. The aerospace industry has over the past decade accumulated a considerable data base on composite materials and this is being made available to the nonaerospace sector. However, the automotive companies will place prime emphasis on low cost resins which lend themselves to rapid fabrication techniques.
Deutsch, G. C.↗
Ultrasonic Attenuation Results of Thermoplastic Resin Composites Undergoing Thermal and Fatigue Loading
As part of an effort to obtain the required information about new composites for aviation use, materials and NDE researchers at NASA are jointly performing mechanical and NDE measurements on new composite materials. The materials testing laboratory at NASA is equipped with environmental chambers mounted on load frames that can expose composite materials to thermal and loading cycles representative of flight protocols. Applying both temperature and load simultaneously will help to highlight temperature and load interactions during the aging of these composite materials. This report highlights our initial ultrasonic attenuation results from thermoplastic composite samples that have undergone over 4000 flight cycles to date. Ultrasonic attenuation measurements are a standard method used to assess the effects of material degradation. Recently, researchers have shown that they could obtain adequate contrast in the evaluation of thermal degradation in thermoplastic composites by using frequencies of ultrasound on the order of 24 MHz. In this study, we address the relationship of attenuation measured at lower frequencies in thermoplastic composites undergoing both thermal and mechanical loading. We also compare these thermoplastic results with some data from thermoset composites undergoing similar protocols. The composite s attenuation is reported as the slope of attenuation with respect to frequency, defined as b = Da(f)/Df. The slope of attenuation is an attractive parameter since it is quantitative, yet does not require interface corrections like conventional quantitative attenuation measurements. This latter feature is a consequence of the assumption that interface correction terms are frequency independent. Uncertainty in those correction terms can compromise the value of conventional quantitative attenuation data. Furthermore, the slope of the attenuation more directly utilizes the bandwidth information and in addition, the bandwidth can be adjusted in the post processing stage to compensate for the loss of dynamic range of the signal as the composites age.
Madaras, Eric I.↗
The composition of Galactic cosmic rays and solar energetic particles
The progress made by U.S. researchers during 1983-1986 in studies on the composition of the Galactic cosmic-ray source (GCRS) and solar energetic particles (SEP) is reviewed. New information concerning element abundances in GCRS (obtained from HEAO-3 data) and SEP composition in large flares and (He-3)-rich events (from data obtained by the Voyager and ISEE spacecraft) was used to obtain direct correlation between the GCRS and SEP compositions. For elements heavier than He, the linear correlation coefficient beween the points was 0.96, and the slope of the least-squares fit line was found to be 1.01 + or - 0.01. Hydrogen and helium are more abundant in the SEP than in the GCRS. The close resemblance between the SEP composition and the GCRS composition means that the ratio of SEP abundances to solar-system abundances shows a correlation with the first ionization potential.
Mason, G. M.↗
Multispectral combination and display of ERTS-1 data
Standard NASA color composites combine the most relevant 3 bands from the 4 MSS bands available. An alternate approach is to extract the principal components of the data by a linear transformation of the 4 bands. This approach leads to a low dimensionality representation of ERTS-1 data with the least degradation, in the mean square sense, of the radiometric accuracy. The technique has been applied with success to ERTS-1 MSS data for several geographic areas in California. For all examples considered the mean square representation error is less than one percent. By combining this dimensionality reduction which our previous results on image enhancement for visual display, color composites are obtained which contain and display most of the information provided by the ERTS-1 sensors.
Algazi, V. R.↗
Transferable predictions of energetic and structural properties for refractory solid solution alloys across chemical compositions
We present a data-efficient approach to train graph neural networks (GNNs) on density functional theory (DFT) data for accurate and transferable predictions of energetic and structural properties of refractory solid solution alloys in the niobium-tantalum-vanadium (Nb-Ta-V) chemical space. We start by training the GNN model only on DFT data that describes refractory binary alloys niobium-tantalum (Nb-Ta), niobium-vanadium (Nb-V), and tantalum-vanadium (Ta-V) to predict formation enthalpy and root mean squared displacement. Once trained, the GNN predictions are tested on DFT data describing refractory ternary alloys Nb-Ta-V. While, unsurprisingly, direct transferability from binary to ternary is not sufficiently accurate, augmenting the training with only 1% of the available ternary data (uniformly distributed across the entire range of chemical compositions) improves significantly the quality of the GNN predictions. For comparison, we assess the transferability in the opposite direction by training GNN models on ternary Nb-Ta-V data and making predictions on binaries Nb-Ta, Nb-V, and Ta-V, which exhibits notably higher predictive errors. The proposed methodology, which favors transferability from lower-component to higher-component alloys, offers an efficient path towards avoiding the curse of dimensionality incurred when collecting DFT data for discovery and design of multi-component disordered alloys.
Density functional theory calculations↗
Improving commercial truck fleet composition in emission modeling using 2021 US VIUS data
Commercial trucks are essential elements of the nation's supply chain system. Meanwhile, intensive truck movements contribute significantly to system externalities, such as energy use and air pollution. However, collecting detailed fleet composition and distribution of operational patterns remains a barrier to accurately accounting for these impacts. The recently released 2021 US Vehicle Inventory and Use Survey (US VIUS) fills a critical gap in understanding commercial truck fleet distributions, their operations, and business constraints at the national scale. This study aims to understand the latest US commercial vehicle fleet composition and operational characteristics using 2021 US VIUS data and calibrate the fleet inputs in regulatory emission models to assess the potential emission implications of the VIUS-derived fleet composition. The emission rates for commercial trucks and default fleet composition are collected from the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES4). The 2021 US VIUS data is applied to improve fleet characteristics such as the long-haul fraction and the vehicle mileage accumulation rate. The study also investigates potential emission reduction benefits under various forecasted fleet electrification scenarios. The energy consumption and critical air pollutant rates by vehicle types are compared between MOVES4 and US VIUS fleets for both current and future scenarios to provide insights into the latest U.S. commercial vehicle fleet characteristics and their implications on energy and emissions. This study helps policymakers and practitioners advance the commercial fleet generation for emission models. It also deepens the understanding of the emission reduction potential of the commercial fleet under various fleet projections.
2021 US VIUS↗
BSEC Air Quality: Stationary Aerosol Composition and Mass Concentration at Baltimore
Data is 10-min average mass composition and mass concentration from the TOF-ACSM-X and Aethalometer AE33. TOF-ACSM-X reports fine (less than 2.5 um diameter) non-refractory aerosol, including organic aerosol, sulfate, nitrate, ammonium, and non-refractory chloride. Aethalometer measured the attenuation at different wavelengths for aerosol collected onto tape; one wavelength is used to convert to black carbon mass concentration. Also reported is the elemental ratios determined for organic aerosol (O/C, H/C, and organic matter to organic carbon ratio, OM/OC).
aerosol↗
BSEC Air Quality: Stationary Aerosol Composition and Mass Concentration at Baltimore
Data is 10-min average mass composition and mass concentration from the TOF-ACSM-X. TOF-ACSM-X reports fine (less than 2.5 um diameter) non-refractory aerosol, including organic aerosol, sulfate, nitrate, ammonium, and non-refractory chloride. Also reported is the elemental ratios determined for organic aerosol (O/C, H/C, and organic matter to organic carbon ratio, OM/OC). Finally, ion ratios of key ions used for identifying sources, ammonium balance, and fractional contribution of organic nitrate aerosol to total aerosol nitrate has been included.
aerosol↗