Data from Explorer 17 on composition of the upper atmosphere
Explorer XVII data on neutral particle concentrations in upper atmosphere
ATMOSPHERIC COMPOSITION↗
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.
Martha's Vineyard and selected Georgia tektites - New chemical data
Chemical composition and ages of high silica Georgia and Marthas Vineyard tektites
TEKTITE↗
Precision measurements of solar energetic particle elemental composition
Using data from the Cosmic Ray Subsystem (CRS) aboard the Voyager 1 and 2 spacecraft, solar energetic particle abundances or upper limits for all elements with 3 = Z = 30 from a combined set of 10 solar flares during the 1977 to 1982 time period were determined. Statistically meaningful abundances have been determined for the first time for several rare elements including P, Cl, K, Ti and Mn, while the precision of the mean abundances for the more abundant elements has been improved by typically a factor of approximately 3 over previously reported values.
Breneman, H.↗
Ultrasonic Characterization of Flaws in Composites Using Plate Waves Dispersion Data
Leaky Lamb wave (LLW) propagation in composite materials has been studied extensively since it was first observed in 1982. The wave is induced using a pitch-catch arrangement and the plate wave modes are detected by searching minima in the reflected spectra.
Composites Leaky Lamb wave composite materials↗
NSSDC Data Listing
Data available from the National Space Science Data Center (NSSDC) are listed. The spacecraft, principal investigator, the experiment, and time span of the data are given. A listing is also included of ground-based data, models, computer routines and composite spacecraft data that are available from NSSDC.
Source record↗
National Space Science Data Center (NSSDC) Data Listing
Satellite and nonsatellite data available from the National Space Science Data Center are listed. The Satellite Data listing includes the spacecraft name, launch date, and an alphabetical list of experiments. The Non-Satellite Data listing contains ground based data, models, computer routines, and composite spacecraft data. The data set name, data form code, quantity of data, and the time space covered are included in the data sets of both listings where appropriate. Geodetic tracking data sets are also included.
Source record↗
NSSDC Data listing
A convenient reference to space science and supportive data available from the National Space Science Data Center (NSSDC) is provided. Satellite data are organized by NSSDC spacecraft common name. The launch date and NSSDC ID are given. Experiments are listed alphabetically by the principal investigator or team leader. The experiment name and NSSDC ID, data set ID, data set name, data form code, quantity of data, and the time span of the data as verified by NSSDC are shown. Ground-based data, models, computer routines, and composite spacecraft data that are available from NSSDC are listed alphabetically by discipline, source, data type, data content, and data set. The data set name, data form code, quantity of data, and the time span covered where appropriate are included.
Source record↗
Review of alternative fuels data bases
Based on an analysis of the interaction of fuel physical and chemical properties with combustion characteristics and indicators, a ranking of the importance of various fuel properties with respect to the combustion process was established. This ranking was used to define a suite of specific experiments whose objective is the development of an alternative fuels design data base. Combustion characteristics and indicators examined include droplet and spray formation, droplet vaporization and burning, ignition and flame stabilization, flame temperature, laminar flame speed, combustion completion, soot emissions, NOx and SOx emissions, and the fuels' thermal and oxidative stability and fouling and corrosion characteristics. Key fuel property data is found to include composition, thermochemical data, chemical kinetic rate information, and certain physical properties.
Harsha, P. T.↗
Origin of the Moon: In search of the holy grail
The Moon's origin could be deduced with certainty if its bulk chemistry were known. However, determination of this chemistry is difficult because of the profound and complex redistribution of elements that occurred in the outer portions of the Moon during crystallization of the magma ocean. The compositions of 23 varieties of volcanic glass, erupted from depths approaching 300 miles, were used to predict the chemistry of a special glass (genesis glass) having a direct link to primordial lunar matter. A sample of glass with the predicted composition was discovered. This allows a new estimate to be made of the Moon's bulk composition. The data indicate that the Moon shares some intriquing chemical similarities with the Earth's mantle. Both genesis glass and lunar gas are furnishing definitive data on the Moon's composition and origin.
Delano, J. W.↗
Genesis Solar Wind Interstream, Coronal Hole and Coronal Mass Ejection Samples: Update on Availability and Condition
Recent refinement of analysis of ACE/SWICS data (Advanced Composition Explorer/Solar Wind Ion Composition Spectrometer) and of onboard data for Genesis Discovery Mission of 3 regimes of solar wind at Earth-Sun L1 make it an appropriate time to update the availability and condition of Genesis samples specifically collected in these three regimes and currently curated at Johnson Space Center. ACE/SWICS spacecraft data indicate that solar wind flow types emanating from the interstream regions, from coronal holes and from coronal mass ejections are elementally and isotopically fractionated in different ways from the solar photosphere, and that correction of solar wind values to photosphere values is non-trivial. Returned Genesis solar wind samples captured very different kinds of information about these three regimes than spacecraft data. Samples were collected from 11/30/2001 to 4/1/2004 on the declining phase of solar cycle 23. Meshik, et al is an example of precision attainable. Earlier high precision laboratory analyses of noble gases collected in the interstream, coronal hole and coronal mass ejection regimes speak to degree of fractionation in solar wind formation and models that laboratory data support. The current availability and condition of samples captured on collector plates during interstream slow solar wind, coronal hole high speed solar wind and coronal mass ejections are de-scribed here for potential users of these samples.
Allton, J. H.↗
Dynamic mechanical analysis and organization/storage of data for polymetric materials
Dynamic mechanical analysis was performed on a variety of temperature resistant polymers and composite resin matrices. Data on glass transition temperatures and degree of cure attained were derived. In addition a laboratory based computer system was installed and data base set up to allow entry of composite data. The laboratory CPU termed TYCHO is based on a DEC PDP 11/44 CPU with a Datatrieve relational data base. The function of TYCHO is integration of chemical laboratory analytical instrumentation and storage of chemical structures for modeling of new polymeric structures and compounds
Rosenberg, M.↗
Comparison between the recent U.S. composite magnetic anomaly map and Magsat anomaly data
The present investigation is concerned with a comparison of Magsat data with a Composite Magnetic Anomaly Map (CMAM) of the conterminous U.S. reported by Zietz (1982). The investigation was initiated to test the validity of the satellite measurements, and to provide insights into error or problems in either data set. It is found that upward continuation of the digital CMAM data is not in qualitative agreement with the Magsat map. However, if a least squares fit polynomial surface is taken out prior to upward continuation, there is improved quantitative agreement between a residual CMAM and Magsat. Causes for the remaining differences between the residual, upward continued CMAM and the Magsat map are also considered.
Schnetzler, C. C.↗
Composite Bond Line Measurements Based on a Bayesian Analysis of Flash Thermography Data
For bonded composite materials, an accurate characterization of the adhesive bond line is needed to predict failure modes and fracture toughness. In this paper, bond line thickness was estimated from data obtained using through transmission flash thermography. The forward model that predicts back surface temperature is based on a three layer heat diffusion equation with varying diffusivity and flux boundary conditions. The corresponding inverse problem of estimating bond line thickness from measurement data was solved using a Bayesian approach that assumed Gaussian priors for the bond line thickness and thermal diffusivity of the adherends. Finally, the outputs of the thermography based method were compared to measurements that were collected using a micrometer and ultrasound testing.
Flash thermography↗
Composite Bond Line Measurements Based on A Bayesian Analysis of Flash Thermography Data
For bonded composite materials, an accurate characterization of the adhesive bond line is needed to predict failure modes and fracture toughness. In this paper, bond line thickness was estimated from data obtained using through transmission flash thermography. The forward model that predicts back surface temperature is based on a three layer heat diffusion equation with varying diffusivity and flux boundary conditions. The corresponding inverse problem of estimating bond line thickness from measurement data was solved using a Bayesian approach that assumed Gaussian priors for the bond line thickness and thermal diffusivity of the adherends. Finally, the outputs of the thermography based method were compared to measurements that were collected using a micrometer and ultrasound testing.
Flash thermography↗
A SUBALGOL program for calculation of molecular compositional formulas from mass spectral data Interim report
IBM 7090 computer program for calculation of molecular composition formulas from mass spectrometer data
MASS SPECTROMETRY↗
Thermal expansion properties of composite materials
Thermal expansion data for several composite materials, including generic epoxy resins, various graphite, boron, and glass fibers, and unidirectional and woven fabric composites in an epoxy matrix, were compiled. A discussion of the design, material, environmental, and fabrication properties affecting thermal expansion behavior is presented. Test methods and their accuracy are discussed. Analytical approaches to predict laminate coefficients of thermal expansion (CTE) based on lamination theory and micromechanics are also included. A discussion is included of methods of tuning a laminate to obtain a near-zero CTE for space applications.
Johnson, R. R.↗
Constructing the "Best" Reliability Data for the Job
Modern business and technical decisions are based on the results of analyses. When considering assessments using "reliability data", the concern is how long a system will continue to operate as designed. Generally, the results are only as good as the data used. Ideally, a large set of pass/fail tests or observations to estimate the probability of failure of the item under test would produce the best data. However, this is a costly endeavor if used for every analysis and design. Developing specific data is costly and time consuming. Instead, analysts rely on available data to assess reliability. Finding data relevant to the specific use and environment for any project is difficult, if not impossible. Instead, we attempt to develop the "best" or composite analog data to support our assessments. One method used incorporates processes for reviewing existing data sources and identifying the available information based on similar equipment, then using that generic data to derive an analog composite. Dissimilarities in equipment descriptions, environment of intended use, quality and even failure modes impact the "best" data incorporated in an analog composite. Once developed, this composite analog data provides a "better" representation of the reliability of the equipment or component can be used to support early risk or reliability trade studies, or analytical models to establish the predicted reliability data points. Data that is more representative of reality and more project specific would provide more accurate analysis, and hopefully a better final decision.
DeMott, D. L.↗
Constructing the Best Reliability Data for the Job
Modern business and technical decisions are based on the results of analyses. When considering assessments using "reliability data", the concern is how long a system will continue to operate as designed. Generally, the results are only as good as the data used. Ideally, a large set of pass/fail tests or observations to estimate the probability of failure of the item under test would produce the best data. However, this is a costly endeavor if used for every analysis and design. Developing specific data is costly and time consuming. Instead, analysts rely on available data to assess reliability. Finding data relevant to the specific use and environment for any project is difficult, if not impossible. Instead, we attempt to develop the "best" or composite analog data to support our assessments. One method used incorporates processes for reviewing existing data sources and identifying the available information based on similar equipment, then using that generic data to derive an analog composite. Dissimilarities in equipment descriptions, environment of intended use, quality and even failure modes impact the "best" data incorporated in an analog composite. Once developed, this composite analog data provides a "better" representation of the reliability of the equipment or component can be used to support early risk or reliability trade studies, or analytical models to establish the predicted reliability data points. Data that is more representative of reality and more project specific would provide more accurate analysis, and hopefully a better final decision.
Kleinhammer, R. K.↗