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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

EUV flux variations with solar rotation observed during 1974-1976 from AE satellites C, D, and E

Solar EUV fluxes in the spectral range from 140 to 1850 A have been observed by spectrophotometers on the satellites AE-C, D, and E. Variations over the long period of one or two years cannot be verified quantitatively, as the observed small variations are of the same magnitude as possible variations of instrumental sensitivities and estimated uncertainties of absolute values from the rocket experiment which established the calibration of the AE-C instrument. Fortunately, no similar difficulty exists for the interpretation of observed EUV variations within smaller time periods up to that of a full solar rotation. Results from AE-C observations for many different wavelength groups for the year 1974 are shown by some detail and compared with some recent observations made by the AE-D and AE-E instruments.

Hinteregger, H. E.↗
NASA NTRS1983

Acoustic emission characterization using AE (parameter) delay

The acoustic emission (AE) parameter delay concept is defined as that particular measured value of a parameter at which a specified baseline level of cumulative AE activity is reached. The parameter can be from any of a broad range of elastic, plastic, viscoelastic, and fracture mechanics parameters, as well as their combinations. Such parameters include stress, load, strain, displacement, time, temperature, loading cycle, unloading stress, stress intensity factor, strain energy release rate, and crack tip plasticity zone size, while the AE activity may be AE event counts, ringdown counts, energy, event duration, etc., as well as their combinations. Attention is given to examples for the AE parameter delay concept, together with various correlations.

Williams, J. H., Jr.↗
NASA NTRS1991

The AE-8 trapped electron model environment

The machine sensible version of the AE-8 electron model environment was completed in December 1983. It has been sent to users on the model environment distribution list and is made available to new users by the National Space Science Data Center (NSSDC). AE-8 is the last in a series of terrestrial trapped radiation models that includes eight proton and eight electron versions. With the exception of AE-8, all these models were documented in formal reports as well as being available in a machine sensible form. The purpose of this report is to complete the documentation, finally, for AE-8 so that users can understand its construction and see the comparison of the model with the new data used, as well as with the AE-4 model.

Vette, James I.↗
NASA NTRS1996

Advanced AE Techniques in Composite Materials Research

Advanced, waveform based acoustic emission (AE) techniques have been successfully used to evaluate damage mechanisms in laboratory testing of composite coupons. An example is presented in which the initiation of transverse matrix cracking was monitored. In these tests, broad band, high fidelity acoustic sensors were used to detect signals which were then digitized and stored for analysis. Analysis techniques were based on plate mode wave propagation characteristics. This approach, more recently referred to as Modal AE, provides an enhanced capability to discriminate and eliminate noise signals from those generated by damage mechanisms. This technique also allows much more precise source location than conventional, threshold crossing arrival time determination techniques. To apply Modal AE concepts to the interpretation of AE on larger composite specimens or structures, the effects of modal wave propagation over larger distances and through structural complexities must be well characterized and understood. To demonstrate these effects, measurements of the far field, peak amplitude attenuation of the extensional and flexural plate mode components of broad band simulated AE signals in large composite panels are discussed. These measurements demonstrated that the flexural mode attenuation is dominated by dispersion effects. Thus, it is significantly affected by the thickness of the composite plate. Furthermore, the flexural mode attenuation can be significantly larger than that of the extensional mode even though its peak amplitude consists of much lower frequency components.

Prosser, William H.↗
NASA NTRS1997

TURBO-AE: An Aeroelastic Code for Propulsion Applications

NASA's Advanced Subsonic Technology (AST) program is developing new technologies to increase the fuel efficiency of commercial aircraft engines, improve the safety of engine operation, and reduce engine emissions and noise. With the development of new designs for ducted fans, compressors, and turbines to achieve these goals, a basic aeroelastic requirement is that there should be no flutter or high resonant blade stresses in the operating regime. To verify the aeroelastic soundness of these designs, we need an accurate prediction and analysis code. Such a two-dimensional viscous propulsion aeroelastic code, named TURBO-AE, is being developed at the NASA Lewis Research Center. The TURBO-AE aeroelastic code is based on a three-dimensional unsteady aerodynamic Euler/Navier-Stokes turbomachinery code TURBO, developed under a grant from NASA Lewis. TURBO-AE can model viscous flow effects that play an important role in certain aeroelastic problems, such as flutter with flow separation (or stall flutter) and flutter in the presence of shock and boundary-layer interaction. The structural dynamics representation of the blade in the TURBO-AE code is based on a normal mode representation. A finite element analysis code, such as NASTRAN, is used to calculate in-vacuum vibration modes and the associated natural frequency. A work-per-cycle approach is used to determine aeroelastic (flutter) stability. With this approach, the motion of the blade is prescribed to be a harmonic vibration in a specified in vacuum normal mode. The aerodynamic forces acting on the vibrating blade and the work done by these forces on the vibrating blade during a cycle of vibration are calculated. If positive work is being done on the blade by the aerodynamic forces, the blade is dynamically unstable, since it will extract energy from the flow, leading to an increase in the amplitude of the blade's oscillation. Initial calculations have been done for a configuration representative of the Energy Efficient Engine fan rotor. The accompanying figure shows the work-per-cycle after each cycle of vibration. It can be seen that the work-per-cycle does not vary much after the fourth cycle. The negative sign of the converged work-per-cycle shows that the fan blade is dynamically stable and will not flutter. TURBO-AE will provide a useful aeroelastic prediction/analysis capability for engine manufacturers. It will reduce design cycle times by allowing new blade designs to be verified for aeroelastic soundness before blades are built and tested. With this prediction capability, it will be possible to build thinner, lighter, and faster rotating blades without encountering aeroelastic problems like stall flutter and high-cycle fatigue due to forced vibrations.

Bakhle, Milind A.↗
NASA NTRS1979

The prediction of AE, ap, and Dst at time lags between 0 and 30 hours

The magnetic activity indexes AE, ap, and Dst are correlated with approximately 35,000 hours of interplanetary plasma and magnetic field measurements acquired near the Earth (assembled by NASA/NSSDC into a composite data sat). Lag times between the indexes and solar wind parameters ranged from 0 to 30 hours. Correlations at lags less than 6 hours yield results in agreement with previous studies. At greater lags, the correlation coefficients between the solar wind parameters and AE and ap approach these parameters' autocorrelation (persistence) values. For Dst the correlation with solar wind parameters is lower than that with AE and ap in the 3 to 4 hour lag range whereas the autocorrelation of Dst is significantly higher over the entire 0 to 30 hour lag range. The implications of these differences between AE, ap, and Dst are discussed in terms of persistence of solar wind structure.

Smart, D. F.↗
NASA NTRS1982

A study of the initial oxidation of evaporated thin films of aluminum by AES, ELS, and ESD

The room temperature, low pressure, oxidation of evaporated aluminum thin films has been studied by AES, ELS, and ESD. ESD was the most sensitive of the three methods to characterize a clean aluminum surface. Two oxidation stages were distinguished in the 0-3000 L oxygen exposure range. Between 0 and 50 L, the chemisorption of oxygen atoms was characterized by a fast decrease of the 67 eV AES Al peak and the 10 eV surface plasmon peak, and by a simultaneous increase of the oxygen AES and ESD signals. After 50 L, a change in slope in all AES and ESD signal variations was attributed to the slow growth of a thin layer of aluminum oxide, which after 3000 L was still only a few angstroms thick.

Bujor, M.↗
NASA NTRS1992

Propagation of Flexural Mode AE Signals in GR/EP Composite Plates

It has been documented that AE signals propagate in thin plates as extensional and flexural plate modes. This was demonstrated using simulated AE sources (pencil lead breaks) by Gorman on thin aluminum and gr/ep composite plates and by Gorman and Prosser on thin aluminum plates. A typical signal from a pencil lead break source which identifies these two modes is shown. AE signals from transverse matrix cracking sources in gr/ep composite plates were also shown to propagate as plate modes by Gorman and Ziola. Smith showed that crack growth events in thin aluminum plates under spectrum fatigue loading produced signals that propagated as plate modes. Additionally, Prosser et al. showed that AE signals propagated as plate modes in a thin walled composite tube.

Prosser, W. H.↗
NASA NTRS2006

Comparison of NASA Team2 and AES-York Ice Concentration Algorithms Against Operational Ice Charts From the Canadian Ice Service

Ice concentration retrieved from spaceborne passive-microwave observations is a prime input to operational sea-ice-monitoring programs, numerical weather prediction models, and global climate models. Atmospheric Environment Service (AES)- York and the Enhanced National Aeronautics and Space Administration Team (NT2) are two algorithms that calculate ice concentration from Special Sensor Microwave/Imager observations. This paper furnishes a comparison between ice concentrations (total, thin, and thick types) output from NT2 and AES-York algorithms against the corresponding estimates from the operational analysis of Radarsat images in the Canadian Ice Service (CIS). A new data fusion technique, which incorporates the actual sensor's footprint, was developed to facilitate this study. Results have shown that the NT2 and AES-York algorithms underestimate total ice concentration by 18.35% and 9.66% concentration counts on average, with 16.8% and 15.35% standard deviation, respectively. However, the retrieved concentrations of thin and thick ice are in much more discrepancy with the operational CIS estimates when either one of these two types dominates the viewing area. This is more likely to occur when the total ice concentration approaches 100%. If thin and thick ice types coexist in comparable concentrations, the algorithms' estimates agree with CIS'S estimates. In terms of ice concentration retrieval, thin ice is more problematic than thick ice. The concept of using a single tie point to represent a thin ice surface is not realistic and provides the largest error source for retrieval accuracy. While AES-York provides total ice concentration in slightly more agreement with CIS'S estimates, NT2 provides better agreement in retrieving thin and thick ice concentrations.

Shokr, Mohammed↗
NASA NTRS2024

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗
NASA NTRS1994

(abstract) Airborne Emission Spectrometer (AES)

AES is a low-cost analog of the TES downlooking modes. Because AES operates at ambient temperature, limb-viewing is not possible. The first flight of AES took place in April 1994 on the NASA P3B aircraft out of Wallops Island, VA. While planned as an engineering test flight, spectra were successfully acquired both over the Atlantic Ocean and the area of the Great Dismal Swamp on the Virginia-North Carolina border. At this writing (July 1994), a second series of flights on the NASA DC8 aircraft out of Ames RC,CA is in progress. By the time of the workshop, a third series using the NASA C130 should have been accomplished.

Airborne Emission Spectrometer spectrometry AES Gr↗
DOE OSTI2022

Surface analysis insight note: Differentiation methods applicable to noisy data for determination of sp2‐ versus sp3‐hybridization of carbon allotropes and AES signal strengths

The derivatives of the spectra are commonly used for quantification in Auger Electron Spectroscopy (AES) spectra, while the derivative of the KLL C Auger line has proven to be valuable in obtaining a measure of the relative proportions of sp 2 ‐ and sp 3 ‐hybridization using the D‐parameter in both AES and X‐ray Photoelectron Spectroscopy (XPS). Differentiation of X‐ray Photoelectron Spectroscopy (XPS) and Auger Electron Spectroscopy (AES) spectra by numerical means is presented and illustrated for polymeric, such as PEEK and Nylon, as well as for graphitic materials including highly ordered pyrolytic graphite and graphene oxide. The most commonly available Savitzky–Golay method is explained mathematically and developed through the case of constructing a 5‐point quadratic polynomial convolution kernel suitable for differentiating spectra of adequate signal to noise. The concept of differentiation of spectra where signal to noise is less than adequate is also developed. Two alternative strategies to Savitzky–Golay differentiation are presented, which fit curves to data that allow derivatives to be obtained where Savitzky–Golay would otherwise fail. These alternative methods involve constructing a parametric curve that fits data over the entire energy interval of interest. Derivatives of spectra are then obtained by differentiating these parametric curves directly. A comparison of results for different materials for which specific sp 2 ‐ vs sp 3 ‐hybridized carbon proportions are of interest is used to emphasize the importance of characterizing methods used to differentiate spectra and understanding the characteristics of instrumentation used to measure spectra. The case for using Principal Component Analysis noise reduction with C KLL spectra is made for spectra collected from a heterogeneous graphene oxide sample.

Fairley, Neal↗
NASA NTRS1973

Cross-correlation analysis of the AE index and the interplanetary magnetic field Bz component.

A cross-correlation study between magnetospheric activity (the AE index) and the southward-directed component of the interplanetary magnetic field (IMF) is made for a total of 792 hours (33 days) with a time resolution of about 5.5 min. The peak correlation tends to occur when the interplanetary data are shifted approximately 40 min later with respect to the AE index data. Cross-correlation analysis is conducted on some idealized wave forms to illustrate that this delay between southward turning of the IMF and the AE index should not be interpreted as being the duration of the growth phase.

Meng, C.-I.↗
NASA NTRS1972

The use of the inner zone electron model AE-5 and associated computer programs

A users guide to the inner radiation zone electron model AE-5 is introduced. The guide covers a description of the model, the forms in which it is available, directions on how to use the model, and a discussion of its limitations. Computer programs MODEL and ORP are described. These are major programs needed to use the electron models AE-4 and AE-5 and the smoothed proton models.

Teague, M. J.↗
NASA NTRS1974

A high voltage power supply for the AE-C and D low energy electron experiment

A description is given of the electrical and mechanical design and operation of high voltage power supplies for space flight use. The supply was used to generate the spiraltron high voltage for low energy electron experiment on AE-C and D. Two versions of the supply were designed and built; one design is referred to as the low power version (AE-C) and the other as the high power version (AE-D). Performance is discussed under all operating conditions.

Gillis, J. A.↗
NASA NTRS1975

Evolution of the moon between 4.6 and 3.3 AE

A model of lunar evolution is proposed. At 4.6 AE an outer shell 60-100 km thick of an initially homogeneous moon was totally molten following accretion. 'Highland basalt' represents remnants of the chilled crust of this molten layer and, therefore, the mean lunar composition. Melt from the partially molten region below the outer shell intruded into it, enriching it in FeO, SiO2, radiogenic, and trivalent trace LIL (large ion lithop) elements. Fractional crystallization of the outer shell produced toward its base a mafic cumulate zone less than 40 km thick, the upper 60 km being anorthosite. The radiogenic elements concentrated together with dense residual melt in the upper parts pf the mafic cumulate zone. Between 4.6 and 4.3 AE a second differentiation led to localized enrichment from below of radiogenic elements in the plagioclase-rich, high-Mg/Mg + Fe residuum below the outer 100-km-thick shell. Melting at these enriched sites at about 4.0 AE produced to KREEP basalts. Later melting at sites of radiogenic element enrichment in the outer 100-km-thick shell produced the mare basalts.

Hollister, L. S.↗
NASA NTRS1981

Auroral arc electrodynamic parameters measured by AE-C and the Chatanika radar

Auroral arc electrodynamic parameters are studied using coordinated measurements between the AE-C satellite and the Chatanika radar. On January 4, 1978, the spacecraft twice crossed an east-west aligned auroral arc at widely spaced longitudes, spanning more than 3 hours in local time. The Chatanika radar was scanning in elevation at a magnetic longitude equidistant from the two AE-C crossings. The electric field pattern around this arc was remarkably similar at the three longitudes. Equatorward of the arc the north-south field was very intense (greater than approximately 60 mV/m), whereas poleward of the arc it was small (approximately 10 mV/m). The east-west field was small and almost constant across the arc. The same arc was observed by the radar for about 1 hour, and this electric field pattern did not change, even though the arc location, intensity, and width changed substantially. For a given electric field the AE-C measured ion temperature was substantially different during each of the arc crossings. This dissimilarity is attributed to differences in the F region neutral wind at the two longitudes. It is shown that the electric field variations are consistent with the existence of polarization charges within the arc, even though the electric field remained small poleward of the arc.

Beaujardiere, O. D. L.↗
NASA NTRS1981

Observational, reference and model data on solar EUV, from measurements on AE-E

Information on solar irradiance at wavelengths below 185 nm, observed by the EUVS experiment on the AE-E satellite over the entire development of the present sunspot cycle 21, is important to a variety of investigations of planetary thermospheres and ionospheres. Since strictly observational information is generally lacking in both the completeness and the spectral detail required by the more advanced programs, it has been necessary to develop computer models in connection with fully detailed compilations of an appropriate reference spectrum. The period of July 13-18, 1976, is selected as an observationally reliable AE-E data reference period reflecting solar conditions of minimum activity for solar cycle 21. It is pointed out that the assignments of absolute irradiance-reference values have been drawn for all available sources of information other than that provided by AE-E.

Hinteregger, H. E.↗