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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

Non-volatile, high density, high speed, Micromagnet-Hall effect Random Access Memory (MHRAM)

The micromagnetic Hall effect random access memory (MHRAM) has the potential of replacing ROMs, EPROMs, EEPROMs, and SRAMs because of its ability to achieve non-volatility, radiation hardness, high density, and fast access times, simultaneously. Information is stored magnetically in small magnetic elements (micromagnets), allowing unlimited data retention time, unlimited numbers of rewrite cycles, and inherent radiation hardness and SEU immunity, making the MHRAM suitable for ground based as well as spaceflight applications. The MHRAM device design is not affected by areal property fluctuations in the micromagnet, so high operating margins and high yield can be achieved in large scale integrated circuit (IC) fabrication. The MHRAM has short access times (less than 100 nsec). Write access time is short because on-chip transistors are used to gate current quickly, and magnetization reversal in the micromagnet can occur in a matter of a few nanoseconds. Read access time is short because the high electron mobility sensor (InAs or InSb) produces a large signal voltage in response to the fringing magnetic field from the micromagnet. High storage density is achieved since a unit cell consists only of two transistors and one micromagnet Hall effect element. By comparison, a DRAM unit cell has one transistor and one capacitor, and a SRAM unit cell has six transistors.

Wu, Jiin C.↗

Unbalanced Nested Random Effects Estimation of Variance Components

To investigate the contributing factors of variance in the measurement of an iodine 127 (127I) sample, we implement a nested random effects analysis of variance (ANOVA). Historically, the reported uncertainty on a measurement of 127I has been obtained by methods of forward uncertainty propagation because there is typically only one replicate of a given sample for which to estimate the uncertainty. When samples are processed there are several types of quality control (QC) standards analyzed along-side the unknown samples with two to five replicates for each. Assuming the variance observed in these replicate QC standards is representative of that of the unknown samples, we use these data in a nested random effects ANOVA to estimate the total uncertainty of a measurement. We demonstrate this approach with two sets of measurements from Idaho National Laboratory and compare the results with the forward uncertainty propagation approach. Variance component estimates for the coarsest level of the nesting structure were most imprecise because replicates were most limited at these levels. We find that the results largely agree between forward propagation and ANOVA, and the greatest contributors of variance are due to instrument variation and chemical processing, with human processing being among the smallest contributors. This analysis provides reassurance that the reported uncertainties using forward propagation are reasonable and the process is well controlled. We propose a future designed experiment to increase replicates at the coarsest level of the hierarchy to improve estimates of these variance components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling Grade IV Gas Emboli using a Limited Failure Population Model with Random Effects

Venous gas emboli (VGE) (gas bubbles in venous blood) are associated with an increased risk of decompression sickness (DCS) in hypobaric environments. A high grade of VGE can be a precursor to serious DCS. In this paper, we model time to Grade IV VGE considering a subset of individuals assumed to be immune from experiencing VGE. Our data contain monitoring test results from subjects undergoing up to 13 denitrogenation test procedures prior to exposure to a hypobaric environment. The onset time of Grade IV VGE is recorded as contained within certain time intervals. We fit a parametric (lognormal) mixture survival model to the interval-and right-censored data to account for the possibility of a subset of "cured" individuals who are immune to the event. Our model contains random subject effects to account for correlations between repeated measurements on a single individual. Model assessments and cross-validation indicate that this limited failure population mixture model is an improvement over a model that does not account for the potential of a fraction of cured individuals. We also evaluated some alternative mixture models. Predictions from the best fitted mixture model indicate that the actual process is reasonably approximated by a limited failure population model.

Thompson, Laura A.↗

The particle background observed by the X-ray detectors onboard Copernicus

The design and characteristics of low energy detectors on the Copernicus satellite are described. The functions of the sensors in obtaining data on the particle background. The procedure for processing the data obtained by the satellite is examined. The most significant positive deviations are caused by known weak X-ray sources in the field of view. In addition to small systemic effects, occasional random effects where the count rate increases suddenly and decreases within a few frames are analyzed.

Davison, P. J. N.↗

Revised (Mixed-Effects) Estimation for Forest Burning Emissions of Gases and Smoke, Fire/Emission Factor Typology, and Potential Remote Sensing Classification of Types for Ozone and Black-Carbon Simulation

We summarize recent progress (a) in correcting biomass burning emissions factors deduced from airborne sampling of forest fire plumes, (b) in understanding the variability in reactivity of the fresh plumes sampled in ARCTAS (2008), DC3 (2012), and SEAC4RS (2013) airborne missions, and (c) in a consequent search for remotely sensed quantities that help classify forest-fire plumes. Particle properties, chemical speciation, and smoke radiative properties are related and mutually informative, as pictures below suggest (slopes of lines of same color are similar). (a) Mixed-effects (random-effects) statistical modeling provides estimates of both emission factors and a reasonable description of carbon-burned simultaneously. Different fire plumes will have very different contributions to volatile organic carbon reactivity; this may help explain differences of free NOx(both gas- and particle-phase), and also of ozone production, that have been noted for forest-fire plumes in California. Our evaluations check or correct emission factors based on sequential measurements (e.g., the Normalized Ratio Enhancement and similar methods). We stress the dangers of methods relying on emission-ratios to CO. (b) This work confirms and extends many reports of great situational variability in emissions factors. VOCs vary in OH reactivity and NOx-binding. Reasons for variability are not only fuel composition, fuel condition, etc., but are confused somewhat by rapid transformation and mixing of emissions. We use "unmixing" (distinct from mixed-effects) statistics and compare briefly to approaches like neural nets. We focus on one particularly intense fire the notorious Yosemite Rim Fire of 2013. In some samples, NOx activity was not so suppressed by binding into nitrates as in other fires. While our fire-typing is evolving and subject to debate, the carbon-burned delta(CO2+CO) estimates that arise from mixed effects models, free of confusion by background-CO2 variation, should provide a solid base for discussion. (c) We report progress using promising links we find between emissions-related "fire types" and promising features deducible from remote observations of plumes, e.g., single scatter albedo, Angstrom exponent of scattering, Angstrom exponent of absorption, (CO column density)/(aerosol optical depth).

Remote sensing↗

Effects of random member length errors on the accuracy and internal loads of truss antennas

The effects of random member length errors on the surface accuracy, the defocus, and the residual, internal loads of tetrahedral truss antenna reflectors have been studied analytically. The analytical procedure involves performing multiple, deterministic finite element structural analyses for a particular truss. For each analysis, the normally distributed, random member length errors are selected by random number generator. A best fit paraboloid analysis is used to determine a root mean square error and defocus from each analysis. The statistical properties of these quantities as well as the internal loads are calculated from the results of many independent analyses. Results indicate that the number of members in a tetrahedral truss antenna of a given diameter has a significant effect on surface accuracy, defocus and internal loads. It was also found that the member axial stiffnesses and antenna focal length have a very small effect on reflector surface accuracy.

Greene, W. H.↗

Effects of Random Micron-Sized Roughness on Swept-Wing Transition

This study examines the effect of random micron-sized distributed roughness on stationary crossflow instabilities. The roughness parameters are varied by creating nanoparticle coatings of various formulations and applying them to inserts that cover approximately the first 14% of the model. In addition to the baseline configuration (no added roughness, root-mean-square (RMS) ≈ 0.42 𝜇m), panels with RMS roughness values of 4.8 and 8.6 𝜇m were tested, with correlation lengths of 1029 and 385 𝜇m, respectively. Despite the significant roughness levels tested, the transition location was found to be only mildly impacted by the additional roughness, and the roughness panel with lower RMS amplitude caused a larger upstream movement of transition, on average. However, the stationary crossflow amplitudes and wavelength content were found to vary substantially depending on the roughness input. In particular, the panel with higher RMS roughness amplitude resulted in significantly larger amplitudes in the 7.5-9 mm wavelength range at the farthest upstream measurement station, while the lower roughness panel resulted in mildly larger amplitudes at 10 mm and wavelengths larger than 15 mm. Nonlinear Parabolized Stability Equations (PSE) computations were performed to attempt to estimate the initial amplitudes of the stationary crossflow instabilities. Wavelength spectra were matched at the most upstream measurement location, but large discrepancies exist between the predicted and measured growth behavior farther downstream, thus, more work is required to improve confidence in initial amplitude estimates.

boundary-layer transition↗

Effects of Random Micron-Sized Roughness on Swept-Wing Transition

This study examines the effect of random micron-sized distributed roughness on stationary crossflow instabilities. The roughness parameters are varied by creating nanoparticle coatings of various formulations and applying them to inserts that cover approximately the first 14% of the model. In addition to the baseline configuration (no added roughness, root-mean-square (RMS) ≈ 0.42 𝜇m), panels with RMS roughness values of 4.8 and 8.6 𝜇m were tested, with correlation lengths of 1029 and 385 𝜇m, respectively. Despite the significant roughness levels tested, the transition location was found to be only mildly impacted by the additional roughness, and the roughness panel with lower RMS amplitude caused a larger upstream movement of transition, on average. However, the stationary crossflow amplitudes and wavelength content were found to vary substantially depending on the roughness input. In particular, the panel with higher RMS roughness amplitude resulted in significantly larger amplitudes in the 7.5-9 mm wavelength range at the farthest upstream measurement station, while the lower roughness panel resulted in mildly larger amplitudes at 10 mm and wavelengths larger than 15 mm. Nonlinear Parabolized Stability Equations (PSE) computations were performed to attempt to estimate the initial amplitudes of the stationary crossflow instabilities. Wavelength spectra were matched at the most upstream measurement location, but large discrepancies exist between the predicted and measured growth behavior farther downstream, thus, more work is required to improve confidence in initial amplitude estimates.

boundary-layer transition↗

Effects of Random Micron-Sized Roughness on Swept-Wing Transition

This study examines the effect of random micron-sized distributed roughness on stationary crossflow instabilities. The roughness parameters are varied by creating nanoparticle coatings of various formulations and applying them to inserts that cover approximately the first 14% of the model. In addition to the baseline configuration (no added roughness, root-mean-square (RMS) ≈ 0.42 𝜇m), panels with RMS roughness values of 4.8 and 8.6 𝜇m were tested, with correlation lengths of 1029 and 385 𝜇m, respectively. Despite the significant roughness levels tested, the transition location was found to be only mildly impacted by the additional roughness, and the roughness panel with lower RMS amplitude caused a larger upstream movement of transition, on average. However, the stationary crossflow amplitudes and wavelength content were found to vary substantially depending on the roughness input. In particular, the panel with higher RMS roughness amplitude resulted in significantly larger amplitudes in the 7.5-9 mm wavelength range at the farthest upstream measurement station, while the lower roughness panel resulted in mildly larger amplitudes at 10 mm and wavelengths larger than 15 mm. Nonlinear Parabolized Stability Equations (PSE) computations were performed to attempt to estimate the initial amplitudes of the stationary crossflow instabilities. Wavelength spectra were matched at the most upstream measurement location, but large discrepancies exist between the predicted and measured growth behavior farther downstream, thus, more work is required to improve confidence in initial amplitude estimates.

boundary-layer transition↗

Effects of random phase changes on the formation of synthetic aperture radar imagery

The effects of Gaussian random fluctuation and linear change of the echo phase on the response of the azimuth matched processor of a synthetic aperture radar (airborne or spaceborne for ocean-surface sensing) is analyzed numerically. It is found that the random fluctuation would not alter appreciably the processor response if its standard deviation is less than pi, while its normalized correlation time is larger than 1. If these two bounding conditions are not satisfied, then the sidelobe level becomes relatively large and overshadows the central peak. In the case of linear displacement it is found that the main effect is the spatial displacement of the point scatterer in the image plane.

Elachi, C.↗

A case study of the effects of random errors in rawinsonde data on computations of ageostrophic winds

Data input for the AVE-SESAME I experiment are utilized to describe the effects of random errors in rawinsonde data on the computation of ageostrophic winds. Computer-generated random errors for wind direction and speed and temperature are introduced into the station soundings at 25 mb intervals from which isentropic data sets are created. Except for the isallobaric and the local wind tendency, all winds are computed for Apr. 10, 1979 at 2000 GMT. Divergence fields reveal that the isallobaric and inertial-geostrophic-advective divergences are less affected by rawinsonde random errors than the divergence of the local wind tendency or inertial-advective winds.

Moore, J. T.↗