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At least 271 records · Page 15

Signatures of bulge triaxiality from kinematics in Baade's window

We study a sample of 62 Baade's Window, (l,b) = (1, -4)deg, K giants that have published proper motions, radial velocity, and metallicity. Using R(sub 0) = 8 kpc, we construct the velocity ellipsoids, namely the 3x3 velocity dispersion tensors, for the metal rich stars ((Fe/H) greater than or equal to 0) and metal poor stars ((Fe/H) less than or equal to -0.2). After diagonalizing the tensor, we find a vertex deviation characteristic of a nonaxisymmetric system. Eigenvalues for the two velocity ellipsoids (sigma(sub 1), sigma(sub 2), sigma(sub 3)) are (126, 89, 65) +/- 13 km/s for the metal rich sample and (154, 77, 83) +/- 25 km/s for the metal poor sample with their long axes pointing to two nearly perpendicular directions (l(sub v), b(sub v)) = (-65 +/- 9 deg, +14 +/- 9 deg) and (l(sub v), b(sub v)) = (25 +/- 14 deg, -11 +/- 14 deg), respectively. The vertex deviations of the velocity ellipsoids cannot be consistently explained by any oblate model. We are able to reject the hypothesis that the metal poor and metal rich populations are drawn from the same distribution at better than the 97% confidence level. We populate orbits in a realistic bar potential with a Gaussian velocity distribution, allowing us to simulate and interpret observations. We conclude that the data are consistent with a triaxial bulge pointing towards (l,b) with l less than 0 deg and b = 0 deg as suggested by earlier work on gas dynamics and the observed light distribution. We also predict that low latitude (absolute value of b less than or equal to 4 deg) bulge fields should show the vertex deviation more strongly and would therefore be the best locations for future proper motion studies. In the classification scheme of Athanassoula et al. (1983) the metal rich stars appear to occupy the B-family orbits which rotate in the prograde sense in the rest frame and have boxy shapes that are aligned with and supporting the bar. The metal poor stars in the sample lag behind the metal rich bulge and appear to occupy R-family orbits which rotate in the retrograde sense in the rest frame. They have nearly round loop shapes and are aligned perpendicularly to the bar, hence limit the triaxiality of the bar potential. The correlations between the metallicity and the orbit families can develop if the bulge forms dissipatively on a sufficiently long time scale. However, it is difficult to explain such correlations if most stars in the inner Galaxy form during the violent relaxation phase.

Zhao, Hongsheng↗

Heavy Ozone Enrichments from ATMOS Infrared Solar Spectra

Vertical enrichment profiles of stratospheric O-16O-16O-18 and O-16O-18O-16 (hereafter referred to as (668)O3 and (686)O3 respectively) have been derived from space-based solar occultation spectra recorded at 0.01 cm(exp-1) resolution by the ATMOS (Atmospheric Trace MOlecule Spectroscopy) Fourier transform infrared (FTIR) spectrometer. The observations, made during the Spacelab 3 and ATLAS-1, -2, and -3 shuttle missions, cover polar, mid-latitude and tropical regions between 26 to 2.6 mb inclusive (approximately 25 to 41 km). Average enrichments, weighted by molecular (48)O3 density, of (15 +/- 6)% were found for (668)O3 and (10 +/- 7)% for (686)O3. Defining the mixing ratio of (50)O3 as the sum of those for (668)O3 and (686)O3, an enrichment of (13 plus or minus 5)% was found for (50)O3 (1 sigma standard deviation). No latitudinal or vertical gradients were found outside this standard deviation. From a series of ground-based measurements by the ATMOS instrument at Table Mountain, California (34.4 deg N), an average total column (668)O3 enrichment of (17 +/- 4)% (1 sigma standard deviation) was determined, with no significant seasonal variation discernable. Possible biases in the spectral intensities that affect the determination of absolute enrichments are discussed.

Irion, F. W.↗

Application of Parametrized Post-Newtonian Methods to the Gravitational IS of Satellite Energy Exchange Data

Project Satellite Energy Exchange (SEE) is a free-flying, high altitude satellite that utilizes space to construct a passive, low-temperature, nano-g environment in order to accurately measure the poorly known gravitational constant G plus other gravitational parameters that are difficult to measure in an earth-based laboratory. Eventually data received from SEE must be analyzed using a model of the gravitational interaction including parameters that describe deviations from general relativity and experiment. One model that can be used to fit tile data is the Parametrized post- Newtonian (PPN) approximation of general relativity (GR) which introduces ten parameters which have specified values in (GR). It is the lowest-order, consistent approximation that contains non linear terms. General relativity predicts that the Robertson parameters, gamma (light deflection), and beta (advance of the perihelion), are both 1 in GR. Another eight parameters, alpha(sub k), k=1,2,3 and zeta(sub k), k=1,2,3,4 and Xi are all zero in GR. Non zero values for alpha(sub k) parameters predict preferred frame effects; for zeta(sub k) violations of globally conserved quantities such as mass, momentum and angular momentum; and for Xi a contribution from the Whitehead theory of gravitation, once thought to be equivalent to GR. In addition, there is the possibility that there may be a preferred frame for the universe. If such a frame exists, then all observers must measure the velocity omega of their motion with respect to this universal rest frame. Such a frame is somewhat reminiscent of the concept of the ether which was supposedly the frame in which the velocity of light took the value c predicted by special relativity. The SEE mission can also look for deviations from the r(exp -2) law of Newtonian gravity, adding parameters alpha and lamda for non Newtonian behavior that describe the magnitude and range of the r(exp -2) deviations respectively. The foundations of the GR supposedly agree with Newtonian gravity to first order so that the parameters alpha and lamda are zero in GR. More important, however, GR subsequently depends on this Newtonian approximation to build up the non linear higher-order terms which forms the basis of the PPN frame work.

Smalley, Larry L.↗

Laser Interferometer Space Antenna (LISA) Far Field Phase Pattern

The Laser Interferometry Space Antenna (LISA) for the detection of Gravitational Waves is a very long baseline interferometer that will measure the changes in the distance of a five million kilometer arm to pico meter accuracies. Knowledge of the phase deviations from a spherical wave and what causes these deviations are needed considerations in (as a minimum) the design of the telescope and in determining pointing requirements. Here we present the far field phase deviations from a spherical wave for given Zernike aberrations and obscurations of the exit pupil.

Waluschka, Eugene↗

Laser Interferometer Space Antenna (LISA) Far Field Phase Patterns

The Laser Interferometer Space Antenna (LISA) for the detection of Gravitational Waves is a very long baseline interferometer, which will measure the changes in the distance of a five million kilometer arm to picometer accuracies. Knowledge of the phase deviations from a spherical wave and what causes these deviations are needed considerations in (as a minimum) the design of the telescope and in determining pointing requirements. Here we will present the far field phase deviations from a spherical wave for given Zernike aberrations of the exit pupil and discuss how these results affect the choice of a telescope design.

Waluschka, Eugene↗

Modelling and Estimation of Dynamic Ocean Topography Within Global Geopotential Solutions

In this poster, we will present a report on the ongoing investigation "Improved Gravitational and Dynamic Height Models Through the use of Oceanographic Data." we have used a two year mean (1993-1994) of the Dynamic ocean Topography (DOT) field implied by the Semtner and Chervin POCM_4B model, and developed normal equations in surface spherical harmonics to degree and order 30. These normal equations, were combined with normal equations derived from TOPEX and ERS-1 altimeter data over the same time period. Combination solutions (based on satellite tracking data, altimeter data, surface gravity data and OCM data) were were developed Test solutions were obtained estimating the DOT field to 2Ox2O and 3ox3O. These solutions were tested with independent DOT values computed over 38 WOCE hydrographic sections, which contained a total of 3072 stations and represented 216000 km of travelled lines. The weighted standard deviation of the differences between the DOT obtained from the hydrographic data and and the field estimated from the joint combination solutions was computed for each of the test models, the weighted standard deviation for the baseline combination solution excluding the POCM4_B data was 9.7 cm for a DOT solution to 30x30, where introducing the POCM4_B data into the combination model reduced the standard deviation to 9.2 cm, indicating the the introduction of oceanographic information benefits the solution for the dynamic ocean topography. We will discuss the weighting schemes applied and the method of solution. Another aspect of our investigation involves testing alternate parametric representations of the dynamic height field. We looked at the alternative representations in terms of the Proudman functions (PF), and compared these to the use of spherical harmonics (SH) to represent the dynamic ocean topography, using once again the 1993 and 1994 output of the POCM4_B OCM as the reference model. A significant advantage of PF's over SH's is that the former require no "fill-in" values over areas where the DOT is undefined. We show that the PF and SH results using equal number of parameters agree quite well in overall content. In addition, PFs appear better suited for representation of high frequency signals close to the signal boundary. The development of the PF solutions for the DOT will be described and the statistics of the comparisons will be presented.

Lemoine, Frank G.↗

A Priori Subgrid Analysis of Temporal Mixing Layers with Evaporating Droplets

Subgrid analysis of a transitional temporal mixing layer with evaporating droplets has been performed using three sets of results from a Direct Numerical Simulation (DNS) database, with Reynolds numbers (based on initial vorticity thickness) as large as 600 and with droplet mass loadings as large as 0.5. In the DNS, the gas phase is computed using a Eulerian formulation, with Lagrangian droplet tracking. The Large Eddy Simulation (LES) equations corresponding to the DNS are first derived, and key assumptions in deriving them are first confirmed by computing the terms using the DNS database. Since LES of this flow requires the computation of unfiltered gas-phase variables at droplet locations from filtered gas-phase variables at the grid points, it is proposed to model these by assuming the gas-phase variables to be the sum of the filtered variables and a correction based on the filtered standard deviation; this correction is then computed from the Subgrid Scale (SGS) standard deviation. This model predicts the unfiltered variables at droplet locations considerably better than simply interpolating the filtered variables. Three methods are investigated for modeling the SGS standard deviation: the Smagorinsky approach, the Gradient model and the Scale-Similarity formulation. When the proportionality constant inherent in the SGS models is properly calculated, the Gradient and Scale-Similarity methods give results in excellent agreement with the DNS.

Okongo, Nora↗

A Priori Subgrid Scale Modeling for a Droplet Laden Temporal Mixing Layer

Subgrid analysis of a transitional temporal mixing layer with evaporating droplets has been performed using a direct numerical simulation (DNS) database. The DNS is for a Reynolds number (based on initial vorticity thickness) of 600, with droplet mass loading of 0.2. The gas phase is computed using a Eulerian formulation, with Lagrangian droplet tracking. Since Large Eddy Simulation (LES) of this flow requires the computation of unfiltered gas-phase variables at droplet locations from filtered gas-phase variables at the grid points, it is proposed to model these by assuming the gas-phase variables to be given by the filtered variables plus a correction based on the filtered standard deviation, which can be computed from the sub-grid scale (SGS) standard deviation. This model predicts unfiltered variables at droplet locations better than simply interpolating the filtered variables. Three methods are investigated for modeling the SGS standard deviation: Smagorinsky, gradient and scale-similarity. When properly calibrated, the gradient and scale-similarity methods give results in excellent agreement with the DNS.

Okongo, Nora↗

Uncertainty Analysis of Decomposing Polyurethane Foam

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

Hobbs, Michael L.↗

Aero-thermal Calibration of the NASA Glenn Icing Research Tunnel (2000 Tests)

Aerothermal calibration measurements and flow quality surveys were made in the test section of the Icing Research Tunnel at the NASA Glenn Research Center. These surveys were made following major facility modifications including widening of the heat exchanger tunnel section, replacement of the heat exchanger, installation of new turning vanes, and installation of new fan exit guide vanes. Standard practice at NASA Glenn requires that test section calibration and flow quality surveys be performed following such major facility modifications. A single horizontally oriented rake was used to survey the flow field at several vertical positions within a single cross-sectional plane of the test section. These surveys provided a detailed mapping of the total and static pressure, total temperature, Mach number, velocity, flow angle and turbulence intensity. Data were acquired over the entire velocity and total temperature range of the facility. No icing conditions were tested; however, the effects of air sprayed through the water injecting spray bars were assessed. All data indicate good flow quality. Mach number standard deviations were less than 0.0017, flow angle standard deviations were between 0.3 deg and 0.8 deg, total temperature standard deviations were between 0.5 and 1.8 F for subfreezing conditions, axial turbulence intensities varied between 0.3 and 1.0 percent, and transverse turbulence intensities varied between 0.3 and 1.5 percent. Measurement uncertainties were also quantified.

Gonsalez, Jose C.↗

Rotational Energy Transfer Cross Sections in N2-N2 Collisions

Rotational inelastic transitions of N2 have been studied in the coupled state (CS, also called centrifugal sudden) and infinite-order-sudden (IOS) approximations, using the N2-N2 rigid-rotor potential of van der Avoird et al. For benchmarking purposes, close coupling (CC) calculations have also been carried out over a limited energy range and for even j - even j collisions only. Both the CC and CS cross sections have been obtained with and without exchange symmetry, whereas exchange is neglected in the IOS calculations. The CS results track the CC cross sections rather well. At total energies between 113 to 219 cm(exp -1) the average deviation is 14%. The deviation decrease with increasing energy, indicating that the CS approximation can be used as a substitute at higher energies when the CC calculations become impractical. Comparison between the CS and IOS cross sections at the high energy end of the CS calculation, 500 - 680 cm(exp-1), shows significant differences between the two. In addition, the IOS results exhibits sensitivity to the amount of inelasticity and the results for large DELTA J transitions are subjected to bigger errors. At total energy 113 cm(exp -1) and above, the average deviation between state-to-state cross sections calculated with even and odd exchange symmetries is 1.5%.

Huo, Winifred M.↗

A Spatio-Temporal Approach for Global Validation and Analysis of MODIS Aerosol Products

With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET-derived aerosol data. The means and standard deviations of identical parameters from MOMS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue.

Ichoku, Charles↗

Determination of Small Animal Long Bone Properties Using Densitometry

Assessment of bone structural property changes due to loading regimens or pharmacological treatment typically requires destructive mechanical testing and sectioning. Our group has accurately and non-destructively estimated three dimensional cross-sectional areal properties (principal moments of inertia, Imax and Imin, and principal angle, Theta) of human cadaver long bones from pixel-by-pixel analysis of three non-coplanar densitometry scans. Because the scanner beam width is on the order of typical small animal diapbyseal diameters, applying this technique to high-resolution scans of rat long bones necessitates additional processing to minimize errors induced by beam smearing, such as dependence on sample orientation and overestimation of Imax and Imin. We hypothesized that these errors are correctable by digital image processing of the raw scan data. In all cases, four scans, using only the low energy data (Hologic QDR-1000W, small animal mode), are averaged to increase image signal-to-noise ratio. Raw scans are additionally processed by interpolation, deconvolution by a filter derived from scanner beam characteristics, and masking using a variable threshold based on image dynamic range. To assess accuracy, we scanned an aluminum step phantom at 12 orientations over a range of 180 deg about the longitudinal axis, in 15 deg increments. The phantom dimensions (2.5, 3.1, 3.8 mm x 4.4 mm; Imin/Imax: 0.33-0.74) were comparable to the dimensions of a rat femur which was also scanned. Cross-sectional properties were determined at 0.25 mm increments along the length of the phantom and femur. The table shows average error (+/- SD) from theory of Imax, Imin, and Theta) over the 12 orientations, calculated from raw and fully processed phantom images, as well as standard deviations about the mean for the femur scans. Processing of phantom scans increased agreement with theory, indicating improved accuracy. Smaller standard deviations with processing indicate increased precision and repeatability. Standard deviations for the femur are consistent with those of the phantom. We conclude that in conjunction with digital image enhancement, densitometry scans are suitable for non-destructive determination of areal properties of small animal bones of comparable size to our phantom, allowing prediction of Imax and Imin within 2.5% and Theta within a fraction of a degree. This method represents a considerable extension of current methods of analyzing bone tissue distribution in small animal bones.

Breit, Gregory A.↗

Probabilistic Analysis and Density Parameter Estimation Within Nessus

This NASA educational grant has the goal of promoting probabilistic analysis methods to undergraduate and graduate UTSA engineering students. Two undergraduate-level and one graduate-level course were offered at UTSA providing a large number of students exposure to and experience in probabilistic techniques. The grant provided two research engineers from Southwest Research Institute the opportunity to teach these courses at UTSA, thereby exposing a large number of students to practical applications of probabilistic methods and state-of-the-art computational methods. In classroom activities, students were introduced to the NESSUS computer program, which embodies many algorithms in probabilistic simulation and reliability analysis. Because the NESSUS program is used at UTSA in both student research projects and selected courses, a student version of a NESSUS manual has been revised and improved, with additional example problems being added to expand the scope of the example application problems. This report documents two research accomplishments in the integration of a new sampling algorithm into NESSUS and in the testing of the new algorithm. The new Latin Hypercube Sampling (LHS) subroutines use the latest NESSUS input file format and specific files for writing output. The LHS subroutines are called out early in the program so that no unnecessary calculations are performed. Proper correlation between sets of multidimensional coordinates can be obtained by using NESSUS' LHS capabilities. Finally, two types of correlation are written to the appropriate output file. The program enhancement was tested by repeatedly estimating the mean, standard deviation, and 99th percentile of four different responses using Monte Carlo (MC) and LHS. These test cases, put forth by the Society of Automotive Engineers, are used to compare probabilistic methods. For all test cases, it is shown that LHS has a lower estimation error than MC when used to estimate the mean, standard deviation, and 99th percentile of the four responses at the 50 percent confidence level and using the same number of response evaluations for each method. In addition, LHS requires fewer calculations than MC in order to be 99.7 percent confident that a single mean, standard deviation, or 99th percentile estimate will be within at most 3 percent of the true value of the each parameter. Again, this is shown for all of the test cases studied. For that reason it can be said that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ; furthermore, the newest LHS module is a valuable new enhancement of the program.

Godines, Cody R.↗

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been proposed by the Society of Automotive Engineers (SAE). The test cases compare different probabilistic methods within NESSUS because it is important that a user can have confidence that estimates of stochastic parameters of a response will be within an acceptable error limit. For each response, the mean, standard deviation, and 0.99 percentile, are repeatedly estimated which allows confidence statements to be made for each parameter estimated, and for each method. Thus, the ability of several stochastic methods to efficiently and accurately estimate density parameters is compared using four valid test cases. While all of the reliability methods used performed quite well, for the new LHS module within NESSUS it was found that it had a lower estimation error than MC when they were used to estimate the mean, standard deviation, and 0.99 percentile of the four different stochastic responses. Also, LHS required a smaller amount of calculations to obtain low error answers with a high amount of confidence than MC. It can therefore be stated that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ and the newest LHS module is a valuable new enhancement of the program.

Chamis, Chrisos C.↗

Specification of the ISS Plasma Environment Variability

Quantifying the spacecraft charging risks and corresponding hazards for the International Space Station (ISS) requires a plasma environment specification describing the natural variability of ionospheric temperature (Te) and density (Ne). Empirical ionospheric specification and forecast models such as the International Reference Ionosphere (IRI) model typically only provide estimates of long term (seasonal) mean Te and Ne values for the low Earth orbit environment. Knowledge of the Te and Ne variability as well as the likelihood of extreme deviations from the mean values are required to estimate both the magnitude and frequency of occurrence of potentially hazardous spacecraft charging environments for a given ISS construction stage and flight configuration. This paper describes the statistical analysis of historical ionospheric low Earth orbit plasma measurements used to estimate Ne, Te variability in the ISS flight environment. The statistical variability analysis of Ne and Te enables calculation of the expected frequency of Occurrence of any particular values of Ne and Te, especially those that correspond to possibly hazardous spacecraft charging environments. The database used in the original analysis included measurements from the AE-C, AE-D, and DE-2 satellites. Recent work on the database has added additional satellites to the database and ground based incoherent scatter radar observations as well. Deviations of the data values from the IRI estimated Ne, Te parameters for each data point provide a statistical basis for modeling the deviations of the plasma environment from the IRI model output. This technique, while developed specifically for the Space Station analysis, can also be generalized to provide ionospheric plasma environment risk specification models for low Earth orbit over an altitude range of 200 km through approximately 1000 km.

Minow, Joseph I.↗

Specifying the ISS Plasma Environment

Quantifying the spacecraft charging risks and corresponding hazards for the International Space Station (ISS) requires a plasma environment specification describing the natural variability of ionospheric temperature (Te) and density (Ne). Empirical ionospheric specification and forecast models such as the International Reference Ionosphere (IN) model typically only provide estimates of long term (seasonal) mean Te and Ne values for the low Earth orbit environment. Knowledge of the Te and Ne variability as well as the likelihood of extreme deviations from the mean values are required to estimate both the magnitude and frequency of occurrence of potentially hazardous spacecraft charging environments for a given ISS construction stage and flight configuration. This paper describes the statistical analysis of historical ionospheric low Earth orbit plasma measurements used to estimate Ne, Te variability in the ISS flight environment. The statistical variability analysis of Ne and Te enables calculation of the expected frequency of occurrence of any particular values of Ne and Te, especially those that correspond to possibly hazardous spacecraft charging environments. The database used in the original analysis included measurements from the AE-C, AE-D, and DE-2 satellites. Recent work on the database has added additional satellites to the database and ground based incoherent scatter radar observations as well. Deviations of the data values from the IRI estimated Ne, Te parameters for each data point provide a statistical basis for modeling the deviations of the plasma environment from the IRI model output.

Minow, Joseph I.↗

Historical Precision of an Ozone Correction Procedure for AMO Solar Cell Calibration

In an effort to improve the accuracy of the high altitude aircraft method for calibration of high band-gap solar cells, the ozone correction procedure has been revisited. The new procedure adjusts the measured short circuit current, Isc, according to satellite based ozone measurements and a model of the atmospheric ozone profile then extrapolates the measurements to air mass zero, AM0. The purpose of this paper is to assess the precision of the revised procedure by applying it to historical data sets. The average Isc of a silicon cell for a flying season increased 0.5% and the standard deviation improved from 0.5% to 0.3% The 12 year average Isc of a GaAs cell increased 1% and the standard deviation improved from 0.8% to 0.5%. The slight increase in measured Isc and improvement in standard deviation suggests that the accuracy of the aircraft method may improve from 1% to nearly 0.5%.

Snyder, David B.↗