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NASA NTRS1993

Probabilistic nonlinear finite element analysis of composite structures

A probabilistic finite element analysis procedure for laminated composite shells is developed. A total Lagrangian finite element formulation, employing a degenerated three-dimensional laminated composite shell element with the full Green-Lagrange strains and first-order shear deformable kinematics, is used. The first-order second-moment technique for probabilistic finite element analysis of random fields is employed, and results are presented in the form of mean and variance of the structural response. Reliability calculations are made by using the first-order reliability method combined with sensitivity derivatives from the finite element analysis. Both ply-level and micromechanics-level random variables are incorporated, the latter by means of the Aboudi micromechanics model. Two sample problems are solved to verify the accuracy of the procedures developed and to quantify the variability of certain material type/structure combinations. In general, the procedure is quite effective in determining the response statistics and reliability for linear and geometric nonlinear behavior of laminated composite shells.

Engelstad, S. P.↗

NASA NTRS1974

On evaluating compliance with air pollution levels not to be exceeded more than once per year

The adequacy is considered of currently practiced monitoring and data reduction techniques for assessing compliance with 24-hour Air Quality Standards (AQS) not to be exceeded more than once per year. The present situation for suspended particulates is discussed. The following conclusions are reached: (1) For typical less than daily sampling (i.e., 60 to 120 24-hour samples per year) the deviation from independence of the data set should not be substantial. (2) The interchange of exponentiation and expectation operations in the EPA data reduction model, underestimates the second highest level by about 4 to 8 percent for typical sigma values. (3) Estimates of the second highest pollution level have associated with them a large statistical variability arising from the finite size of the sample. The 0.95 confidence interval ranges from + or - 40 percent for 120 samples per year to + or - 84 percent for 30 samples per year. (4) The design value suggested by EPA for abatement and/or control planning purposes typically gives a margin of safety of 60 to 120 percent.

Neustadter, H. E.↗

NASA NTRS1984

Forest inventory using multistage sampling with probability proportional to size

A multistage sampling technique, with probability proportional to size, for forest volume inventory using remote sensing data is developed and evaluated. The study area is located in the Southeastern Brazil. The LANDSAT 4 digital data of the study area are used in the first stage for automatic classification of reforested areas. Four classes of pine and eucalypt with different tree volumes are classified utilizing a maximum likelihood classification algorithm. Color infrared aerial photographs are utilized in the second stage of sampling. In the third state (ground level) the time volume of each class is determined. The total time volume of each class is expanded through a statistical procedure taking into account all the three stages of sampling. This procedure results in an accurate time volume estimate with a smaller number of aerial photographs and reduced time in field work.

Parada, N. D. J.↗

NASA NTRS2002

Experimental Investigations of Non-Stationary Properties In Radiometer Receivers Using Measurements of Multiple Calibration References

Radiometers must be periodically calibrated because the receiver response fluctuates. Many techniques exist to correct for the time varying response of a radiometer receiver. An analytical technique has been developed that uses generalized least squares regression (LSR) to predict the performance of a wide variety of calibration algorithms. The total measurement uncertainty including the uncertainty of the calibration can be computed using LSR. The uncertainties of the calibration samples used in the regression are based upon treating the receiver fluctuations as non-stationary processes. Signals originating from the different sources of emission are treated as simultaneously existing random processes. Thus, the radiometer output is a series of samples obtained from these random processes. The samples are treated as random variables but because the underlying processes are non-stationary the statistics of the samples are treated as non-stationary. The statistics of the calibration samples depend upon the time for which the samples are to be applied. The statistics of the random variables are equated to the mean statistics of the non-stationary processes over the interval defined by the time of calibration sample and when it is applied. This analysis opens the opportunity for experimental investigation into the underlying properties of receiver non stationarity through the use of multiple calibration references. In this presentation we will discuss the application of LSR to the analysis of various calibration algorithms, requirements for experimental verification of the theory, and preliminary results from analyzing experiment measurements.

Racette, Paul↗

NASA NTRS2006

Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don↗

NASA NTRS2006

Temperature-dependent Absolute Refractive Index Measurements of Synthetic Fused Silica

Using the Cryogenic, High-Accuracy Refraction Measuring System (CHARMS) at NASA's Goddard Space Flight Center, we have measured the absolute refractive index of five specimens taken from a very large boule of Corning 7980 fused silica from temperatures ranging from 30 to 310 K at wavelengths from 0.4 to 2.6 microns with an absolute uncertainty of plus or minus 1 x 10 (exp -5). Statistical variations in derived values of the thermo-optic coefficient (dn/dT) are at the plus or minus 2 x 10 (exp -8)/K level. Graphical and tabulated data for absolute refractive index, dispersion, and thermo-optic coefficient are presented for selected wavelengths and temperatures along with estimates of uncertainty in index. Coefficients for temperature-dependent Sellmeier fits of measured refractive index are also presented to allow accurate interpolation of index to other wavelengths and temperatures. We compare our results to those from an independent investigation (which used an interferometric technique for measuring index changes as a function of temperature) whose samples were prepared from the same slugs of material from which our prisms were prepared in support of the Kepler mission. We also compare our results with sparse cryogenic index data from measurements of this material from the literature.

Leviton, Douglas B.↗

NASA NTRS2003

Design and Performance Tests of Ultra-Compact Calorimeters for High Energy Astrophysics

This R&D project had two goals: a) the study of general-application ultra-compact calorimetry technologies for use in High Energy Astrophysics and, b) contribute to the design of an efficient calorimeter for the ACCESS mission. The direct measurement of galactic cosmic ray fluxes is performed from space or from balloon-borne detectors. Detectors used in those studies are limited in size and, specially, in weight. Since galactic cosmic ray fluxes are very small, detectors with high geometrical acceptances and long exposures are usually required for collecting enough statistics. We have studied calorimeter techniques that could produce large geometrical acceptance per unit of mass (G/w) and that may be used to study galactic cosmic rays at intermediate energies (knee energies).-The most important asset for detection of primary cosmic rays at and about the knee is large acceptance. To construct a large acceptance calorimeter (this term is used here in its most general accepted meaning of calorimeter as a device to measure particle energies ) the detector needs to be verv liaht or verv shallow . We studied two possible technologies to built compact calorimeters: the use of lead-tungstate crystals (PWO) and the use of sampling calorimetry using scintillating fibers embedded in a matrix of powder tungsten. For a very light detector, we considered the possibility of using Optical Transition Radiation (OTR) to measure the energy (and perhaps also direction and identity) of VHE cosmic rays.

Salgado, Carlos W.↗

NASA NTRS2009

A Comparison Study of Normal-Incidence Acoustic Impedance Measurements of a Perforate Liner

The eduction of the acoustic impedance for liner configurations is fundamental to the reduction of noise from modern jet engines. Ultimately, this property must be measured accurately for use in analytical and numerical propagation models of aircraft engine noise. Thus any standardized measurement techniques must be validated by providing reliable and consistent results for different facilities and sample sizes. This paper compares normal-incidence acoustic impedance measurements using the two-microphone method of ten nominally identical individual liner samples from two facilities, namely 50.8 mm and 25.4 mm square waveguides at NASA Langley Research Center and the University of Florida, respectively. The liner chosen for this investigation is a simple single-degree-of-freedom perforate liner with resonance and anti-resonance frequencies near 1.1 kHz and 2.2 kHz, respectively. The results show that the ten measurements have the most variation around the anti-resonance frequency, where statistically significant differences exist between the averaged results from the two facilities. However, the sample-to-sample variation is comparable in magnitude to the predicted cross-sectional area-dependent cavity dissipation differences between facilities, providing evidence that the size of the present samples does not significantly influence the results away from anti-resonance.

Schultz, Todd↗

NASA NTRS2006

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗

NASA NTRS2010

A Geostatistical Data Fusion Technique for Merging Remote Sensing and Ground-Based Observations of Aerosol Optical Thickness

Particles in the atmosphere reflect incoming sunlight, tending to cool the Earth below. Some particles, such as soot, also absorb sunlight, which tens to warm the ambient atmosphere. Aerosol optical depth (AOD) is a measure of the amount of particulate matter in the atmosphere, and is a key input to computer models that simulate and predict Earth's changing climate. The global AOD products from the Multi-angle Imaging SpectroRadiometer (MISR) and the MODerate resolution Imaging Spectroradiometer (MODIS), both of which fly on the NASA Earth Observing System's Terra satellite, provide complementary views of the particles in the atmosphere. Whereas MODIS offers global coverage about four times as frequent as MISR, the multi-angle data makes it possible to separate the surface and atmospheric contributions to the observed top-of-atmosphere radiances, and also to more effectively discriminate particle type. Surface-based AERONET sun photometers retrieve AOD with smaller uncertainties than the satellite instruments, but only at a few fixed locations. So there are clear reasons to combine these data sets in a way that takes advantage of their respective strengths. This paper represents an effort at combining MISR, MODIS and AERONET AOD products over the continental US, using a common spatial statistical technique called kriging. The technique uses the correlation between the satellite data and the "ground-truth" sun photometer observations to assign uncertainty to the satellite data on a region-by-region basis. The larger fraction of the sun photometer variance that is duplicated by the satellite data, the higher the confidence assigned to the satellite data in that region. In the Western and Central US, MISR AOD correlation with AERONET are significantly higher than those with MODIS, likely due to bright surfaces in these regions, which pose greater challenges for the single-view MODIS retrievals. In the east, MODIS correlations are higher, due to more frequent sampling of the varying AOD. These results demonstrate how the MISR and MODIS aerosol products are complementary. The underlying technique also provides one method for combining these products in such a way that takes advantage of the strengths of each, in the places and times when they are maximal, and in addition, yields an estimate of the associated uncertainties in space and time.

Chatterjee, Abhishek↗

NASA NTRS1984

Processes and subdivisions in diogenites, a multivariate statistical analysis

Multivariate statistical techniques used on diogenite orthopyroxene analyses show the relationships that occur within diogenites and the two orthopyroxenite components (class I and II) in the polymict diogenite Garland. Cluster analysis shows that only Peckelsheim is similar to Garland class I (Fe-rich) and the other diogenites resemble Garland class II. The unique diogenite Y 75032 may be related to type I by fractionation. Factor analysis confirms the subdivision and shows that Fe does not correlate with the weakly incompatible elements across the entire pyroxene composition range, indicating that igneous fractionation is not the process controlling total diogenite composition variation. The occurrence of two groups of diogenites is interpreted as the result of sampling or mixing of two main sequences of orthopyroxene cumulates with slightly different compositions.

Harriott, T. A.↗

NASA NTRS1982

Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data

Detection of a periodic signal hidden in noise is frequently a goal in astronomical data analysis. This paper does not introduce a new detection technique, but instead studies the reliability and efficiency of detection with the most commonly used technique, the periodogram, in the case where the observation times are unevenly spaced. This choice was made because, of the methods in current use, it appears to have the simplest statistical behavior. A modification of the classical definition of the periodogram is necessary in order to retain the simple statistical behavior of the evenly spaced case. With this modification, periodogram analysis and least-squares fitting of sine waves to the data are exactly equivalent. Certain difficulties with the use of the periodogram are less important than commonly believed in the case of detection of strictly periodic signals. In addition, the standard method for mitigating these difficulties (tapering) can be used just as well if the sampling is uneven. An analysis of the statistical significance of signal detections is presented, with examples

Scargle, J. D.↗

NASA NTRSDate not supplied

Evaluating the Efficacy of Conditional Variational Autoencoders in Generating Synthetic Single Nuclei RNA-Seq Data for Space Biology Research

Astronauts are subject to unique stressors during spaceflight, leading to changes in their cellular function. However, neither astronauts nor model organisms respond the same to spaceflight, and research implicates a contribution of omics components in differential responses. Understanding how gene expression affects astronaut health is critical for the success of long-term space missions, prompting interest in developing personalized predictive models leveraging artificial intelligence (AI) and machine learning (ML) techniques. Developing such models requires extensive data, which is challenging to obtain and share. This study explores the use of conditional variational autoencoders (CVAEs) to synthetically generate single-nuclei RNA-seq (snRNA-seq) data. CVAEs build on standard variational autoencoders (VAEs) by conditioning data generation on covariates like sample identity and mission parameters, enhancing the relevance of generated data for specific contexts. For our work, we built two CVAEs with varying degrees of sparsity to optimize both interpretability and generative power. We train and validate models on existing snRNA-seq data collected from the brain tissue of mice subjected to spaceflight conditions and their ground control counterparts. We evaluate model performance using statistical tests and visualizations to compare synthetic data to real data. We aim to demonstrate that these prototype CVAE architectures could be used in future space biology work and that this is a method worth further exploring.

Sarah Golts↗

NASA NTRS1972

Thermospheric temperature measurement technique.

A method for measurement of temperature in the earth's lower thermosphere from a high-velocity probes is described. An undisturbed atmospheric sample is admitted to the instrument by means of a free molecular flow inlet system of skimmers which avoids surface collisions of the molecules prior to detection. Measurement of the time-of-flight distribution of an initially well-localized group of nitrogen metastable molecular states produced in an open, crossed electron-molecular beam source, yields information on the atmospheric temperature. It is shown that for high vehicle velocities, the time-of-flight distribution of the metastable flux is a sensitive indicator of atmospheric temperature. The temperature measurement precision should be greater than 94% at the 99% confidence level over the range of altitudes from 120-170 km. These precision and altitude range estimates are based on the statistical consideration of the counting rates achieved with a multichannel analyzer using realistic values for system parameters.

Hueser, J. E.↗

NASA NTRS1987

Probabilistic finite elements

In the Probabilistic Finite Element Method (PFEM), finite element methods have been efficiently combined with second-order perturbation techniques to provide an effective method for informing the designer of the range of response which is likely in a given problem. The designer must provide as input the statistical character of the input variables, such as yield strength, load magnitude, and Young's modulus, by specifying their mean values and their variances. The output then consists of the mean response and the variance in the response. Thus the designer is given a much broader picture of the predicted performance than with simply a single response curve. These methods are applicable to a wide class of problems, provided that the scale of randomness is not too large and the probabilistic density functions possess decaying tails. By incorporating the computational techniques we have developed in the past 3 years for efficiency, the probabilistic finite element methods are capable of handling large systems with many sources of uncertainties. Sample results for an elastic-plastic ten-bar structure and an elastic-plastic plane continuum with a circular hole subject to cyclic loadings with the yield stress on the random field are given.

Belytschko, Ted↗

NASA NTRS1994

A coronagraphic search for brown dwarfs around nearby stars

Brown dwarf companions have been searched for around stars within 10 pc of the Sun using the Johns-Hopkins University Adaptive Optics Coronagraph (AOC), a stellar coronagraph with an image stabilizer. The AOC covers the field around the target star with a minimum search radius of 1 sec .5 and a field of view of 1 arcmin sq. We have reached an unprecedented dynamic range of Delta m = 13 in our search for faint companions at I band. Comparison of our survey with other brown dwarf searches shows that the AOC technique is unique in its dynamic range while at the same time just as sensitive to brown dwarfs as the recent brown dwarf surveys. The present survey covered 24 target stars selected from the Gliese catalog. A total of 94 stars were detected in 16 fields. The low-latitude fields are completely dominated by background star contamination. Kolmogorov-Smirnov tests were carried out for a sample restricted to high latitudes and a sample with small angular separations. The high-latitude sample (b greater than or equal to 44 deg) appears to show spatial concentration toward target stars. The small separation sample (Delta Theta less than 20 sec) shows weaker dependence on Galactic coordinates than field stars. These statistical tests suggest that both the high-latitude sample and the small separation sample can include a substantial fraction of true companions. However, the nature of these putative companions is mysterious. They are too faint to be white dwarfs and too blue for brown dwarfs. Ignoring the signif icance of the statistical tests, we can reconcile most of the detections with distant main-sequence stars or white dwarfs except for a candidate next to GL 475. Given the small size of our sample, we conclude that considerably more targets need to be surveyed before a firm conclusion on the possibility of a new class of companions can be made.

Nakajima, T.↗

NASA NTRS2017

First Application of the Zeeman Technique to Remotely Measure Auroral Electrojet Intensity From Space

Using the O2 118 GHz spectral radiance measurements obtained by the Microwave Limb Sounder instrument on board the Aura spacecraft, we demonstrate that the Zeeman effect can be used to remotely measure the magnetic field perturbations produced by the auroral electrojet near the Hall current closure altitudes. Our derived current-induced magnetic field perturbations are found to be highly correlated with those coincidently obtained by ground magnetometers. These perturbations are also found to be linearly correlated with auroral electrojet strength. The statistically derived polar maps of our measured magnetic field perturbation reveal a spatial-temporal morphology consistent with that produced by the Hall current during substorms and storms. With today's technology, a constellation of compact, low-power, high spectral-resolution cubesats would have the capability to provide high precision and spatiotemporal magnetic field samplings needed for auroral electrojet measurements to gain insights into the spatiotemporal behavior of the auroral electrojet system.

spectral radiance measurements; Aur↗

NASA NTRS2020

Exploring Carbon Mineral Systems: Recent Advances in C Mineral Evolution, Mineral Ecology, and Network Analysis

Large and growing data resources on the spatial and temporal diversity and distribution of the more than 400 carbon-bearing mineral species reveal patterns of mineral evolution and ecology. Recent advances in analytical and visualization techniques leverage these data and are propelling mineralogy from a largely descriptive field into one of prediction within complex, integrated, multidimensional systems. These discoveries include: (1) systematic changes in the character of carbon minerals and their networks of coexisting species through deep time; (2) improved statistical predictions of the number and types of carbon minerals that occur on Earth but are yet to be discovered and described; and (3) a range of proposed and ongoing studies related to the quantification of network structures and trends, relation of mineral “natural kinds” to their genetic environments, prediction of the location of mineral species across the globe, examination of the tectonic drivers of mineralization through deep time, quantification of preservational and sampling bias in the mineralogical record, and characterization of feedback relationships between minerals and geochemical environments with microbial populations. These aspects of Earth’s carbon mineralogy underscore the complex coevolution of the geosphere and biosphere and highlight the possibility for scientific discovery in Earth and planetary systems.

Carbon↗