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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 505 records · Page 28
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NASA NTRS2005

Glucose determination in human aqueous humor with Raman spectroscopy

It has been suggested that spectroscopic analysis of the aqueous humor of the eye could be used to indirectly predict blood glucose levels in diabetics noninvasively. We have been investigating this potential using Raman spectroscopy in combination with partial least squares (PLS) analysis. We have determined that glucose at clinically relevant concentrations can be accurately predicted in human aqueous humor in vitro using a PLS model based on artificial aqueous humor. We have further determined that with proper instrument design, the light energy necessary to achieve clinically acceptable prediction of glucose does not damage the retinas of rabbits and can be delivered at powers below internationally acceptable safety limits. Herein we summarize our current results and address our strategies to improve instrument design. 2005 Society of Photo-Optical Instrumentation Engineers.

Spectrum Analysis, Raman/methods↗
NASA NTRS2006

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used to produce simulated MODIS and VIIRS products. Hyperion-derived MODIS data will be compared with near-coincident MODIS collects to validate both spectral and spatial synthesis, which will ascertain the accuracy of converting from MODIS to VIIRS. MODIS-derived VIIRS data is needed for global coverage and for the generation of time series for regional and global investigations. These types of simulations will have errors associated with aliasing for some scene types. This study will help quantify these errors and will identify cases where high-quality, MODIS-derived VIIRS data will be available.

Ross, Kenton W.↗
NASA NTRS2007

Preliminary Evaluation of an Aviation Safety Thesaurus' Utility for Enhancing Automated Processing of Incident Reports

This document presents a preliminary evaluation the utility of the FAA Safety Analytics Thesaurus (SAT) utility in enhancing automated document processing applications under development at NASA Ames Research Center (ARC). Current development efforts at ARC are described, including overviews of the statistical machine learning techniques that have been investigated. An analysis of opportunities for applying thesaurus knowledge to improving algorithm performance is then presented.

Barrientos, Francesca↗
NASA NTRS2015

Polarized Bidirectional Reflectance of Optically Thick Sparse Particulate Layers: an Efficient Numerically Exact Radiative-Transfer Solution

We describe a simple yet efficient numerical algorithm for computing polarized bidirectional reflectance of an optically thick (semi-infinite), macroscopically flat layer composed of statistically isotropic and mirror symmetric random particles. The spatial distribution of the particles is assumed to be sparse, random, and statistically uniform. The 44 Stokes reflection matrix is calculated by iterating the Ambartsumian's vector nonlinear integral equation. The result is a numerically exact solution of the vector radiative transfer equation and as such fully satisfies the energy conservation law and the fundamental reciprocity relation. Since this technique bypasses the computation of the internal radiation field, it is very fast and highly accurate. The FORTRAN implementation of the technique is publicly available on the World Wide Web at http://www.giss.nasa.gov/staff/ mmishchenko/brf. It can be combined with several existing computer programs providing the requisite single-scattering properties of spherical or morphologically complex particles and applied to a wide range of optical characterization problems. Benchmark results obtained with this program can be used for testing alternative solvers of the vector radiative transfer equation.

radiative transfer↗
NASA NTRS2016

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

anomaly detection↗
NASA NTRS2019

The Cumulus and Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD)

Low clouds continue to contribute greatly to the uncertainty in cloud feedback estimates. Depending on whether a region is dominated by cumulus (Cu) or stratocumulus (Sc) clouds, the interannual low-cloud feedback is somewhat different in both spaceborne and large-eddy simulation studies. Therefore, simulating the correct amount and variation of the Cu and Sc cloud distributions could be crucial to predict future cloud feedbacks. Here we document spatial distributions and profiles of Sc and Cu clouds derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat measurements. For this purpose, we create a new dataset called the Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD), which identifies Sc, broken Sc, Cu under Sc, Cu with stratiform outflow and Cu. To separate the Cu from Sc, we design an original method based on the cloud height, horizontal extent, vertical variability and horizontal continuity, which is separately applied to both CALIPSO and combined CloudSat–CALIPSO observations. First, the choice of parameters used in the discrimination algorithm is investigated and validated in selected Cu, Sc and Sc–Cu transition case studies. Then, the global statistics are compared against those from existing passive- and active-sensor satellite observations. Our results indicate that the cloud optical thickness – as used in passive-sensor observations – is not a sufficient parameter to discriminate Cu from Sc clouds, in agreement with previous literature. Using clustering-derived datasets shows better results although one cannot completely separate cloud types with such an approach. On the contrary, classifying Cu and Sc clouds and the transition between them based on their geometrical shape and spatial heterogeneity leads to spatial distributions consistent with prior knowledge of these clouds, from ground-based, ship-based and field campaigns. Furthermore, we show that our method improves existing Sc–Cu classifications by using additional information on cloud height and vertical cloud fraction variation. Finally, the CASCCAD datasets provide a basis to evaluate shallow convection and stratocumulus clouds on a global scale in climate models and potentially improve our understanding of low-level cloud feedbacks. The CASCCAD dataset (Cesana, 2019, https://doi.org/10.5281/zenodo.2667637) is available on the Goddard Institute for Space Studies (GISS) website at https://data.giss.nasa.gov/clouds/casccad/ (last access: 5 November 2019) and on the zenodo website at https://zenodo.org/record/2667637 (last access: 5 November 2019).

Cesana, Gregory V.↗
NASA NTRS2011

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Platnick, Steven E.↗
NASA NTRS2015

Parameter Estimation for Compact Binaries with Ground-Based Gravitational-Wave Observations Using the LALInference

The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star (BNS), a neutron star - black hole binary (NSBH) and a binary black hole (BBH), where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence (CBC) parameter space.

gravitational wave↗
NASA NTRSDate not supplied

A Universal Algorithm for the Detection of Bi-directional Gage Output Characteristics

A universal algorithm was developed that may be used to assess the bi-directional characteristics of the gage outputs of a wind tunnel strain-gage balance. The algorithm assumes that balance loads and gage outputs are described in the design format of the balance. It can also be applied to balance calibration data that is processed by using either the Iterative Method or the Non-Iterative Method. The algorithm uses an estimate of the bi-directional part of a gage output at load capacity as input. In addition, the statistical significance of the principle absolute value term in the regression model of either the gage output or the related primary load component is determined. A gage output is assumed to be bi-directional if two conditions are fulfilled: the bi-directional part of the output at load capacity exceeds 0.5 percent of the maximum output at load capacity; the p-value of the principle absolute value term of the regression model of the balance data is less than the threshold of 0.001. Data from the calibration of two six-component force balances and one five-component semi-span balance are used to illustrate the application of the universal detection algorithm.

wind tunnel test↗
NASA NTRS1999

Random Dopant Induced Threshold Voltage Lowering and Fluctuations in Sub 50 nm MOSFETs: a Statistical 3D 'Atomistic' Simulation Study

A 3D 'atomistic' simulation study of random dopant induced threshold voltage fluctuations and lowering in sub 50 nm MOSFETs is presented. The attention is focused mainly on devices with 30 nm effective channel length which represent the expected level of scaling at the end of the Silicon Roadmap. An efficient algorithm, based on a single 3D ap solution of the Poisson equation and a simplified current continuity equation, is used in the simulations. Large samples of microscopically different devices (typically 200) arc used in order to obtain statistically reliable results. The influence of different aspects of the conventional MOSFET design on the threshold voltage fluctuations and lowering are investigated. Results for fluctuation resistant device architectures based on low-doped epitaxial channel MOSFETs are also presented.

Asenov, Asen↗
NASA NTRSDate not supplied

Algorithmic Classification of Raman Spectra Biosignatures: Improving Life Detection Confidence

“Agnostic” biosignatures – indicators of life (or the absence of life), independent of a particular biochemistry – are increasingly considered a high standard for life detection. The Ladder of Life Detection (2018) called for investigating how combinations of independent and different potential biosignatures affect confidence. To address this gap, statistical classification of elemental abundances, isotopic fractionation, and reflectance spectroscopy (VNIR) has been implemented. Raman spectroscopy, highly desirable due to its wide availability, has the potential to improve this predictive power. This work implemented biosignature classification algorithms on Raman data alone, in preparation for combination with the other data types. Raman spectroscopy data was collected from published databases and papers as part of a manually curated dataset of “indicative” and “non-indicative of life” samples. These currently include 61 non-indicative samples (meteorites, magnetite); 3 indicative living samples (bacteria); 20 indicative non-living samples (chalk, bone); and 12 indicative mixed (with non-indicative material) samples (soil, microbial mats). Laboratory work is ongoing to characterize additional samples, particularly a greater breadth of mixed systems. Spectra were interpolated, filtered with the Savitzsky-Golay filter, and de-noised. For a preliminary examination, agnostic features were manually extracted including mean intensity, number of peaks, and mean peak width. Different peak prominences and filtering polynomials were used to refine features. Classification algorithms were implemented: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), random forest (RF), Gaussian naïve bayes (GNB). Lastly, Monte Carlo simulations on 1,000 50%-train-test-splits were used to validate classification performance and feature significance. The preliminary feature set achieved its highest AUC of 0.52 with LR, with no strongly discriminatory features. Work to improve feature extraction, such as through deep learning with back propagation, is planned. In future work, the Raman data will be combined with the other data types, and potentially new data types such as enantiomeric excess. This project was partially supported through the NASA Ames Project EXcellence (APEX) incubator program.

Astrobiology↗
NASA NTRS1989

A correction algorithm for particle size distribution measurements made with the forward-scattering spectrometer probe

A correction algorithm for evaluating the particle size distribution measurements of atmospheric aerosols obtained with a forward-scattering spectrometer probe (FSSP) is examined. A model based on Poisson statistics is employed to calculate the average diameter and rms width of the particle size distribution. The dead time and coincidence errors in the measured number density are estimated. The model generated data are compared with a Monte Carlo simulation of the FSSP operation. It is observed that the correlation between the actual and measured size distribution is nonlinear. It is noted that the algorithm permits more accurate calculation of the average diameter and rms width of the distribution compared to uncorrected measured quantities.

Lock, James A.↗
NASA NTRS1977

Design of redundant systems

Algorithmic approach is useful for analysis of systems with noisy inputs and when outputs are required in terms of statistical quantities and probabilities of signal excursions beyond desired levels. Procedure can be used with circuits, chemical processes, material design, and other systems with known transfer functions and parameter tolerances.

Doty, L. F.↗
NASA NTRS1978

A study of digital holographic filters generation. Phase 2: Digital data communication system, volume 1

An empirical study of the performance of the Viterbi decoders in bursty channels was carried out and an improved algebraic decoder for nonsystematic codes was developed. The hybrid algorithm was simulated for the (2,1), k = 7 code on a computer using 20 channels having various error statistics, ranging from pure random error to pure bursty channels. The hybrid system outperformed both the algebraic and the Viterbi decoders in every case, except the 1% random error channel where the Viterbi decoder had one bit less decoding error.

Ingels, F. M.↗
NASA NTRS1980

Radar image enhancement and simulation as an aid to interpretation and training

Greatly increased activity in the field of radar image applications in the coming years demands that techniques of radar image analysis, enhancement, and simulation be developed now. Since the statistical nature of radar imagery differs from that of photographic imagery, one finds that the required digital image processing algorithms (e.g., for improved viewing and feature extraction) differ from those currently existing. This paper addresses these problems and discusses work at the Remote Sensing Laboratory in image simulation and processing, especially for systems comparable to the formerly operational SEASAT synthetic aperture radar.

Frost, V. S.↗
NASA NTRS1985

Grid-free simulation of diffusion using random walk methods

The simulation of the diffusion of a continuum field by the random walk (RW) displacement of a set of particles is considered. Elements of the gradients of the diffusive concentration are transported by computational particles. It is demonstrated that, by the use of concentration gradients in the RW process, statistical errors are reduced and each realization of the numerical solution is a representation of the exact solution. The algorithm is grid-free, and the computational elements move to follow the gradients; hence, the algorithm is self-adaptive, and uniform resolution is achieved for all times.

Ghoniem, A. F.↗
NASA NTRS1986

New aspects of the equilibrium pole tide

A new spherical harmonic algorithm is developed for the calculation of the loading and self-gravitating equilibrium pole tide. Based on a suggestion of Dahlen (1976), this approach minimizes the distortions in tide height caused by an incomplete representation of the ocean function. With slight modification this approach easily could be used to compute self-gravitating and loading lunisolar tides as well. Using the algorithm, the static pole tide is compared with tide observations at a variety of locations around the world, and statistically significant evidence for pole tide enhancements is found in midocean as well as the shallow seas. Also included is a reinvestigation of the effect of the static tide on the Chandler-wobble period. The difference between the wobble period of an oceanless elastic earth with a fluid core (Smith and Dahlen, 1981) and the period of an earth minus static oceans yields a 7.4-day discrepancy. It is concluded from tide observations that much of the discrepancy can probably be accounted for by nonequilibrium pole-tide behavior in the deep oceans.

Dickman, S. R.↗
NASA NTRS1987

Turbulence control on airborne laser platform

An avctive flow control device to generate large-scale, periodic structures in a turbulent shear flow is developed. Together with adaptive optics, the device may be used on airborne laser platforms to reduce or eliminate optical distortion caused by the turbulence in the aircraft's boundary layer. A flat plate towed in a water channel is used as a test bed. A cyclic jet issuing from a spanwise slot is used to collect the turbulent boundary layer for a finite time during its 'on' period. When the jet is turned 'off', all of the turbulent fluid is released instantaneously in one large eddy that convects downstream. Flow visualization and hot-film probe measurements are used together with pattern recognition algorithms to demonstrate the viability of the flow control method. The instantaneous velocity signal is used to compute important statistical quantities of the random velocity field, such as the mean, the root-mean-square, the spectral distribution, and the probability density function. When optimized for a given boundary layer, the cyclic jet produces periodic structures that are qualitatively similar to the random, naturally occurring ones. These structures seem to trigger the onset of bursting events near the wall. Thus, the present device generates periodic structures in both the outer and inner regions of a turbulent boundary layer.

Gad-El-hak, Mohamed↗