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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Electronic Characterization of Defects in Narrow Gap Semiconductors-Comparison of Electronic Energy Levels and Formation Energies in Mercury Cadmium Telluride, Mercury Zinc Telluride, and Mercury Zinc Selenide

We have used a Green's function technique to calculate the energy levels and formation energy of deep defects in the narrow gap semiconductors mercury cadmium telluride (MCT), mercury zinc telluride (MZT) and mercury zinc selenide (MZS). The formation energy is calculated from the difference between the total energy with an impurity cluster and the total energy for the perfect crystal. Substitutional (including antisite), interstitial (self and foreign), and vacancy deep defects are considered. Relaxation effects are calculated (with molecular dynamics). By use of a pseudopotential, we generalize the ideal vacancy model so as to be able to consider relaxation for vacancies. Different charge states are considered and the charged state energy shift (as computed by a modified Haldane-Anderson model) can be twice that due to relaxation. Different charged states for vacancies were not calculated to have much effect on the formation energy. For all cases we find deep defects in the energy gap only for cation site s-like orbitals or anion site p-like orbitals, and for the substitutional case only the latter are appreciably effected by relaxation. For most cases for MCT, MZT, MZS, we consider x (the concentration of Cd or Zn) in the range appropriate for a band gap of 0.1 eV. For defect energy levels, the absolute accuracy of our results is limited, but the precision is good, and hence chemical trends are accurately predicted. For the same reason, defect formation energies are more accurately predicted than energy level position. We attempt, in Appendix B, to calculate vacancy formation energies using relatively simple chemical bonding ideas due to Harrison. However, these results are only marginally accurate for estimating vacancy binding energies. Appendix C lists all written reports and publications produced for the grant. We include abstracts and a complete paper that summarizes our work which is not yet available.

Patterson, James D.↗
NASA NTRSDate not supplied

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential in mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail walking and US-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986 to 2022. Using data from Landsat 5 and 8, Sentinel-2, the National Agriculture Imagery Program, and PlanetScope, the team computed vegetation indices including the Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Modified Soil Adjusted Vegetation Index 2, Enhanced Vegetation Index, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on the vegetation indices and spectral bands before running k-means++ clustering and random forest classification algorithms. Between all datasets, we found the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use the end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants. The NPS’s collection of ground data for 2022–2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive spread over time.

Carson Schuetze↗
NASA NTRS1989

A Simple Algebraic Grid Adaptation Scheme with Applications to Two- and Three-dimensional Flow Problems

An algebraic adaptive grid scheme based on the concept of arc equidistribution is presented. The scheme locally adjusts the grid density based on gradients of selected flow variables from either finite difference or finite volume calculations. A user-prescribed grid stretching can be specified such that control of the grid spacing can be maintained in areas of known flowfield behavior. For example, the grid can be clustered near a wall for boundary layer resolution and made coarse near the outer boundary of an external flow. A grid smoothing technique is incorporated into the adaptive grid routine, which is found to be more robust and efficient than the weight function filtering technique employed by other researchers. Since the present algebraic scheme requires no iteration or solution of differential equations, the computer time needed for grid adaptation is trivial, making the scheme useful for three-dimensional flow problems. Applications to two- and three-dimensional flow problems show that a considerable improvement in flowfield resolution can be achieved by using the proposed adaptive grid scheme. Although the scheme was developed with steady flow in mind, it is a good candidate for unsteady flow computations because of its efficiency.

Hsu, Andrew T.↗
NASA NTRS1999

Parallel Finite Element Solution of 3D Rayleigh-Benard-Marangoni Flows

A domain decomposition strategy and parallel gradient-type iterative solution scheme have been developed and implemented for computation of complex 3D viscous flow problems involving heat transfer and surface tension effects. Details of the implementation issues are described together with associated performance and scalability studies. Representative Rayleigh-Benard and microgravity Marangoni flow calculations and performance results on the Cray T3D and T3E are presented. The work is currently being extended to tightly-coupled parallel "Beowulf-type" PC clusters and we present some preliminary performance results on this platform. We also describe progress on related work on hierarchic data extraction for visualization.

Carey, G. F.↗
NASA NTRS2002

Enabling Computational Nanotechnology through JavaGenes in a Cycle Scavenging Environment

A genetic algorithm procedure is developed and implemented for fitting parameters for many-body inter-atomic force field functions for simulating nanotechnology atomistic applications using portable Java on cycle-scavenged heterogeneous workstations. Given a physics based analytic functional form for the force field, correlated parameters in a multi-dimensional environment are typically chosen to fit properties given either by experiments and/or by higher accuracy quantum mechanical simulations. The implementation automates this tedious procedure using an evolutionary computing algorithm operating on hundreds of cycle-scavenged computers. As a proof of concept, we demonstrate the procedure for evaluating the Stillinger-Weber (S-W) potential by (a) reproducing the published parameters for Si using S-W energies in the fitness function, and (b) evolving a "new" set of parameters using semi-empirical tightbinding energies in the fitness function. The "new" parameters are significantly better suited for Si cluster energies and forces as compared to even the published S-W potential.

Globus, Al↗
NASA NTRS1981

Quantum chemical calculation of the equilibrium structures of small metal atom clusters

The application of ab initio quantum mechanical approaches in the study of metal atom clusters requires simplifying techniques that do not compromise the reliability of the calculations. Various aspects of the implementation of the effective core potential (ECP) technique for the removal of the metal atom core electrons from the calculation were examined. The ECP molecular integral formulae were modified to bring out the shell characteristics as a first step towards fulfilling the increasing need to speed up the computation of the ECP integrals. Work on the relationships among the derivatives of the molecular integrals that extends some of the techniques pioneered by Komornicki for the calculation of the gradients of the electronic energy was completed and a formulation of the ECP approach that quite naturally unifies the various state-of-the-art "shape- and Hamiltonian-consistent" techniques was discovered.

Kahn, L. R.↗
NASA NTRS2001

Validation of a High-Order Compact Code for Nonlinear Flows About Complex Geometric

The slides review computational requirements for nozzle exhaust flow and noise calculations and the current numerical method, validation of prefactored compact scheme on CAA benchmark problems, a curvilinear grid performance test of gust response of a Joukowski airfoil, airfoil surface RMS pressure distribution and far field noise radiation results for Joukowski airfoil in a vortical gust, boundary distance study for Joukowski airfoil problem, and performance of ICOMP parallel Macintosh cluster.

Hixon, Ray↗
NASA NTRS1982

GRID3C: Computer program for generation of C type multilevel, three dimensional and boundary conforming periodic grids

A fast computer program, GRID3C, was developed for accurately generating periodic, boundary conforming, three dimensional, consecutively refined computational grids applicable to realistic axial turbomachinery geometries. The method is based on using two functions to generate two dimensional grids on a number of coaxial axisymmetric surfaces positioned between the centerbody and the outer radial boundary. These boundary fitted grids are of the C type and are characterized by quasi-orthogonality and geometric periodicity. The built in nonorthogonal coordinate stretchings and shearings cause the grid clustering in the regions of interest. The stretching parameters are part of the input to GRID3C. In its present version GRID3C can generate and store a maximum of four consecutively refined three dimensional grids. The output grid coordinates can be calculated either in the Cartesian or in the cylindrical coordinate system.

Dulikravich, D. S.↗
NASA NTRS1994

AutoClass: A Bayesian Approach to Classification

We describe a Bayesian approach to the untutored discovery of classes in a set of cases, sometimes called finite mixture separation or clustering. The main difference between clustering and our approach is that we search for the "best" set of class descriptions rather than grouping the cases themselves. We describe our classes in terms of a probability distribution or density function, and the locally maximal posterior probability valued function parameters. We rate our classifications with an approximate joint probability of the data and functional form, marginalizing over the parameters. Approximation is necessitated by the computational complexity of the joint probability. Thus, we marginalize w.r.t. local maxima in the parameter space. We discuss the rationale behind our approach to classification. We give the mathematical development for the basic mixture model and describe the approximations needed for computational tractability. We instantiate the basic model with the discrete Dirichlet distribution and multivariant Gaussian density likelihoods. Then we show some results for both constructed and actual data.

Stutz, John↗
NASA NTRS2004

On Efficient Multigrid Methods for Materials Processing Flows with Small Particles

Multiscale modeling of materials requires simulations of multiple levels of structural hierarchy. The computational efficiency of numerical methods becomes a critical factor for simulating large physical systems with highly desperate length scales. Multigrid methods are known for their superior efficiency in representing/resolving different levels of physical details. The efficiency is achieved by employing interactively different discretizations on different scales (grids). To assist optimization of manufacturing conditions for materials processing with numerous particles (e.g., dispersion of particles, controlling flow viscosity and clusters), a new multigrid algorithm has been developed for a case of multiscale modeling of flows with small particles that have various length scales. The optimal efficiency of the algorithm is crucial for accurate predictions of the effect of processing conditions (e.g., pressure and velocity gradients) on the local flow fields that control the formation of various microstructures or clusters.

Thomas, James↗
NASA NTRS1976

A computer analysis of ERTS data of the Lake Gregory area of South Australia with particular emphasis on its role in terrain classification for engineering

A digital computer and multivariate statistical techniques were used to analyze 4-band multispectral data. A representation of the original data for each of the four bands allows a certain degree of terrain interpretation; however, variations in appearance of sites within and between bands, without additional criteria for deciding which representation should be preferred, create difficulties for classification. Investigation of the video data groups produced by principal components analysis and cluster analysis techniques shows that effective correlations with classifications of terrain produced by conventional methods could be carried out. The analyses also highlighted underlying relationships between the various elements. The approach used allows large areas (185 cm by 185 cm) to be classified into fundamental units within a matter of hours and can be applied to those parts of the Earth where facilities for conventional studies are poor or lacking.

Lodwick, G. D.↗
NASA NTRS2000

Cosmic Rays and Their Radiative Processes in Numerical Cosmology

A cosmological hydrodynamic code is described, which includes a routine to compute cosmic ray acceleration and transport in a simplified way. The routine was designed to follow explicitly diffusive, acceleration at shocks, and second-order Fermi acceleration and adiabatic loss in smooth flows. Synchrotron cooling of the electron population can also be followed. The updated code is intended to be used to study the properties of nonthermal synchrotron emission and inverse Compton scattering from electron cosmic rays in clusters of galaxies, in addition to the properties of thermal bremsstrahlung emission from hot gas. The results of a test simulation using a grid of 128 (exp 3) cells are presented, where cosmic rays and magnetic field have been treated passively and synchrotron cooling of cosmic ray electrons has not been included.

Ryu, Dongsu↗
NASA NTRS1995

Effect of Stacking Faults on the X-Ray Diffraction Profiles of Beta-SiC Powders

X-ray diffraction patterns or beta-SiC (3C or the cubic polytype or sic) powders often exhibit an additional peak at d = 0.266 nm, high background intensity around the (111) peak, and relative intensities for peaks which differ from those predicted from the crystal structure. Computer simulations were used to show that all these features are due to stacking faults in the powders and not due to the presence of other polytypes in the powders. Such simulations allow diffraction patterns to be generated for different types, frequencies, and spatial distribution or faults. Comparison of the simulation results to the XRD data indicates that the B-SiC particles consist either of heavily faulted clusters distributed irregularly between regions that have only occasional faults or twins, or the powders consist of two types of particles with different populations of faults: those with a high density of faults and those with only twins or occasional faults. Additional information is necessary to determine which description is correct. However, the simulation results can be used to rule out certain fault configurations.

Pujar, Vijay V.↗
NASA NTRS2005

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Iverson, David L.↗
NASA NTRS2008

Software for Verifying Image-Correlation Tie Points

A computer program enables assessment of the quality of tie points in the image-correlation processes of the software described in the immediately preceding article. Tie points are computed in mappings between corresponding pixels in the left and right images of a stereoscopic pair. The mappings are sometimes not perfect because image data can be noisy and parallax can cause some points to appear in one image but not the other. The present computer program relies on the availability of a left- right correlation map in addition to the usual right left correlation map. The additional map must be generated, which doubles the processing time. Such increased time can now be afforded in the data-processing pipeline, since the time for map generation is now reduced from about 60 to 3 minutes by the parallelization discussed in the previous article. Parallel cluster processing time, therefore, enabled this better science result. The first mapping is typically from a point (denoted by coordinates x,y) in the left image to a point (x',y') in the right image. The second mapping is from (x',y') in the right image to some point (x",y") in the left image. If (x,y) and(x",y") are identical, then the mapping is considered perfect. The perfect-match criterion can be relaxed by introducing an error window that admits of round-off error and a small amount of noise. The mapping procedure can be repeated until all points in each image not connected to points in the other image are eliminated, so that what remains are verified correlation data.

Klimeck, Gerhard↗
NASA NTRS2004

Knowledge Driven Image Mining with Mixture Density Mercer Kernels

This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels; which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper, we present the theory of Mercer Kernels, describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

Srivastava, Ashok N.↗
NASA NTRS2004

Knowledge Driven Image Mining with Mixture Density Mercer Kernals

This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper we present the theory of Mercer Kernels; describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

Srivastava, Ashok N.↗
NASA NTRS1996

Kinetics of Diffusional Droplet Growth in a Liquid/Liquid Two-Phase System

We address the problem of diffusional interactions in a finite sized cluster of spherical particles for volume fractions, V(sub v) in the range 0-0.01. We determined the quasi-static monopole diffusion solution for n particles distributed at random in a continuous matrix. A global mass conservation condition is employed, obviating the need for any external boundary condition. The numerical results provide the instantaneous (snapshot) growth or shrinkage rate of each particle, precluding the need for extensive time-dependent computations. The close connection between these snapshot results and the coarsegrained kinetic constants are discussed. A square-root dependence of the deviations of the rate constants from their zero volume fraction value is found for the higher V(sub v) investigated. This behavior is consistent with predictions from diffusion Debye-Huckel screening theory. By contrast, a cube-root dependence, reported in earlier numerical studies, is found for the lower V(sub v) investigated. The roll-over region of the volume fraction where the two asymptotics merge depends on the number of particles, n, alone. A theoretical estimate for the roll-over point predicts that the corresponding V(sub v) varies as n(sup -2), in good agreement with the numerical results.

Glicksman, M. E.↗