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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Operations analysis (study 2.1): Program manual and users guide for the LOVES computer code

Information is provided necessary to use the LOVES Computer Program in its existing state, or to modify the program to include studies not properly handled by the basic model. The Users Guide defines the basic elements assembled together to form the model for servicing satellites in orbit. As the program is a simulation, the method of attack is to disassemble the problem into a sequence of events, each occurring instantaneously and each creating one or more other events in the future. The main driving force of the simulation is the deterministic launch schedule of satellites and the subsequent failure of the various modules which make up the satellites. The LOVES Computer Program uses a random number generator to simulate the failure of module elements and therefore operates over a long span of time typically 10 to 15 years. The sequence of events is varied by making several runs in succession with different random numbers resulting in a Monte Carlo technique to determine statistical parameters of minimum value, average value, and maximum value.

Wray, S. T., Jr.↗
NASA NTRS1976

On the optimal minimum order observer-based compensator and the limited state variable feedback controller

Four design problems are considered: two on the optimal minimum order observer-based compensator design and two on the optimal limited state variable feedback controller. The problem of designing an optimal discrete time linear time-invariant observer-based compensator for the regulation of an n dimensional linear discrete time time-invariant plant with m independent outputs is considered. This is a stochastic design problem to the extent that the initial plant state is assumed to be a random vector with known first and second order statistics. The compensator parameters are obtained by minimizing the expectation, with respect to the initial conditions, of the standard cost, quadratic in the state and control vectors with the inclusion of cross terms.

Llorens-Ortiz, B.↗
NASA NTRS1980

Second moments of optical degradation due to a thin turbulent layer

The effect of thin turbulent layers, including boundary layers and shear layers, on light propagation is examined from a theoretical point of view. In particular, a mathematical model is developed to describe the interaction between the aerodynamic or, more precisely, the density fluctuations and the electromagnetic field. It is assumed that the turbulence induces a normally distributed phase aberration which is a homogeneous random function in the plane of the aperture. Hypotheses concerning the density fluctuations in the layer sufficient to guarantee such a phase aberration are exhibited. The optical degradation is described in terms of the optical transfer function (OTF) and the Strehl ratio (I/I O ) which are random. Expressions for the first and second moments of these two parameters are developed from the definitions. Asymptotic ("large" aperture) approximations to these expressions are derived and discussed. Finally, the exact and approximate results are compared for several "typical" values of the ratios of aperture diameter to scale of density fluctuations and rms phase aberration to wave length respectively.

W J Steinmetz↗
NASA NTRS1986

Fluctuation and rotation in diffusion-influenced monomolecular reactions

Models of partially absorbing boundaries for calculating diffusion-influenced chemical reactions are examined analytically. The limitations of diffusion-equation and random-walk models are indicated; the presence of an ambiguous length parameter in a standard radiation-boundary-condition (RBC) model is demonstrated; the RBC model for a boundary with oscillation (at a rate much faster than the rate of thermal collisions) between absorbing and nonabsorbing states is considered; an alternative stochastically switching absorber (SSA) model is introduced and shown to be physically consistent; the equivalence of one-dimensional RBC and SSA models under some conditions is shown; one time passage is calculated for an axially symmetric three-dimensional SSA model with anisotropic absorption; and the analogy between rotation and stochastic switching is explored.

Bashford, Donald↗
NASA NTRS1989

Coverage modeling for dependability analysis of fault-tolerant systems

Several different models for predicting coverage in a fault-tolerant system, including models for permanent, intermittent, and transient errors, are discussed. Markov, semi-Markov, nonhomogeneous Markov, and extended stochastic Petri net models for computing coverage are developed. Two types of events that interfere with recovery are examined; and methods for modeling such events, whether they are deterministic or random, are given. The sensitivity of system reliability/availability to the coverage parameter and the sensitivity of the coverage parameter to various error-handling strategies are investigated. It is found that a policy of attempting transient recovery upon detection of an error can actually increase the unreliability of the system. This result is true if the error detectability is not nearly perfect, so that the risk of producing an undetectable error is greater than the benefit gained by not discarding the component.

Dugan, Joanne Bechta↗
NASA NTRS1992

More About Gravitational Bumps And Repeating Orbits

Improved algorithm reduces computation needed to estimate dynamics affecting trajectory of satellite in orbit around Earth with approximately repeating ground track. Underlying concepts presented in "Computing Gravitational Bumps From Repeating-Orbit Data", (NPO-17925). Satellite presumed to undergo same gravitational perturbation upon each near-repetition. Tracking data from multiple nearly repeating arcs collected into segments called "bins" and processed together to reduce effects of random errors, and thereby obtain more-accurate estimates of dynamical parameters. Bumps in gravitational field of Earth estimated with less computation.

Wu, Jiun-Tsong↗
NASA NTRS1993

Coherent Doppler lidar signal covariance including wind shear and wind turbulence

The performance of coherent Doppler lidar is determined by the statistics of the coherent Doppler signal. The derivation and calculation of the covariance of the Doppler lidar signal is presented for random atmospheric wind fields with wind shear. The random component is described by a Kolmogorov turbulence spectrum. The signal parameters are clarified for a general coherent Doppler lidar system. There are two distinct physical regimes: one where the transmitted pulse determines the signal statistics and the other where the wind field dominates the signal statistics. The Doppler shift of the signal is identified in terms of the wind field and system parameters.

Frehlich, R. G.↗
NASA NTRS1992

SIMBAD quality-control

The astronomical database SIMBAD developed at the Centre de donnees astronomiques de Strasbourg presently contains 760,000 objects (stellar and non-stellar). It has the unique characteristic of being structured specifically for astronomical objects. All types of heterogeneous data (bibliographic references, measurements, and sets of identification) are connected with each object. The attributes that define quality of the database include the following. Reliability: cross-identification should not rely upon just exact values object coordinates. It also means that information attached to one simple object should be consistent. The existing data must be controlled in order to start with a reliable base and to cross-identify new data assuring the quality as data grows. Exhaustivity: delays between publication of new informations and their inclusion in the database should be as short as possible. The integrity of the database has to be maintained as data accumulates. Taking the amount of data into consideration and the rate of new data production, it is necessary to use automatic methods. One of the possibilities is to use multivariate data analysis. The factor-space is a n-dimensional relevancy space which is described by the n-axes representing a set of n subject matter headings; the words and phrases can be used to scale the axes and the documents are then a vector average of the terms within them. The application reported herein is based on the NASA-STI bibliographical database. The selected data concern astronomy, astrophysics, and space radiation (102,963 references from 1975 to 1991 included 8070 keywords). The F-space is built from this bibliographical data. By comparing the F-space position obtained from the NASA-STI keywords with the F-space position obtained from the SIMBAD references, the authors will be able to show whether it is possible to retrieve information with a restricted set of words only. If the comparison is valid, this will be a way to enter bibliographic information in the SIMBAD quality control process. Furthermore, it is possible to connect the physical measurements of stars from SIMBAD to literature concerning these stars from the NASA-STI abstracts. The physical properties of stars (e.g. UBV colors) are not randomly distributed. Stars are distributed among different clusters in a physical parameter space. The authors will show that there are some relations between this classification and the literature concerning these objects clusters in a factor space. They will investigate the nature of the relationship between the SIMBAD measurements and the bibliography. These would be new relationships that are not pre-established by an astronomer. In addition, the bibliography could be neutral information that can be used in combination with the measured parameters.

Lesteven, Soizick↗
NASA NTRS2005

Measurement and Prediction of the Thermomechanical Response of Shape Memory Alloy Hybrid Composite Beams

Previous work at NASA Langley Research Center (LaRC) involved fabrication and testing of composite beams with embedded, pre-strained shape memory alloy (SMA) ribbons within the beam structures. That study also provided comparison of experimental results with numerical predictions from a research code making use of a new thermoelastic model for shape memory alloy hybrid composite (SMAHC) structures. The previous work showed qualitative validation of the numerical model. However, deficiencies in the experimental-numerical correlation were noted and hypotheses for the discrepancies were given for further investigation. The goal of this work is to refine the experimental measurement and numerical modeling approaches in order to better understand the discrepancies, improve the correlation between prediction and measurement, and provide rigorous quantitative validation of the numerical analysis/design tool. The experimental investigation is refined by a more thorough test procedure and incorporation of higher fidelity measurements such as infrared thermography and projection moire interferometry. The numerical results are produced by a recently commercialized version of the constitutive model as implemented in ABAQUS and are refined by incorporation of additional measured parameters such as geometric imperfection. Thermal buckling, post-buckling, and random responses to thermal and inertial (base acceleration) loads are studied. The results demonstrate the effectiveness of SMAHC structures in controlling static and dynamic responses by adaptive stiffening. Excellent agreement is achieved between the predicted and measured results of the static and dynamic thermomechanical response, thereby providing quantitative validation of the numerical tool.

Davis, Brian↗
NASA NTRS2022

Regression Bias in using Solar Wind Measurements

Simultaneous solar wind measurements from the solar wind monitors, WIND and ACE, differ due to the spatial and temporal structure of the solar wind. Correlation studies that use these measurements as input may infer an incorrect correlation due to uncertainties arising from this spatial and temporal structure, especially at extreme and rare solar wind values. In particular, regression analysis will lead to a regression function whose slope is biased towards the mean value of the measurement parameter. This article demonstrates this regression bias by comparing simultaneous ACE and WIND solar wind measurements. A non-linear regression analysis between them leads to a perception of underestimation of extreme values of one measurement on average over the other. Using numerical experiments, we show that popular regression analysis techniques such as linear least-squares, orthogonal least-squares, and non-linear regression are not immune to this bias. Hence while using solar wind parameters as an independent variable in a correlation or regression analysis, random uncertainty in the independent variable can create unintended biases in the response of the dependent variable. More generally, the regression to the mean effect can impact both event-based, statistical studies of magnetospheric response to solar wind forcing.

magnetosphere↗
NASA NTRS2012

Validation of Slosh Model Parameters and Anti-Slosh Baffle Designs of Propellant Tanks by Using Lateral Slosh Testing

The slosh dynamics of propellant tanks can be represented by an equivalent pendulum-mass mechanical model. The parameters of this equivalent model, identified as slosh model parameters, are slosh mass, slosh mass center of gravity, slosh frequency, and smooth-wall damping. They can be obtained by both analysis and testing for discrete fill heights. Anti-slosh baffles are usually needed in propellant tanks to control the movement of the fluid inside the tank. Lateral slosh testing, involving both random testing and free-decay testing, are performed to validate the slosh model parameters and the damping added to the fluid by the anti-slosh baffles. Traditional modal analysis procedures are used to extract the parameters from the experimental data. Test setup of sub-scale test articles of cylindrical and spherical shapes will be described. A comparison between experimental results and analysis will be presented.

Perez, Jose G.↗
DOE OSTI2024

Probabilistic and maximum entropy modeling of chemical reaction systems: Characteristics and comparisons to mass action kinetic models

We demonstrate and characterize a first-principles approach to modeling the mass action dynamics of metabolism. Starting from a basic definition of entropy expressed as a multinomial probability density using Boltzmann probabilities with standard chemical potentials, we derive and compare the free energy dissipation and the entropy production rates. We express the relation between entropy production and the chemical master equation for modeling metabolism, which unifies chemical kinetics and chemical thermodynamics. Because prediction uncertainty with respect to parameter variability is frequently a concern with mass action models utilizing rate constants, we compare and contrast the maximum entropy model, which has its own set of rate parameters, to a population of standard mass action models in which the rate constants are randomly chosen. We show that a maximum entropy model is characterized by a high probability of free energy dissipation rate and likewise entropy production rate, relative to other models. We then characterize the variability of the maximum entropy model predictions with respect to uncertainties in parameters (standard free energies of formation) and with respect to ionic strengths typically found in a cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

TOPEX orbit determination and gravity recovery using Global Positioning System data from repeat orbits

A covariance analysis is presented for satellite tracking and gravity recovery with a differential Global Positioning System-based technique to be demonstrated on TOPEX in the early 1990s. The technique employs data from an ensemble of repeat ground tracks to recover a unique satellite epoch state for each track and a set of invariant positional parameters common to all tracks. The positional parameters represent the effect of mismodeled gravitational field on the satellite orbit. At an altitude of 1336 km, where gravity modeling is the dominant systematic error, averaging of random error over many arcs and adjustment of the gravity model reduce the final satellite position error. The positional parameters can then be used to produce a refined global gravity model. The analysis indicates that errors ranging from 5 to 8 cm in TOPEX altitude and 0.05 to 0.2 mGal for the gravity field can be achieved, depending on the number of repeat arcs used.

Wu, Jiun-Tsong↗
NASA NTRS1975

A random search algorithm for laboratory computers

The small laboratory computer is ideal for experimental control and data acquisition. Postexperimental data processing is often performed on large computers because of the availability of sophisticated programs, but costs and data compatibility are negative factors. Parameter optimization can be accomplished on the small computer, offering ease of programming, data compatibility, and low cost. A previously proposed random-search algorithm ('random creep') was found to be very slow in convergence. A method is proposed (the 'random leap' algorithm) which starts in a global search mode and automatically adjusts step size to speed convergence. A FORTRAN executive program for the random-leap algorithm is presented which calls a user-supplied function subroutine. An example of a function subroutine is given which calculates maximum-likelihood estimates of receiver operating-characteristic parameters from binary response data. Other applications in parameter estimation, generalized least squares, and matrix inversion are discussed.

Curry, R. E.↗
NASA NTRS2010

Scaled CMOS Technology Reliability Users Guide

The desire to assess the reliability of emerging scaled microelectronics technologies through faster reliability trials and more accurate acceleration models is the precursor for further research and experimentation in this relevant field. The effect of semiconductor scaling on microelectronics product reliability is an important aspect to the high reliability application user. From the perspective of a customer or user, who in many cases must deal with very limited, if any, manufacturer's reliability data to assess the product for a highly-reliable application, product-level testing is critical in the characterization and reliability assessment of advanced nanometer semiconductor scaling effects on microelectronics reliability. A methodology on how to accomplish this and techniques for deriving the expected product-level reliability on commercial memory products are provided.Competing mechanism theory and the multiple failure mechanism model are applied to the experimental results of scaled SDRAM products. Accelerated stress testing at multiple conditions is applied at the product level of several scaled memory products to assess the performance degradation and product reliability. Acceleration models are derived for each case. For several scaled SDRAM products, retention time degradation is studied and two distinct soft error populations are observed with each technology generation: early breakdown, characterized by randomly distributed weak bits with Weibull slope (beta)=1, and a main population breakdown with an increasing failure rate. Retention time soft error rates are calculated and a multiple failure mechanism acceleration model with parameters is derived for each technology. Defect densities are calculated and reflect a decreasing trend in the percentage of random defective bits for each successive product generation. A normalized soft error failure rate of the memory data retention time in FIT/Gb and FIT/cm2 for several scaled SDRAM generations is presented revealing a power relationship. General models describing the soft error rates across scaled product generations are presented. The analysis methodology may be applied to other scaled microelectronic products and their key parameters.

Microelectronics Reliability↗
NASA NTRS1993

Application of the target decomposition theorem to a polarimetric random media model

With advances in polarimetric radar measurements of land surfaces, the need for understanding the underlying scattering mechanisms and dominant target features has become the focus of many studies. In particular, the maximum use of the polarimetric information to identify and/or separate parameters related to the surface features such as vegetation thickness, structure, water content, and soil surface characteristics will enhance the possibility of using polarimetric radars for monitoring the earth's surface from space. In this paper, Cloude's decomposition theorem is applied to a polarimetric random media model to simulate the radar measurements of vegetated canopies. The vegetated canopies are modeled as a three layer discrete random medium with leaves and branches in the first layer, tree trunks in the second layer, and a half space of homogeneous ground with rough interface as the bottom layer. The distorted born approximation (DBA) has been used to compute full Mueller matrix of the canopy, using canonical dielectric objects such as thin discs and cylinders as leaves, branches, and trunks, respectively. The Mueller matrix and the derived covariance matrix contain information on the second order statistics of radar signals at various polarizations from the canopy. To decompose the covariance matrix to its constituent targets, the eigenvalues and eigenvectors of the covariance matrix are computed in terms of the physical parameters of the canopy. In addition, each eigenvector explicitly shows the scattering mechanisms such as odd and even reflections in the canopy. Cloude's decomposition theorem is applied using the Pauli spin matrices as a basis and an expression for the degree of disorder or the entropy for the vegetated surface is found. Then, the physical parameters estimated from in situ measurements are used in the random media to obtain realistic covariance matrices. As a result, the sensitivity of the eigenvalue spectrums and the coefficients resulting from the target decomposition theorem to the physical parameters of the canopy are examined and the possible use of Cloude's theorem to estimate vegetation and soil parameters is discussed.

Saatchi, Sasan S.↗
DOE OSTI2024

Random forest prediction of crystal structure from electron diffraction patterns incorporating multiple scattering

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here, in this study, we train an architecture of hierarchical random forest models capable of predicting the crystal system, space group, and lattice parameters from one or more unknown two-dimensional electron diffraction patterns. Our initial model correctly identifies the crystal system of a simulated electron diffraction pattern from a 20-nm-thick specimen of arbitrary orientation 67% of the time. We achieve a topline accuracy of 79% when aggregating predictions from ten patterns of the same material but different zone axes. The space group and lattice predictions range from 70% to 90% accuracy and median errors of 0.01-0.5Å, respectively, for cubic, hexagonal, trigonal, and tetragonal crystal systems while being less reliable on orthorhombic and monoclinic systems. We apply this architecture to a four-dimensional scanning transmission electron microscopy scan of gold nanoparticles, where it accurately predicts the crystal structure and lattice constants. These random forest models can be used to significantly accelerate the analysis of electron diffraction patterns, particularly in the case of unknown crystal structures. Additionally, due to the speed of inference, these models could be integrated into live transmission electron microscopy experiments, allowing real-Time labeling of a specimen.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Surrogate-Based Autotuning for Randomized Sketching Algorithms in Regression Problems

Algorithms from Randomized Numerical Linear Algebra (RandNLA) are known to be effective in handling high-dimensional computational problems, providing high-quality empirical performance as well as strong probabilistic guarantees. However, their practical application is complicated by the fact that the user needs to set various algorithm-specific tuning parameters which are different from those used in traditional NLA. This paper demonstrates how a surrogate-based autotuning approach can be used to address fundamental problems of parameter selection in RandNLA algorithms. In particular, we provide a detailed investigation of surrogate-based autotuning for sketch-and-precondition (SAP)-based randomized least squares methods, which have been one of the great success stories in modern RandNLA. Empirical results show that our surrogate-based autotuning approach can achieve near-optimal performance with much less tuning cost than a random search (up to about 7.6x fewer trials of different parameter configurations). Moreover, while our experiments focus on least squares, our results demonstrate a general-purpose autotuning pipeline applicable to any kind of RandNLA algorithm.

Cho, Younghyun↗