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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

An orthogonal coordinate grid following the three-dimensional viscous flow over a concave surface

Swept wings designed for laminar flow control exhibit both centrifugal and crossflow instabilities which produce streamwise vortices that can lead to early transition from laminar to turbulent flow in the presence of Tollmien-Schlichting waves. This paper outlines an iterative algorithm for generation of an orthogonal, curvilinear, coordinate grid following the streamlines of the three-dimensional viscous flow over a swept, concave surface. The governing equations for the metric tensor are derived from the Riemann-Christoffel tensor for an Euclidian geometry. Unit vectors along streamline, normal and binormal directions are determined. The governing equations are not solved directly, but are employed only as compatibility equations. The scale factor for the streamline coordinate is obtained by an iterative integration scheme on a 200 x 100 x 5 grid, while the other two scale factors are determined from definitions. Sample results are obtained which indicate that the compatibility equation error decreases linearly with grid step size. Grids smaller than 200 x 100 x 5 are found to be inadequate to resolve the grid curvature.

Dagenhart, J. R↗
NASA NTRS1991

Data compression: The end-to-end information systems perspective for NASA space science missions

The unique characteristics of compressed data have important implications to the design of space science data systems, science applications, and data compression techniques. The sequential nature or data dependence between each of the sample values within a block of compressed data introduces an error multiplication or propagation factor which compounds the effects of communication errors. The data communication characteristics of the onboard data acquisition, storage, and telecommunication channels may influence the size of the compressed blocks and the frequency of included re-initialization points. The organization of the compressed data are continually changing depending on the entropy of the input data. This also results in a variable output rate from the instrument which may require buffering to interface with the spacecraft data system. On the ground, there exist key tradeoff issues associated with the distribution and management of the science data products when data compression techniques are applied in order to alleviate the constraints imposed by ground communication bandwidth and data storage capacity.

Tai, Wallace↗
NASA NTRS1992

Monthly mean global satellite data sets available in CCM history tape format

Satellite data for climate monitoring have become increasingly important over the past decade, especially with increasing concern for inadvertent antropogenic climate change. Although most satellite based data are of short record, satellites can provide the global coverage that traditional meteorological observations network lack. In addition, satellite data are invaluable for the validation of climate models, and they are useful for many diagnostic studies. Herein, several satellite data sets were processed and transposed into 'history tape' format for use with the Community Climate Model (CCM) modular processor. Only a few of the most widely used and best documented data sets were selected at this point, although future work will expand the number of data sets examined as well as update the archived data sets. An attempt was made to include data of longer record and only monthly averaged data were processed. For studies using satellite data over an extended period, it is important to recognize the impact of changes in instrumentation, drift in instrument calibration, errors introduced by retrieval algorithms and other sources of errors such as those resulting from insufficient space and/or time sampling.

Hurrell, James W.↗
NASA NTRS1990

Multicolor pyrometer for materials processing in space

This report documents the work performed by Physical Sciences Inc. (PSI), under contract to NASA JPL, during a 2.5-year SBIR Phase 2 Program. The program goals were to design, construct, and program a prototype passive imaging pyrometer capable of measuring, as accurately as possible, and controlling the temperature distribution across the surface of a moving object suspended in space. These goals were achieved and the instrument was delivered to JPL in November 1989. The pyrometer utilizes an optical system which operates at short wavelengths compared to the peak of the black-body spectrum for the temperature range of interest, thus minimizing errors associated with a lack of knowledge about the heated sample's emissivity. To cover temperatures from 900 to 2500 K, six wavelengths are available. The preferred wavelength for measurement of a particular temperature decreases as the temperature increases. Images at all six wavelengths are projected onto a single CCD camera concurrently. The camera and optical system have been calibrated to relate the measured intensity at each pixel to the temperature of the heated object. The output of the camera is digitized by a frame grabber installed in a personal computer and analyzed automatically to yield temperature information. The data can be used in a feedback loop to alter the status of computer-activated switches and thereby control a heating system.

Frish, M. B.↗
NASA NTRS1998

Automated Track Recognition and Event Reconstruction in Nuclear Emulsion

The major advantages of nuclear emulsion for detecting charged particles are its submicron position resolution and sensitivity to minimum ionizing particles. These must be balanced, however, against the difficult manual microscope measurement by skilled observers required for the analysis. We have developed an automated system to acquire and analyze the microscope images from emulsion chambers. Each emulsion plate is analyzed independently, allowing coincidence techniques to be used in order to reject back- ground and estimate error rates. The system has been used to analyze a sample of high-multiplicity Pb-Pb interactions (charged particle multiplicities approx. 1100) produced by the 158 GeV/c per nucleon Pb-208 beam at CERN. Automatically reconstructed track lists agree with our best manual measurements to 3%. We describe the image analysis and track reconstruction techniques, and discuss the measurement and reconstruction uncertainties.

Deines-Jones, P.↗
NASA NTRS1997

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quasi-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗
NASA NTRS1997

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗
NASA NTRS2001

Development of a fully integrated analysis system for ions based on ion-selective optodes and centrifugal microfluidics

A fully integrated, miniaturized analysis system for ions based on a centrifugal microfluidics platform and ion-selective optode membranes is described. The microfluidic architecture is composed of channels, five solution reservoirs, a measuring chamber, and a waste reservoir manufactured onto a disk-shaped substrate of poly(methyl methacrylate). Ion-selective optode membranes, composed of plasticized poly(vinyl chloride) impregnated with an ionophore, a proton chromoionophore, and a lipophilic anionic additive, were cast, with a spin-on device, onto a support layer and then immobilized on the disk. Fluid propulsion is achieved by the centrifugal force that results from spinning the disk, while a system of valves is built onto the disk to control flow. These valves operate based on fluid properties and fluid/substrate interactions and are controlled by the angular frequency of rotation. With this system, we have been able to deliver calibrant solutions, washing buffers, or "test" solutions to the measuring chamber where the optode membrane is located. An analysis system based on a potassium-selective optode has been characterized. Results indicate that optodes immobilized on the platform demonstrate theoretical responses in an absorbance mode of measurement. Samples of unknown concentration can be quantified to within 3% error by fitting the response function for a given optode membrane using an acid (for measuring the signal for a fully protonated chromoionophore), a base (for fully deprotonated chromoionophore), and two standard solutions. Further, the ability to measure ion concentrations by employing one standard solution in conjunction with acid and base and with two standards alone were studied to delineate whether the current architecture could be simplified. Finally, the efficacy of incorporating washing steps into the calibration protocol was investigated.

NASA Discipline Life Sciences Technologies↗
NASA NTRS2006

Modeling the Atmospheric Phase Effects of a Digital Antenna Array Communications System

In an antenna array system such as that used in the Deep Space Network (DSN) for satellite communication, it is often necessary to account for the effects due to the atmosphere. Typically, the atmosphere induces amplitude and phase fluctuations on the transmitted downlink signal that invalidate the assumed stationarity of the signal model. The degree to which these perturbations affect the stationarity of the model depends both on parameters of the atmosphere, including wind speed and turbulence strength, and on parameters of the communication system, such as the sampling rate used. In this article, we focus on modeling the atmospheric phase fluctuations in a digital antenna array communications system. Based on a continuous-time statistical model for the atmospheric phase effects, we show how to obtain a related discrete-time model based on sampling the continuous-time process. The effects of the nonstationarity of the resulting signal model are investigated using the sample matrix inversion (SMI) algorithm for minimum mean-squared error (MMSE) equalization of the received signal

Tkacenko, A.↗
NASA NTRS2004

Bayesian Approach to the Joint Inversion of Gravity and Magnetic Data, with Application to the Ismenius Area of Mars

This viewgraph presentation reviews a Bayesian approach to the inversion of gravity and magnetic data with specific application to the Ismenius Area of Mars. Many inverse problems encountered in geophysics and planetary science are well known to be non-unique (i.e. inversion of gravity the density structure of a body). In hopes of reducing the non-uniqueness of solutions, there has been interest in the joint analysis of data. An example is the joint inversion of gravity and magnetic data, with the assumption that the same physical anomalies generate both the observed magnetic and gravitational anomalies. In this talk, we formulate the joint analysis of different types of data in a Bayesian framework and apply the formalism to the inference of the density and remanent magnetization structure for a local region in the Ismenius area of Mars. The Bayesian approach allows prior information or constraints in the solutions to be incorporated in the inversion, with the "best" solutions those whose forward predictions most closely match the data while remaining consistent with assumed constraints. The application of this framework to the inversion of gravity and magnetic data on Mars reveals two typical challenges - the forward predictions of the data have a linear dependence on some of the quantities of interest, and non-linear dependence on others (termed the "linear" and "non-linear" variables, respectively). For observations with Gaussian noise, a Bayesian approach to inversion for "linear" variables reduces to a linear filtering problem, with an explicitly computable "error" matrix. However, for models whose forward predictions have non-linear dependencies, inference is no longer given by such a simple linear problem, and moreover, the uncertainty in the solution is no longer completely specified by a computable "error matrix". It is therefore important to develop methods for sampling from the full Bayesian posterior to provide a complete and statistically consistent picture of model uncertainty, and what has been learned from observations. We will discuss advanced numerical techniques, including Monte Carlo Markov

data analysis↗
NASA NTRSDate not supplied

A Data-Driven Approach to Recognizing and Understanding Human Contributions to Aviation Safety

Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence, and are influenced by, how decision makers characterize problems and identify solutions. In the commercial aviation domain, large volumes of data are collected and analyzed on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on safety-producing behaviors, safety management and system design decisions are based on a small sample of non-representative safety data. Analysis of aviation accident data suggests that human error is implicated in up to 80% of accidents, which has been used to justify future visions for aviation in which the roles of human operators are greatly diminished or eliminated in the interest of creating a safer aviation system. However, failure to fully consider the human contributions to aviation safety represents a significant and largely unrecognized risk when making policy decisions about safety management and system design. Opportunities exist to leverage the vast amount of data that have already been collected, or could be easily obtained, to increase our understanding of human contributions to safety in commercial aviation. This presentation will focus on those opportunities as well as the challenges associated with collecting and analyzing data on operators’ safety-producing behaviors.

Safety↗
NASA NTRS2021

State of the Art in GNSS-R Capabilities Over Inland Waters

GNSS Reflectometry (GNSS-R) measurements are very sensitive to the presence of inland waters such as wetlands, floods, rivers and lakes. This paper reviews the basic characteristics of a GNSS-R ‘water detection’ product, including resolution and temporal sampling of wetlands, and discusses the main known sources of errors.

Morris, Mary↗
NASA NTRS2024

Summarizing Multiple Aspects of Triple Collocation Analysis in a Single Diagram

With the ongoing expansion of global observation networks, it is expected that we shall routinely analyze records of geophysical variables such as temperature from multiple collocated instruments. Validating datasets in this situation is not a trivial task because every observing system has its own bias and noise. Triple collocation is a general statistical framework to estimate the error characteristics in three or more observational-based datasets. In a triple colocation analysis, several metrics are routinely reported but traditional multiple-panel plots are not the most effective way to display information. A new formula of error variance is derived for connecting the key terms in the triple collocation theory. A diagram based on this formula is devised to facilitate triple collocation analysis of any data from observations, as illustrated using three aerosol optical depth datasets from the recent Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). An observational-based skill score is also derived to evaluate the quality of three datasets by taking into account both error variance and correlation coefficient. Several applications are discussed and sample plotting routines are provided.

triple collocation↗
DOE OSTI2018

The Mismeasure of Mergers: Revised Limits on Self-interacting Dark Matter in Merging Galaxy Clusters

In an influential recent paper, Harvey et al. derive an upper limit to the self-interaction cross section of dark matter (DM) (${\sigma }_{{\rm{DM}}}/m$ < 0.47 cm 2 g -1 at 95% confidence) by averaging the DM–galaxy offsets in a sample of merging galaxy clusters. Using much more comprehensive data on the same clusters, we identify several substantial errors in their offset measurements. Correcting these errors relaxes the upper limit on ${\sigma }_{{\rm{DM}}}/m$ to $\lesssim$2 cm 2 g -1 , following the Harvey et al. prescription for relating offsets to cross sections in a simple solid-body scattering model. Furthermore, many clusters in the sample violate the assumptions behind this prescription, so even this revised upper limit should be used with caution. Although this particular sample does not tightly constrain self-interacting DM models when analyzed this way, we discuss how merger ensembles may be used more effectively in the future. Finally, we conclude that errors inherent in using single-band imaging to identify mass and light peaks do not necessarily average out in a sample of this size, particularly when a handful of substructures constitute a majority of the weight in the ensemble.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Accuracy of tip-sample interaction measurements using dynamic atomic force microscopy techniques: Dependence on oscillation amplitude, interaction strength, and tip-sample distance

Atomic force microscopy (AFM) is a versatile surface characterization method that can map a sample’s topography with high spatial resolution while simultaneously interrogating its surface chemistry through the site-specific high-resolution quantification of the forces acting between the sample and the probe tip. Thanks to considerable advances in AFM measurement technology, such local measurements of chemical properties have gained much popularity in recent years. To this end, dynamic AFM methodologies are implemented where either the oscillation frequency or the oscillation amplitude and phase of the vibrating cantilever are recorded as a function of tip-sample distance and subsequently converted to reflect tip-sample forces or interaction potentials. Such conversion has, however, been shown to produce non-negligible errors when applying the most commonly used mathematical conversion procedures if oscillation amplitudes are of the order of the decay length of the interaction. Extending on these earlier findings, the computational study presented in this paper reveals that the degree of divergence from actual values may also critically depend on both the overall strength of tip-sample interaction and the distance at which the interaction is obtained. These systematic errors can, however, be effectively eliminated by using oscillation amplitudes that are sufficiently larger than the decay length of the interaction potential.

Electrical properties and parameters↗
NASA NTRS1971

Delta Modulation

An optimum adaptive delta modulator-demodulator configuration is derived. This device utilizes two past samples to obtain a step size which minimizes the mean square error for a Markov Gaussian source. The optimum system is compared using computer simulations with the linear delta modulator and an enhanced Abate delta modulator. In addition the performance is compared to the rate distortion bound for a Markov source. It is shown that the optimum delta modulator is neither quantization nor slope-overload limited. The results show that the output signal-to-noise ratio is independent of the input signal power and is subject only to the limitations of the hardware employed. In addition, voice was recorded using these systems. The demodulated voice indicates negligible degradation is caused by the optimum system and by the enhanced Abate system while the linear delta modulator suffers significant degradation at a sampling frequency of 56 kilobits/sec.

Schilling, D. L.↗
DOE OSTI2023

Deep nonparametric estimation of intrinsic data structures by chart autoencoders: Generalization error and robustness

Autoencoders have demonstrated remarkable success in learning low-dimensional latent features of high-dimensional data across various applications. Assuming that data are sampled near a low-dimensional manifold, we employ chart autoencoders, which encode data into low-dimensional latent features on a collection of charts, preserving the topology and geometry of the data manifold. Our paper establishes statistical guarantees on the generalization error of chart autoencoders, and we demonstrate their denoising capabilities by considering n noisy training samples, along with their noise-free counterparts, on a d-dimensional manifold. By training autoencoders, we show that chart autoencoders can effectively denoise the input data with normal noise. We prove that, under proper network architectures, chart autoencoders achieve a squared generalization error in the order of n–$\frac{2}{d+2}$log 4 n, which depends on the intrinsic dimension of the manifold and only weakly depends on the ambient dimension and noise level. We further extend our theory on data with noise containing both normal and tangential components, where chart autoencoders still exhibit a denoising effect for the normal component. As a special case, our theory also applies to classical autoencoders, as long as the data manifold has a global parametrization. Furthermore, our results provide a solid theoretical foundation for the effectiveness of autoencoders, which is further validated through several numerical experiments.

97 MATHEMATICS AND COMPUTING↗