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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Fourier transform techniques for the evaluation of the Thematic Mapper line spread function

An endeavor was made to use Fourier transform techniques to estimate the line spread function (LSF) of the Thematic Mapper (TM) from processed data. Data near the boundary of small fields from TM scenes were sampled, fitted to a theoretical curve, lowpass filtered, and then deconvolved to obtain the LSF. Lowpass filtering improved the truncation effect and eliminated the discontinuity at both ends of the data sequence.The selection of the cutoff frequency and the order of a lowpass filter is based on a newly defined criterion which tests the distortion of the processed edge by comparing it with the original edge. A parameter of the LSF, the equivalent width, is used to compare these LSF's deconvolved from sampled edge data with those evaluated by the derivative techniques. The calculated equivalent widths using the Fourier transform techniques for infrared bands are very close to TM design specifications.

Carnahan, W. H.↗
NASA NTRS1986

An analysis at mesospheric coherent-scatter power enhancements during solar flare events

Solar flares produce increases in coherent-scatter power from the mesosphere due to the increase in free electrons produced by X-ray photoionization. Thirteen such power enhancements were observed at Urbana. When such an enhancement occurs at an altitude containing a turbulence layer with constant strength, the relative enhancement of electon density is estimated from the enhancement in power. Such estimates of enchanced electron density are compared with estimates of the X-ray photoionization at that altitude, deduced from geostationary satellite measurements. It is found that possible types ion-chemical reaction scheme may be distinguished, and the nonflare ion-pair production function may be estimated. The type of ion-chemical scheme and the nonflare ion-production function are shown to depend on the solar zenith angle.

Parker, J.↗
NASA NTRS1994

Performance of mean-frequency estimators for Doppler radar and lidar

The performance of mean-frequency estimators for Doppler radar and lidar measurements of winds is presented in terms of two basic parameters: Phi, the ratio of the average signal energy per estimate to the spectral noise level; and Omega, which is proportional to the number of independent samples per estimate. For fixed Phi and Omega, the Cramer-Rao bound (CRB) (theoretical best performance) for unbiased estimators of mean frequency (normalized by the spectral width of the signal), signal power, and spectral width are essentially independent of the number of data samples M. For large Phi, the estimators of mean frequency are unbiased and the performance is independent of M. The spectral domain estimators and covariance based estimators are bounded by the approximate period of M. The spectral domain estimators and covariance based estimators are bounded by the approximate periodogram CRB. The standard deviation of the maximum-likelihood estimator approaches the exact CRB, which can be more than a factor of 2 better than the performance of the spectral domain estimators or covariance-based estimators for typical Omega. For small Phi, the estimators are biased due to the effects of the uncorrelated noise (white noise), which results in uniformly distributed 'bad' estimates. The fraction of bad estimates is a function of Phi and M with weak dependence on the parameter Omega. Simple empirical models describe the standard deviation of the good estimates and the fraction of bad estimates. For Doppler lidar and for large Phi, better performance is obtained by using many low-energy pulses instead of one pulse with the same total energy. For small Phi, the converse is true.

Frehlich, R. G.↗
NASA NTRS2017

Methods of Constructing a Blended Performance Function Suitable for Formation Flight

This paper presents two methods for constructing an approximate performance function of a desired parameter using correlated parameters. The methods are useful when real-time measurements of a desired performance function are not available to applications such as extremum-seeking control systems. The first method approximates an a priori measured or estimated desired performance function by combining real-time measurements of readily available correlated parameters. The parameters are combined using a weighting vector determined from a minimum-squares optimization to form a blended performance function. The blended performance function better matches the desired performance function mini- mum than single-measurement performance functions. The second method expands upon the first by replacing the a priori data with near-real-time measurements of the desired performance function. The resulting blended performance function weighting vector is up- dated when measurements of the desired performance function are available. Both methods are applied to data collected during formation- flight-for-drag-reduction flight experiments.

control systems↗
NASA NTRS1983

A function space approach to state and model error estimation for elliptic systems

An approach is advanced for the concurrent estimation of the state and of the model errors of a system described by elliptic equations. The estimates are obtained by a deterministic least-squares approach that seeks to minimize a quadratic functional of the model errors, or equivalently, to find the vector of smallest norm subject to linear constraints in a suitably defined function space. The minimum norm solution can be obtained by solving either a Fredholm integral equation of the second kind for the case with continuously distributed data or a related matrix equation for the problem with discretely located measurements. Solution of either one of these equations is obtained in a batch-processing mode in which all of the data is processed simultaneously or, in certain restricted geometries, in a spatially scanning mode in which the data is processed recursively. After the methods for computation of the optimal estimates are developed, an analysis of the second-order statistics of the estimates and of the corresponding estimation error is conducted. Based on this analysis, explicit expressions for the mean-square estimation error associated with both the state and model error estimates are then developed.

Rodriguez, G.↗
NASA NTRS1983

A function space approach to state and model error estimation for elliptic systems

An approach is advanced for the concurrent estimation of the state and of the model errors of a system described by elliptic equations. The estimates are obtained by a deterministic least-squares approach that seeks to minimize a quadratic functional of the model errors, or equivalently, to find the vector of smallest norm subject to linear constraints in a suitably defined function space. The minimum norm solution can be obtained by solving either a Fredholm integral equation of the second kind for the case with continuously distributed data or a related matrix equation for the problem with discretely located measurements. Solution of either one of these equations is obtained in a batch-processing mode in which all of the data is processed simultaneously or, in certain restricted geometries, in a spatially scanning mode in which the data is processed recursively. After the methods for computation of the optimal esimates are developed, an analysis of the second-order statistics of the estimates and of the corresponding estimation error is conducted. Based on this analysis, explicit expressions for the mean-square estimation error associated with both the state and model error estimates are then developed. While this paper focuses on theoretical developments, applications arising in the area of large structure static shape determination are contained in a closely related paper (Rodriguez and Scheid, 1982).

Rodriguez, G.↗
NASA NTRS1983

Estimation of delays and other parameters in nonlinear functional differential equations

A spline-based approximation scheme for nonlinear nonautonomous delay differential equations is discussed. Convergence results (using dissipative type estimates on the underlying nonlinear operators) are given in the context of parameter estimation problems which include estimation of multiple delays and initial data as well as the usual coefficient-type parameters. A brief summary of some of the related numerical findings is also given.

Banks, H. T.↗
NASA NTRS1984

Viking bistatic radar experiment - Summary of results in near-equatorial regions

Viking bistatic radar have been processed using Hagfors' scattering function to obtain estimates of rms surface roughness from ground tracks primarily in the equatorial region of Mars. Roughness varies from as little as 0.75 deg rms east of Solis and Sinai Plana to at least 8 deg on the western slope of Arsia Mons. Estimated roughness in cratered terrain is generally about 5 deg or less, implying the existence of smoothing processes on scales less than 100 m. There is good agreement between bistatic roughness estimates and earth-based results at ground track intersections near the equator in both cratered terrain and plains. Surface tilt probability density functions derived from these observations are usually more sharply peaked than the Hagfors function for similar values of rms surface roughness. Earlier results using the Gaussian model appear to have overestimated the surface roughness by 30-40 percent.

Simpson, R. A.↗
NASA NTRS1968

Application of a truncated normal failure distribution in reliability testing

Statistical truncated normal distribution function is applied as a time-to-failure distribution function in equipment reliability estimations. Age-dependent characteristics of the truncated function provide a basis for formulating a system of high-reliability testing that effectively merges statistical, engineering, and cost considerations.

Groves, C., Jr.↗
NASA NTRS1980

Heating of the moon by heterogeneous accretion

Monte Carlo models of lunar accretion are developed by randomly sampling mass and velocity distributions of objects in the solar nebula in circumsolar and circumterrestrial orbits. The thermal effect of an impact is expressed as the volume of melt produced; the melt volumes produced by each Monte Carlo case are sorted into regions to produce percentage melt estimates as a function of radius. One-hundred cases are calculated to obtain a range of plausible thermal histories for lunar accretion. The average melt percentage estimates show substantial deep melting, but the spread of melt percentage values about the mean from the random sampling procedure is wide enough to include 0% melting for radii below 100 km and 100% melting for radii below 500 km.

Ransford, G. A.↗
NASA NTRS1985

Admittance functions from Venus vertical gravity and modes of topographic support

Two-dimensional Fourier admittance functions have been estimated for various regions of Venus, using as input the Pioneer Venus topography data and the Venus vertical gravity model of Sjogren. Model admittance functions are computed for various cases, such as lithospheric loading from above, and support from below, for comparison. These models are functions of depth of compensation, flexural rigidity, and crust and mantle densities. The long wavelength topography and gravity signals contain most of the spectral power in the Venus data, and the admittances at these wavelengths are compatible with deep compensation of surface topography.

Williams, D. R.↗
NASA NTRS1972

Signal sequence detection given noisy, common background image sets.

The optimum processing (likelihood functional) is found for a set of M images, each the sum of a member of a signal sequence due to an object to be detected and its parameters estimated, a sample function of a noise field, and a sample function of a common background field. The noise fields are independent, zero mean, white Gaussian fields, all independent of the background field. The latter is assumed to be either (1) completely unknown or of known mean and covariance functions with (2) a certain fluctuation property or (3) Gaussian. Three equivalent forms of the optimum processing are found: (1) a summation of generalized matched filterings of the images, (2) a summation of matched filtering of certain generalized differences of the images, and (3) a summation of 'estimator-correlator' type filterings. The detection performance and optimum signal/image selection under the Neyman-Pearson criterion is given, and is shown that optimum processor and signal design can completely eliminate any effect of the background on detectability.

Harger, R. O.↗
NASA NTRS2007

Propagation of Computational Uncertainty Using the Modern Design of Experiments

This paper describes the use of formally designed experiments to aid in the error analysis of a computational experiment. A method is described by which the underlying code is approximated with relatively low-order polynomial graduating functions represented by truncated Taylor series approximations to the true underlying response function. A resource-minimal approach is outlined by which such graduating functions can be estimated from a minimum number of case runs of the underlying computational code. Certain practical considerations are discussed, including ways and means of coping with high-order response functions. The distributional properties of prediction residuals are presented and discussed. A practical method is presented for quantifying that component of the prediction uncertainty of a computational code that can be attributed to imperfect knowledge of independent variable levels. This method is illustrated with a recent assessment of uncertainty in computational estimates of Space Shuttle thermal and structural reentry loads attributable to ice and foam debris impact on ascent.

DeLoach, Richard↗
NASA NTRS1994

Generation of electrostatic waves as a consequence of chaotic ion acceleration in the neutral sheet

The stability of ion distributions with velocity space holes caused by chaotic ion acceleration in the vicinity of the field reversal region in the Earth's magnetotail is investigated. It is shown that such distributions are unstable to electrostatic waves with wave vector directed along the Sun-Earth line. The solution of the quasi-linear equation shows that the saturation of the instability occurs due to velocity space trapping of the low-energy background ions and results in a flattening of the reduced ion distribution function in the region of the original velocity space hole. The energy level of the excited waves in the vicinity of the Earth's midplane is estimated as a function of the initial size of the empty velocity space region.

Burinskaya, T.↗
NASA NTRS1995

On treatments of fetch and stability sensitivity in large-area estimates of sensible heat flux over sea ice

Bulk transfer coefficients estimated as a function of atmospheric stability and sea-ice lead width are combined with Arctic meteorological observations and ice thickness data to calculate the sensitivity of turbulent flux estimates to changes in lead width, wind speed, air temperature, and ice thickness for a high-concentration ice pack. These results are considered in terms of bulk transfer parameterizations that use a fixed transfer coefficient r that address atmospheric stability only. On the basis of the fetch-sensitive parameterizations considered here, differences in lead width for widths up to about 200 m can exert a substantial influence on sensible heat transfer coefficients and heat flux from leads under typical Arctic conditions. Fluxes from an open water lead decrease by 34% if fetch increases from 10 m to 100 m. This effect is greatest for open water leads, decreases considerably as leads refreeze, and is negligible for ice thicker than about 0.3 m. If open or newly refrozen leads make up 2% of the ice cover, than an increase in mean fetch from 10 m to 100 m yields a decrease of about 2 W/sq m in areally averaged flux from the ice pack. Calculations using observed and theoretical lead width distributions suggest that parameterizing lead widths in a sea ice model can be done effectively using a single, representative lead width rather than requiring a full distribution of widths. When coupled to the lowest atmospheric boundary layer using a bulk similarity theory model, this sensitivity of heat transfer to fetch results in substantially higher near-surface air temperatures over narrow leads, with equilibrium air temperatures decreasing by about 50% as fetch increases from 10 to 100 m.

Maslanik, J. A.↗
NASA NTRS1990

The augmented Lagrangian method for parameter estimation in elliptic systems

In this paper a new technique for the estimation of parameters in elliptic partial differential equations is developed. It is a hybrid method combining the output-least-squares and the equation error method. The new method is realized by an augmented Lagrangian formulation, and convergence as well as rate of convergence proofs are provided. Technically the critical step is the verification of a coercivity estimate of an appropriately defined Lagrangian functional. To obtain this coercivity estimate a seminorm regularization technique is used.

Ito, Kazufumi↗
NASA NTRS2010

Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

Ice, Cloud, and land Elevation Satellite (ICESat) / Geosciences Laser Altimeter System (GLAS) waveform data are used to estimate biomass and carbon on a 1.27 X 10(exp 6) square km study area in the Province of Quebec, Canada, below the tree line. The same input datasets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include non-stratified and stratified versions of a multiple linear model where either biomass or (biomass)(exp 0.5) serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial dry biomass estimates of up to 0.35 G, with a range of 4.94 +/- 0.28 Gt to 5.29 +/-0.36 Gt. The differences among model estimates are statistically non-significant, however, and the results demonstrate the degree to which carbon estimates vary strictly as a function of the model used to estimate regional biomass. Results also indicate that GLAS measurements become problematic with respect to height and biomass retrievals in the boreal forest when biomass values fall below 20 t/ha and when GLAS 75th percentile heights fall below 7 m.

Nelson, Ross F.↗
NASA NTRS2018

Improving Carbon Estimation of Large Tropical Trees by Linking Airborne Lidar Crown Size to Field Inventory

Quantifying tropical aboveground biomass (agb) is an outstanding challenge that requires knowledge on the 3D structure of forests. Recent studies suggest that the uncertainty in estimating agb of large trees is significantly reduced if tree height and crown size are accounted for in addition to the traditional trunk diameter and wood density. Due to the fact that field inventory techniques are not adapted to characterize the 3D forest structure, crown size metrics (e.g. height and radius) are commonly estimated as a function of trunk diameter using allometric models with limitations in explaining crown variability. Airborne lidar techniques have the potential for characterizing tree height and crown size but are not adapted to estimate trunk diameter, which is a strong predictor of agb. Here, we investigate the synergy of field inventory and airborne lidar techniques to characterize the forest structure by assessing the uncertainty introduced by the field-based allometric models in the estimation of agb at the tree-level. We focus in 1454 large individual trees (trunk diameter > 60 cm) located within the La Selva Biological Station for which we dispose of field observations (trunk diameter and wood density) and lidar derived metrics (tree height and crown radius). We show that the field-based allometric models overestimate tree height and underestimate crown radius. As a result, the allometric approach overestimates the tree-level agb in 0.8 Mg when considering the 1454 individuals and the errors can reach more than 50% of the agb of individual trees. These errors on the large trees agb highly impact on the plot-level results and then propagate to the estimation of carbon stocks at the regional and national-levels.

Clark, David↗