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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Jupiter orbiter lifetime: The hazard of Galilean satellite collision

The four Galilean satellites of Jupiter present a long-term collision hazard to an uncontrolled orbiting spacecraft that repeatedly enters the spatial region occupied by the satellites. Satellite close encounters and the likelihood of collision over a wide range of initial orbit conditions were analyzed. The effect of orbit inclination was of key interest. The scope of the analysis was restricted to orbital dynamic considerations alone, i.e. the question of biological contamination given the event of collision was not considered. A quarantine or orbiter lifetime of 50 years was assumed. This time period begins at spacecraft shutdown following completion of the mission objectives. A numerical approach was adopted wherein each initial orbit is propagated for 50 years, and satellite closest encounter distances recorded on every revolution. The computer program includes approximations of the three major perturbation effects on the long-term motion of the orbiter: (1) Jupiter oblateness, (2) solar gravity, and (3) satellite gravity.

Friedlander, A. L.↗
NASA NTRS1975

Mapping of the wildland fuel characteristics of the Santa Monica mountains of Southern California

LANDSAT digital data was successfully used to map and evaluate the wildland fuels of the Santa Monica Mountains in Southern California. A mixed classification scheme was used where training areas of known vegetation types were entered and the maximum likelihood classifier run, followed by an evaluation of the results and an unsupervised retraining of the classifier using an image of the probability of misclassification. Estimation of maturity class and crown closure percents of the major cover types were assigned to each computer class by associating the photointerpretation of 159 large scale photo samples with the resultant computer classes using analysis of variance and analysis of categorized data. The result of the computer classification and statistical analysis were then transformed from the LANDSAT Coordinate California State Plane Coordinate system for use in a digital format in the FIRESCOPE data retrieval and fire modeling system.

Nichols, J. D.↗
NASA NTRS1975

Geological mapping in northwestern Saudi Arabia using LANDSAT multispectral techniques

Various computer enhancement and data extraction systems using LANDSAT data were assessed and used to complement a continuing geologic mapping program. Interactive digital classification techniques using both the maximum-likelihood and thresholding statistical approaches achieve very limited success in areas of highly dissected terrain. Computer enhanced imagery developed by color compositing stretched MSS ratio data was constructed for a test site in northwestern Saudi Arabia. Initial results indicate that several igneous and sedimentary rock-types can be discriminated.

Blodget, H. W.↗
NASA NTRS1975

Layered classification techniques for remote sensing applications

The single-stage method of pattern classification utilizes all available features in a single test which assigns the unknown to a category according to a specific decision strategy (such as the maximum likelihood strategy). The layered classifier classifies the unknown through a sequence of tests, each of which may be dependent on the outcome of previous tests. Although the layered classifier was originally investigated as a means of improving classification accuracy and efficiency, it was found that in the context of remote sensing data analysis, other advantages also accrue due to many of the special characteristics of both the data and the applications pursued. The layered classifier method and several of the diverse applications of this approach are discussed.

Swain, P. H.↗
NASA NTRS1975

M-DAS: System for multispectral data analysis

M-DAS is a ground data processing system designed for analysis of multispectral data. M-DAS operates on multispectral data from LANDSAT, S-192, M2S and other sources in CCT form. Interactive training by operator-investigators using a variable cursor on a color display was used to derive optimum processing coefficients and data on cluster separability. An advanced multivariate normal-maximum likelihood processing algorithm was used to produce output in various formats: color-coded film images, geometrically corrected map overlays, moving displays of scene sections, coverage tabulations and categorized CCTs. The analysis procedure for M-DAS involves three phases: (1) screening and training, (2) analysis of training data to compute performance predictions and processing coefficients, and (3) processing of multichannel input data into categorized results. Typical M-DAS applications involve iteration between each of these phases. A series of photographs of the M-DAS display are used to illustrate M-DAS operation.

Johnson, R. H.↗
NASA NTRS1975

Satellite information on Orlando, Florida

A land use map of Orange County, Florida was prepared from EREP photography while LANDSAT and EREP multispectral scanner data were used to provide more detailed information on Orlando and its suburbs. The generalized maps were prepared by tracing the patterns on an overlay, using an enlarging viewer. Digital analysis of the multispectral scanner data was basically the maximum likelihood classification method with training sample input and computer printer mapping of the results. Urban features delineated by the maps are discussed. It is concluded that computer classification, accompanied by human interpretation and manual simplification can produce land use maps which are useful on a regional, county, and city basis.

Hannah, J. W.↗
NASA NTRS1975

Factors affecting snow assessment from LANDSAT data

Problems associated with using LANDSAT as a snow monitoring satellite are studied. Data cover problems of slop hinderance in thematic mapping of snow and detection of snow in forested areas. It was concluded that if detector saturation threshold is raised and the upper spectral limit of the MSS is extended, snow extent mapping will be improved along with the likelihood of monitoring some aspects of the physical condition of snow pack.

Mcginnis, D. F., Jr.↗
NASA NTRS1975

Future US energy demands based upon traditional consumption patterns lead to requirements which significantly exceed domestic supply

Energy consumption in the United States has risen in response to both increasing population and to increasing levels of affluence. Depletion of domestic energy reserves requires consumption modulation, production of fossil fuels, more efficient conversion techniques, and large scale transitions to non-fossile fuel energy sources. Widening disparity between the wealthy and poor nations of the world contributes to trends that increase the likelihood of group action by the lesser developed countries to achieve political and economic goals. The formation of anticartel cartels is envisioned.

Source record↗
NASA NTRS1976

Analytical evaluation of tilting proprotor wind tunnel test requirements

Specific test requirements related to the wind tunnel testing of the XV-15 advanced tilt rotor research aircraft were determined. The following analytical tools were developed: (1) digital simulation of the XV-15, incorporating a simplified tunnel support model, control system loop, measurement lags, gust disturbances, and sensor noise, (2) specialization of existing data analysis programs to the high order XV-15 dynamical model (transfer function program, a time series analysis program, an advanced maximum likelihood parameter identification program), (3) several auxiliary programs to provide estimates of damping from transfer functions as well as calculations of model decomposition of system response. The following results were discussed: (1) modelling of the aircraft, instrumentation, and controls, (2) results of the rotor/cantilever wing model and coupled wing, (3) examples of data prediction with system identification techniques, and (4) detailed conclusions and recommendations.

Hall, W. E., Jr.↗
NASA NTRS1975

Multidimensional stochastic approximation using locally contractive functions

A Robbins-Monro type multidimensional stochastic approximation algorithm which converges in mean square and with probability one to the fixed point of a locally contractive regression function is developed. The algorithm is applied to obtain maximum likelihood estimates of the parameters for a mixture of multivariate normal distributions.

Lawton, W. M.↗
NASA NTRS1976

Dynamics and identification of flexible aircraft

The equations of motion and a maximum likelihood parameter identification formulation are developed for a flexible aircraft. The various levels of approximation associated with the modal substitution representation of the elastic displacement field are discussed and illustrated when appropriate. The necessary extension of the parameter set of stability and control derivatives due to the aeroelastic effects is obtained.

Wells, W. R.↗
NASA NTRS1975

Mapping forest vegetation with ERTS-1 MSS data and automatic data processing techniques

This study was undertaken with the intent of elucidating the forest mapping capabilities of ERTS-1 MSS data when analyzed with the aid of LARS' automatic data processing techniques. The site for this investigation was the Great Dismal Swamp, a 210,000 acre wilderness area located on the Middle Atlantic coastal plain. Due to inadequate ground truth information on the distribution of vegetation within the swamp, an unsupervised classification scheme was utilized. Initially pictureprints, resembling low resolution photographs, were generated in each of the four ERTS-1 channels. Data found within rectangular training fields was then clustered into 13 spectral groups and defined statistically. Using a maximum likelihood classification scheme, the unknown data points were subsequently classified into one of the designated training classes. Training field data was classified with a high degree of accuracy (greater than 95 percent), and progress is being made towards identifying the mapped spectral classes.

Messmore, J.↗
NASA NTRS1976

Classification improvement by optimal dimensionality reduction when training sets are of small size

A computer simulation was performed to test the conjecture that, when the sizes of the training sets are small, classification in a subspace of the original data space may give rise to a smaller probability of error than the classification in the data space itself; this is because the gain in the accuracy of estimation of the likelihood functions used in classification in the lower dimensional space (subspace) offsets the loss of information associated with dimensionality reduction (feature extraction). A number of pseudo-random training and data vectors were generated from two four-dimensional Gaussian classes. A special algorithm was used to create an optimal one-dimensional feature space on which to project the data. When the sizes of the training sets are small, classification of the data in the optimal one-dimensional space is found to yield lower error rates than the one in the original four-dimensional space.

Starks, S. A.↗
NASA NTRS1975

Jupiter orbiter lifetime - The hazard of Galilean satellite collision

An assessment of the long-term collision risk is made for an uncontrolled orbiting spacecraft that repeatedly enters the spatial region occupied by the satellites. Numerical data are obtained for 50-year orbit propagations which account approximately for the major perturbative effects of Jupiter oblateness, solar gravity and satellite gravity. A broad statistical viewpoint regarding the question of collision likelihood is adopted and is based on a total sample size of 480 initial orbits distributed among 4 orbit classes, 8 inclinations and 15 initial epochs. Numerical results compare favorably with an analytical prediction formula which shows that eccentric, low-inclination orbits have high collision probability.

Friedlander, A. L.↗
NASA NTRS1976

Optical pulse timing resolution

This correspondence evaluates the performance of the maximum likelihood (ML) and several suboptimal arrival time estimators for optical pulses. The performance analysis of a 'sliding window' counter followed by a threshold detector is achieved by deriving an expression for the first-crossing density of the output of the counter.

Lee, G.↗
NASA NTRS1975

The decision tree classifier - Design and potential

A new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.

Hauska, H.↗