Search NASA⌕ Search

SEARCH · Search NASA

Results for “.NET”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Petri net model for analysis of concurrently processed complex algorithms

This paper presents a Petri-net model suitable for analyzing the concurrent processing of computationally complex algorithms. The decomposed operations are to be processed in a multiple processor, data driven architecture. Of particular interest is the application of the model to both the description of the data/control flow of a particular algorithm, and to the general specification of the data driven architecture. A candidate architecture is also presented.

Stoughton, John W.↗
NASA NTRS1987

The power of neural nets

Implementation of the Hopfield net which is used in the image processing type of applications where only partial information about the image may be available is discussed. The image classification type of algorithm of Hopfield and other learning algorithms, such as the Boltzmann machine and the back-propagation training algorithm, have many vital applications in space.

Ryan, J. P.↗
NASA NTRS1987

Channel size influence on the heat flux density at zero net mass flow in the non-linear transport regime between 1.2 and 2.1 K

Porous media and narrow ducts of simple shape at zero net mass flow (ZNMF) are used to investigate the influence of pore size on the entropy/heat convection rate at ZNMF. The study is relevant to the development of specific types of phase separators. Previous work on heat transport by convection is extended to porous media without mass loss. The experimental results show the influence of pore size on heat flux for permeabilities between 10 to the -8th and 10 to the -6th sq cm. ZNMF plug data are found to be similar to results obtained for vapor liquid phase separation.

Frederking, T. H. K.↗
NASA NTRS1987

Evaluating North American net primary productivity with satellite observations

An ecological model is developed to estimate annual net primary productivity (NPP) in 12 North American biomes. The model combines existing models which address canopy photosynthesis in response to light, temperature, and moisture availability, and account for respiration. Climate data, solar radiation data, and spectral vegetation index data are utilized. Estimates of NPP from the model compare well with data in the literature, but a systematic error is suspected. Difficulties encountered in specifying certain model parameters are discussed as possible sources of this error. The results of this study suggest the promise of remotely sensed measurements for macroscale evaluation and modeling of NPP.

Goward, Samuel N.↗
NASA NTRS1989

The utilization of neural nets in populating an object-oriented database

Existing NASA supported scientific data bases are usually developed, managed and populated in a tedious, error prone and self-limiting way in terms of what can be described in a relational Data Base Management System (DBMS). The next generation Earth remote sensing platforms (i.e., Earth Observation System, (EOS), will be capable of generating data at a rate of over 300 Mbs per second from a suite of instruments designed for different applications. What is needed is an innovative approach that creates object-oriented databases that segment, characterize, catalog and are manageable in a domain-specific context and whose contents are available interactively and in near-real-time to the user community. Described here is work in progress that utilizes an artificial neural net approach to characterize satellite imagery of undefined objects into high-level data objects. The characterized data is then dynamically allocated to an object-oriented data base where it can be reviewed and assessed by a user. The definition, development, and evolution of the overall data system model are steps in the creation of an application-driven knowledge-based scientific information system.

Campbell, William J.↗
NASA NTRS1989

Stochastic Petri net analysis of a replicated file system

A stochastic Petri-net model of a replicated file system is presented for a distributed environment where replicated files reside on different hosts and a voting algorithm is used to maintain consistency. Witnesses, which simply record the status of the file but contain no data, can be used in addition to or in place of files to reduce overhead. A model sufficiently detailed to include file status (current or out-of-date), as well as failure and repair of hosts where copies or witnesses reside, is presented. The number of copies and witnesses is a parameter of the model. Two different majority protocols are examined, one where a majority of all copies and witnesses is necessary to form a quorum, and the other where only a majority of the copies and witnesses on operational hosts is needed. The latter, known as adaptive voting, is shown to increase file availability in most cases.

Bechta Dugan, Joanne↗
NASA NTRS1989

Optical neural net for classifying imaging spectrometer data

The problem of determining the composition of an unknown input mixture from its measured spectrum, given the spectra of a number of elements, is studied. The Hopfield minimization procedure was used to express the determination of the compositions as a problem suitable for solution by neural nets. A mathematical description of the problem was developed and used as a basis for a neural network solution and an optical implementation.

Barnard, Etienne↗
NASA NTRS1990

Net Photorefractive Gain In Gallium Arsenide

Prerequisite includes applied electric field. Electric field applied to GaAs crystal in which two infrared beams interfere. Depending on quality of sample and experimental conditions, net photorefractive gain obtained. Results offer possibility of new developments in real-time optical processing of signals by use of near-infrared lasers of low power.

Liu, Tsuen-Hsi↗
NASA NTRS1990

Neural Network Development Tool (NETS)

Artificial neural networks formed from hundreds or thousands of simulated neurons, connected in manner similar to that in human brain. Such network models learning behavior. Using NETS involves translating problem to be solved into input/output pairs, designing network configuration, and training network. Written in C.

Baffes, Paul T.↗
NASA NTRS1989

A hybrid architecture for the implementation of the Athena neural net model

The implementation of an earlier introduced neural net model for pattern classification is considered. Data flow principles are employed in the development of a machine that efficiently implements the model and can be useful for real time classification tasks. Further enhancement with optical computing structures is also considered.

Koutsougeras, C.↗
NASA NTRS1990

Mechanisms leading to net drag reduction in manipulated turbulent boundary layers

Turbulent boundary layers have been manipulated successfully using passive devices called BLADES (boundary-layer alteration devices) leading to net drag reduction. Measurements of various turbulence quantities including intermittency have led to the identification of some of the mechanisms involved in skin-friction reduction. Velocity and vorticity fluctuations associated with oncoming large scales are inhibited significantly by the manipulator blades and the vorticity shed in their wake. The manipulated boundary layers exhibit a reduced intermittency in the outer part of the layer. The effects of manipulation relax with downstream distance and the boundary layer returns toward normal conditions after 100 or 150 boundary-layer thicknesses.

Guezennec, Y. G.↗
NASA NTRS1989

Estimating satellite pose and motion parameters using a novelty filter and neural net tracker

A system for determining the position, orientation and motion of a satellite with respect to a robotic spacecraft using video data is advanced. This system utilizes two levels of pose and motion estimation: an initial system which provides coarse estimates of pose and motion, and a second system which uses the coarse estimates and further processing to provide finer pose and motion estimates. The present paper emphasizes the initial coarse pose and motion estimation sybsystem. This subsystem utilizes novelty detection and filtering for locating novel parts and a neural net tracker to track these parts over time. Results of using this system on a sequence of images of a spin stabilized satellite are presented.

Lee, Andrew J.↗
NASA NTRS1990

Interannual variability of the global net radiation balance and its consequence on global energy transport

Global cloudiness and radiation budget data from Nimbus 6 and 7 are used to investigate the role of cloud and surface radiative forcing and elements of the earth's general circulation. Although globally integrated cloud forcing is nearly zero, there are large regional imbalances and well regulated processes in the shortwave and longwave spectrum that control the meridional gradient structure of the net radiation balance and the factors modulating the east-west oriented North Africa-western Pacific energy transport dipole. The analysis demonstrates that clouds play a dual role in both the shortwave and longwave spectra in terms of tropical and midlatitude east-west gradients. The key result is that cloud forcing, although not always the principle regulator of interannual variability of the global climate, serves to reinforce the basic three-cell meridional circulation.

Smith, Eric A.↗
NASA NTRS1990

A neural net approach to space vehicle guidance

The space vehicle guidance problem is formulated using a neural network approach, and the appropriate neural net architecture for modeling optimum guidance trajectories is investigated. In particular, an investigation is made of the incorporation of prior knowledge about the characteristics of the optimal guidance solution into the neural network architecture. The online classification performance of the developed network is demonstrated using a synthesized network trained with a database of optimum guidance trajectories. Such a neural-network-based guidance approach can readily adapt to environment uncertainties such as those encountered by an AOTV during atmospheric maneuvers.

Caglayan, Alper K.↗
NASA NTRS1991

Comparison of polynomial approximations and artificial neural nets for response surfaces in engineering optimization

Engineering optimization problems involve minimizing some function subject to constraints. In areas such as aircraft optimization, the constraint equations may be from numerous disciplines such as transfer of information between these disciplines and the optimization algorithm. They are also suited to problems which may require numerous re-optimizations such as in multi-objective function optimization or to problems where the design space contains numerous local minima, thus requiring repeated optimizations from different initial designs. Their use has been limited, however, by the fact that development of response surfaces randomly selected or preselected points in the design space. Thus, they have been thought to be inefficient compared to algorithms to the optimum solution. A development has taken place in the last several years which may effect the desirability of using response surfaces. It may be possible that artificial neural nets are more efficient in developing response surfaces than polynomial approximations which have been used in the past. This development is the concern of the work.

Carpenter, William C.↗
NASA NTRS1991

Applying generalized stochastic Petri nets to manufacturing systems containing nonexponential transition functions

Generalized stochastic Petri nets (GSPNs) are applied to flexible manufacturing systems (FMSs). Throughput subnets and s-transitions are presented. Two FMS examples containing nonexponential distributions which were analyzed in previous papers by queuing theory and probability theory, respectively, are treated using GSPNs developed using throughput subnets and s-transitions. The GSPN results agree with the previous results, and developing and analyzing the GSPN models are straightforward and relatively easy compared to other methodologies.

Watson, James F., III↗
NASA NTRS1990

Cloud forcing and the net longwave surface radiation

A method is suggested which determines the monthly mean longwave radiation at the surface over the oceans using currently available satellite data sets. An independent estimate of the frequency of occurrence of clouds or cloud top heights is not required. A climatological relationship between the LWCRF (longwave cloud radiation forcing) at the top of the atmosphere and surface may be substituted. This ratio is obtained from a GMC simulation but in principle could be obtained observationally, although global coverage is doubtful. A flow diagram shows the procedure used to obtain maps for the monthly mean net upward longwave flux at the surface.

HARSHVARDHAN↗
NASA NTRS1993

NETS

NETS development tool provides environment for simulation and development of neural networks - computer programs that "learn" from experience. Written in ANSI standard C, program allows user to generate C code for implementation of neural network.

Baffes, Paul T.↗