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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

An Overview of ANN Application in the Power Industry

The paper presents a survey on the development and experience with artificial neural net (ANN) applications for electric power systems, with emphasis on operational systems. The organization and constraints of electric utilities are reviewed, motivations for investigating ANN are identified, and a current assessment is given from the experience of 2400 projects using ANN for load forecasting, alarm processing, fault detection, component fault diagnosis, static and dynamic security analysis, system planning, and operation planning.

artificial neural networks ANN electric power syst↗
NASA NTRSDate not supplied

Artificial Neural Network (ANN) Surface Longwave and Shortwave Fluxes Trained on CERES Observations

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of the radiative fluxes and clouds systems. CERES climate quality data products typically take several months of calibration and validation before release to the public. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed to provide key data for the applied sciences and educational users within a week of observation. FLASHFlux achieves this by using simplified calibration, an operational meteorological product from Global Modeling and Assimilation Office (GMAO), and its own surface parameterizations model. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Terra and NOAA-20 observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1o x 1o gridded data that combines Terra and NOAA-20 observations. Currently, FLASHFlux uses the Langley Parameterized Shortwave Algorithm (LPSA) and Langley Parameterized Longwave Algorithm (LPLA) to derive its surface fluxes (Kratz et al., 2010; Gupta et al, 2001). A new Machine Learning (ML) based approach using Artificial Neural Networks to derive Surface Longwave (LW) & Shortwave (SW) fluxes based on training data from the CERES Clouds Radiative Swath (CRS) product is being investigated to replace LPSA and LPLA in the SSF surface flux products. One of the biggest hurdles in training ML model is model fitting. To overcome the problem of overfitting we use feature engineering that helps in finding the important feature and remove features that are irrelevant to the model. In our training we employed the Leave-One-Feature-Out Importance (LOFO) to evaluate the significance of each feature in our training. We intercompare ANN fluxes against surface fluxes produced from the Fu-Liou model in CRS and the LPSA/LPLA in FLASHFlux SSF. Furthermore, we validated ANN derived fluxes to the Baseline Surface Radiation Network (BSRN).

P C Sawaengphokhai↗
NASA NTRS1993

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Lure, Y. M. Fleming↗
NASA NTRS2021

Follow-up Water Quality Analysis at the Little Patuxent River in Anne Arundel County, Maryland andImpact to the Health of the Chesapeake Bay

In accordance with the federal Clean Water Act, it is of utmost importance to identify impaired water bodies and subsequently implement Total Maximum Daily Loads (TMDL) as needed to achieve desirable water quality standards. One of these water bodies include the Little Patuxent River (LPR) in the Anne Arundel and Howard Counties in Maryland, which is the subject of this report. In the 1996, 1998, and then 2006 Maryland Integrated Report, the LPR was found to be impaired by nutrients, bacteria, suspended sediments, and cadmium (Cd). As a result, TMDLs were created to limit factors that were contributing to these problems (Maryland Department of the Environment 2011, December). But later in 2008 and 2009, water quality analyses (WQAs) found that the LPR’s condition had improved. From a Category 5 Cd and phosphorus classification in 1996 it was reduced to Category 2 in 2008 for Cd and in 2009 for phosphorus (Maryland Department of the Environment 2011, December). However, it has been more than a decade since the last WQA and the environmental conditions may have changed. This lack of testing could result in untracked, accumulated damages to the overall health of the LPR. We present testing results for the 13 site locations on the LPR to evaluate turbidity, pH, phosphates, nitrates, water temperature, dissolved oxygen (D.O.), coliform bacteria, and cadmium concentrations in sediments. We will also present next steps including remediation strategies.

Aaban Syed↗
NASA NTRS1971

International Symposium on Remote Sensing of Environment, 7th, University of Michigan, Ann Arbor, Mich., May 17-21, 1971, Proceedings. Volumes 1, 2 & 3.

The sessions dealt in full detail with basic research in geology and soils; manual interpretation of data on land use, snow, and ice; machine assisted data handling; instrumentation; basic research in water, snow, and ice; manual interpretation of data on vegetation, soils, and geology; user studies and instrumentation; and operational systems. Individual items are abstracted in this issue.

Source record↗
NASA NTRS1973

International Symposium on Remote Sensing of Environment, 8th, University of Michigan, Ann Arbor, Mich., October 2-6, 1972, Proceedings. Volumes 1 & 2.

Recent developments in remote sensing techniques and applications are described in papers dealing with (1) ground-based, airborne, and space-borne sensor systems, (2) machine assisted data analysis and interpretation, and (3) specific uses of sensing techniques by various government units. Topics covered include monitoring of environmental quality factors, delineation of geological formations and mineral deposits, watershed management, observation of vegetative parameters in forestry and agriculture, design and performance details of various sensor systems and equipment, interpretation of multispectral imagery, and applications of ERTS-1 satellite imagery in resource study programs. Individual items are announced in this issue.

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NASA NTRS1974

International Symposium on Remote Sensing of Environment, 9th, University of Michigan, Ann Arbor, Mich., April 15-19, 1974, Proceedings. Volumes 1, 2 & 3

The present work gathers together numerous papers describing the use of remote sensing technology for mapping, monitoring, and management of earth resources and man's environment. Studies using various types of sensing equipment are described, including multispectral scanners, radar imagery, spectrometers, lidar, and aerial photography, and both manual and computer-aided data processing techniques are described. Some of the topics covered include: estimation of population density in Tokyo districts from ERTS-1 data, a clustering algorithm for unsupervised crop classification, passive microwave sensing of moist soils, interactive computer processing for land use planning, the use of remote sensing to delineate floodplains, moisture detection from Skylab, scanning thermal plumes, electrically scanning microwave radiometers, oil slick detection by X-band synthetic aperture radar, and the use of space photos for search of oil and gas fields. Individual items are announced in this issue.

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NASA NTRS1975

International Symposium on Remote Sensing of Environment, 10th, University of Michigan, Ann Arbor, Mich., October 6-10, 1975, Proceedings. Volumes 1 & 2

Topics treated include the application of a Fourier transform spectrometer to infrared remote sensing, the performance optimization of a satellite-borne thematic mapper, a data handling system to be integrated with a digital airborne multispectral scanner, infrared thermography for micro- and mesometeorological measurements, satellite interrogated data collection platforms for river and flood forecasting and the automatic measurement of sea surface temperature from a GOES satellite. Solar and atmospheric effects on satellite imagery derived from aircraft reflectance measurements, methods for determining haze levels from multispectral scanner data, restoration of Landsat images by discrete two-dimensional deconvolution and the automatic classification of aircraft and satellite multispectral images using mixed integer programming are also discussed. Individual items are announced in this issue.

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NASA NTRS1977

International Symposium on Remote Sensing of Environment, 11th, University of Michigan, Ann Arbor, Mich., April 25-29, 1977, Proceedings. Volumes 1 & 2

Consideration is given to remote sensor development and sensor data analysis and interpretation, and to the following fields of application of remote sensors: geology and mineral resources, meteorology, agriculture, forestry and rangeland, ocean and coastal regions, and environmental quality. Attention is also given to economic and institutional issues and technology transfer in the field of remote sensing, to microwave remote sensing and to the current and future role of remote sensing in operational programs.

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NASA NTRS1979

International Symposium on Remote Sensing of Environment, 13th, Ann Arbor, Mich., April 23-27, 1979, Proceedings. Volumes 1, 2 & 3

The presentations document current activities in the field of remote sensing. Papers include those concerned with data collection, processing, and analysis hardware and methodology, as well as the application of this technology to monitoring and managing the earth's resources and man's global environment. Ground-based, airborne, and spaceborne sensor systems and both manual and machine-assisted data analysis and interpretation are considered.

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NASA NTRS1981

International Symposium on Remote Sensing of Environment, 15th, University of Michigan, Ann Arbor, MI, May 11-15, 1981, Proceedings. Volumes 1, 2 & 3

Developments related to advanced sensors and sensor systems are being examined, taking into account advanced aerospace remote sensing systems for global resource applications, spaceborne radar observation of the earth surface, a concept for an advanced earth resources satellite system, technologies for the multispectral mapping of earth resources, and the use of Landsat images and morphologic analogs in space exploration. Other topics discussed are related to modeling for terrain analysis, digital processing and analysis of remotely sensed data, microwave remote sensing, new discoveries from planetary remote sensing, and data base utilization. Advances in the area of luminescence are also considered along with future plans and prospects concerning the remote sensing of the earth from space.

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NASA NTRS1984

International Symposium on Remote Sensing of Environment, 17th, University of Michigan, Ann Arbor, MI, May 9-13, 1983, Proceedings. Volumes 1, 2 & 3

The collection, processing, and analysis of remote-sensing data from ground-based, airborne, and spaceborne instruments for application to the monitoring and management of the earth and environment and resources are examined in reviews and reports, some in summary form. Subject areas covered include US policy and directions on remote sensing (RS); the future of terrestrial RS from space; RS of land, oceans, and atmosphere from a global perspective; RS in hydrological modeling; microprocessing technology; array processors; geobased information systems; artificial intelligence; the Shuttle imaging radar; and current results from Landsat-4. Among the specific topics discussed are RS application to hydrocarbon exploration, airborne gamma-radiation assessment of snow water equivalent, surface-vegetation-biomass modeling from AVHRR and Landsat data, Landsat imagery of Mediterranean pollution, fast two-dimensional filtering of thermal-scanner data, RS of severe convective storms, registration of rotated images by invariant moments, and the geometric accuracy of Landsat-4 Thematic-Mapper P-tapes.

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NASA NTRS1985

Symposium (International) on Combustion, 20th, University of Michigan, Ann Arbor, MI, August 12-17, 1984, Proceedings

The present conference on combustion phenomena considers topics in automotive engine combustion, turbulent reacting flows, the modeling of practical combustion systems, reaction kinetics, combustion-generated particulates, combustion diagnostics, coal combustion process characteristics, fire-related phenomena, explosion/detonation phenomena, spray combustion, ignition/extinction, laminar flames, pollutant formation processes, practical combustor devices, and rocket propellant combustion. Attention is given to the contributions of combustion science to piston engine design, modeling and measurement techniques for turbulent combustion, the specific effects of energy, collisions, and transport processes in combustion chemistry kinetics, the formation of large molecules, particulates and ions in premixed hydrocarbon flames, the application of laser diagnostics to combustion systems, spark ignition energies for dust-air mixtures, the controlling mechanisms of flow-assisted flame spread, the ignition and combustion of coal-water slurries, spontaneous ignition of methane, turbulent and accelerating dust flames, and the temperature sensitivity of double base propellants.

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NASA NTRS1986

International Symposium on Remote Sensing of Environment, 19th, Ann Arbor, MI, October 21-25, 1985, Proceedings. Volumes 1 & 2

The technology and applications of terrestrial remote sensing (RS) are discussed in reviews and reports. Topics examined include the future of the NASA earth-sciences program, NOAA plans for earth observations in the 1990s, space RS in France, international coordination of RS satellite programs, and applications of geocoded imagery. Consideration is given to spatial and tabular databases for order-three soil surveys, an AVHRR and Landsat regional inventory of irrigated agriculture, classification of wetlands, microwave radiometry of ocean surface winds and sea ice, and floodplain land-cover mapping with Thematic-Mapper data.

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NASA NTRS1991

International Symposium on Space Terahertz Technology, 1st, University of Michigan, Ann Arbor, Mar. 5, 6, 1990, Proceedings

Problems, proposed solutions, and recent results related to the development of solid-state oscillators, detectors, mixers, diode multipliers, and antennas at THz frequencies are addressed. Individual topics considered include: submillimeter heterodyne remote sensing of upper atmospheric gases, planar dipole array antenna with an elliptical lens, twin slot antenna structures integrated with microbolometer detectors for 94-GHz imaging. Also discussed are: quantum-well and quantum-barrier diodes for generating submillimeter wave power, planar Schottky barrier mixer diodes for space applications at submillimeter wavelengths, GaAs Schottky barrier varactor diodes for submillimeter wavelength power generation, planar doped barrier devices for subharmonic mixers.

Ulaby, Fawwaz↗
NASA NTRS1992

On the use of ANN interconnection weights in optimal structural design

The present paper describes the use of interconnection weights of a multilayer, feedforward network, to extract information pertinent to the mapping space that the network is assumed to represent. In particular, these weights can be used to determine an appropriate network architecture, and an adequate number of training patterns (input-output pairs) have been used for network training. The weight analysis also provides an approach to assess the influence of each input parameter on a selected output component. The paper shows the significance of this information in decomposition driven optimal design.

Hajela, P.↗
NASA NTRS1994

Innovation and application of ANN in Europe demonstrated by Kohonen maps

One of the most important contributions to neural networks comes from Kohonen, Helsinki/Espoo, Finland, who had the idea of self-organizating maps in 1981. He verified his idea by an algorithm of which many applications make use of. The impetus for this idea came from biology, a field where the Europeans have always been very active at several research laboratories. The challenge was to model the self-organization found in the brain. Today one goal is the development of more sophisticated neurons which model the biological neurons more exactly. They should come to a better performance of neural nets with only a few complex neurons instead of many simple ones. A lot of application concepts arise from this idea: Kohonen himself applied it to speech recognition, but the project did not overcome much more than the recognition of the numerals one to ten at that time. A more promising application for self-organizing maps is process control and process monitoring. Several proposals were made which concern parameter classification of semiconductor technologies, design of integrated circuits, and control of chemical processes. Self-organizing maps were applied to robotics. The neural concept was introduced into electric power systems. At Dortmund we are working on a system which has to monitor the quality and the reliability of gears and electrical motors in equipment installed in coal mines. The results are promising and the probability to apply the system in the field is very high. A special feature of the system is that linguistic rules which are embedded in a fuzzy controller analyze the data of the self-organizing map in regard to life expectation of the gears. It seems that the fuzzy technique will introduce the technology of neural networks in a tandem mode. These technologies together with the genetic algorithms start to form the attractive field of computational intelligence.

Goser, Karl↗